Open Access

On April, 23rd 2007 a series of postings started on Infobib.de, where guest authors from all over the world introduced the library and library related blogs of their own country. This book is a collection of 30 revised LibWorld articles, accompanied by a foreword by Walt Crawford. Included are articles about the blogosphere of: Argentina, Australia, Austria, Belarus, Belgium, Brazil, Canada, Denmark, Finland, France, Greece, Hungary, Iran, Italy, Japan, Latvia, Malawi, Netherlands, New Zealand, Norway, Peru, Puerto Rico, Russia, Singapore, Spain, Sweden, Switzerland, Trinidad & Tobago, USA.

The IfBB – Institute for Bioplastics and Biocomposites is a research institute within the Hochschule Hannover, University of Applied Sciences and Arts, which was established in 2011 to respond to the growing need for expert knowledge in the area of bioplastics. With its practice-oriented research and its collaboration with industrial partners, the IfBB is able to shore up the market for bioplastics and, in addition, foster unbiased public awareness and understanding of the topic. As an independent research-led expert institution for bioplastics, the IfBB is willing to share its expertise, research findings and data with any interested party via the Internet, online and offline publications or at fairs and conferences. In carrying on these efforts, substantial information regarding market trends, processes and resource needs for bioplastics is being presented here in a concise format, in addition to the more detailed and comprehensive publication and “Engineering Biopolymers”1. One of our main concerns is to furnish a more rational basis for discussing bioplastics and use fact-based arguments in the public discourse. Furthermore, “Biopolymers – facts and statistics” aims to provide specific, qualified answers easily and quickly for decision-makers in particular from public administration and the industrial sector. Therefore, this publication is made up like a set of rules and standards and largely foregoes textual detail. It offers extensive market-relevant and technical facts presented in graphs and charts, which means that the information is much easier to grasp. The reader can expect comparative market figures for various materials, regions, applications, process routes, agricultural land use or resource consumption, production capacities, geographic distribution, etc.

Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.

In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.

Background: After kidney transplantation, immunosuppressive therapy causes impaired cellular immune defense leading to an increased risk of viral complications. Trough level monitoring of immunosuppressants is insufficient to estimate the individual intensity of immunosuppression. We have already shown that virus-specific T cells (Tvis) correlate with control of virus replication as well as with the intensity of immunosuppression. The multicentre IVIST01-trial should prove that additional steering of immunosuppressive and antiviral therapy by Tvis levels leads to better graft function by avoidance of over-immunosuppression (for example, viral infections) and drug toxicity (for example, nephrotoxicity). Methods/design: The IVIST-trial starts 4 weeks after transplantation. Sixty-four pediatric kidney recipients are randomized either to a non-intervention group that is only treated conservatively or to an intervention group with additional monitoring by Tvis. The randomization is stratified by centre and cytomegalovirus (CMV) prophylaxis. In both groups the immunosuppressive medication (cyclosporine A and everolimus) is adopted in the same target range of trough levels. In the non-intervention group the immunosuppressive therapy (cyclosporine A and everolimus) is only steered by classical trough level monitoring and the antiviral therapy of a CMV infection is performed according to a standard protocol. In contrast, in the intervention group the dose of immunosuppressants is individually adopted according to Tvis levels as a direct measure of the intensity of immunosuppression in addition to classical trough level monitoring. In case of CMV infection or reactivation the antiviral management is based on the individual CMV-specific immune defense assessed by the CMV-Tvis level. Primary endpoint of the study is the glomerular filtration rate 2 years after transplantation; secondary endpoints are the number and severity of viral infections and the incidence of side effects of immunosuppressive and antiviral drugs. Discussion: This IVIST01-trial will answer the question whether the new concept of steering immunosuppressive and antiviral therapy by Tvis levels leads to better future graft function. In terms of an effect-related drug monitoring, the study design aims to realize a personalization of immunosuppressive and antiviral management after transplantation. Based on the IVIST01-trial, immunomonitoring by Tvis might be incorporated into routine care after kidney transplantation.