Search

This article presents an overview of regulations, guidelines and societal debates in eight member states of the EC about a) embryonic and fetal tissue transplantation (EFTT), and b) the use of human embryonic stem cells (hES cells) for research into cell therapy, including `therapeutic' cloning. There appears to be a broad acceptance of EFTT in these countries. In most countries guidance has been developed. There is a `strong' consensus about some of the central conditions for `good clinical practice' regarding EFTT. International differences concern, amongst others, some of the informed consent issues involved, and the questions whether an intermediary organisation is necessary, whether the methods of abortion may be influenced by the possible use of EFT, and whether EFTT should only be used for the experimental treatment of rare disorders. The potential use of hES cells for research into cell therapy has given a new impetus to the debate about (human) embryo research. The therapeutic prospects with regard to the retrieval and research use of hES cells appear to function as a catalyst for the introduction of less restrictive regulations concerning research with spare embryos, at least in some European countries. It remains to be seen whether the prospect of treating patients suffering from serious disorders with transplants produced by therapeutic cloning will decrease the societal and moral resistance to allowing the generation of embryos for `instrumental' use.

Abstract:: The ac-transport properties of a one-dimensional quantum dot with non-Fermi liquid correlations are investigated. It is found that the linear photoconductance is drastically influenced by the interaction. While for weak interaction it shows peak-like resonances, in the strong interaction regime it assumes a step-like behavior. In both cases the photo-transport provides precise informations about the quantized plasmon modes in the dot. Temperature and voltage dependences of the sideband peaks are treated in detail. Characteristic Luttinger liquid power laws are found.

Die Gewinnung aktiver Kulturfiltrate aus Kulturen des A. clavatus und P. expansum wird beschrieben. Der Einfluß verschiedener äußerer und Ernährungsbedingungen, besonders die Anwesenheit des Kasein und seiner Aminosäuren für das Wachstum und die Hemmstoffbildung von A. clavatus wurden studiert und dabei die günstige Wirkung von Glutaminsäure festgestellt. Aus aktiven Kulturfiltraten der zwei Pilze erfolgt die Isolierung der kristallisierten Hemmstoffe. Die gleichartigen chemischen und biologischen Eigenschaften der Hemmstoffkristane wurden beschrieben und daraus gefolgert, daß es sich in beiden Fällen offenbar um denselben Hemmstoff handelt.

Terrestrial laser scanning (TLS) is providing exciting new ways to quantify tree and forest structure, particularly above-ground biomass (AGB). We show how TLS can address some of the key uncertainties and limitations of current approaches to estimating AGB based on empirical allometric scaling equations (ASEs) that underpin all large-scale estimates of AGB. TLS provides extremely detailed non-destructive measurements of tree form independent of tree size and shape. We show examples of three-dimensional (3D) TLS measurements from various tropical and temperate forests and describe how the resulting TLS point clouds can be used to produce quantitative 3D models of branch and trunk size, shape and distribution. These models can drastically improve estimates of AGB, provide new, improved large-scale ASEs, and deliver insights into a range of fundamental tree properties related to structure. Large quantities of detailed measurements of individual 3D tree structure also have the potential to open new and exciting avenues of research in areas where difficulties of measurement have until now prevented statistical approaches to detecting and understanding underlying patterns of scaling, form and function. We discuss these opportunities and some of the challenges that remain to be overcome to enable wider adoption of TLS methods.

This paper investigates if and to what point it is possible to trade on news sentiment and if deep learning (DL), given the current hype on the topic, would be a good tool to do so. DL is built explicitly for dealing with significant amounts of data and performing complex tasks where automatic learning is a necessity. Thanks to its promise to detect complex patterns in a dataset, it may be appealing to those investors that are looking to improve their trading process. Moreover, DL and specifically LSTM seem a good pick from a linguistic perspective too, given its ability to "remember" previous words in a sentence. After having explained how DL models are built, we will use this tool for forecasting the market sentiment using news headlines. The prediction is based on the Dow Jones industrial average by analyzing 25 daily news headlines available between 2008 and 2016, which will then be extended up to 2020. The result will be the indicator used for developing an algorithmic trading strategy. The analysis will be performed on two specific cases that will be pursued over five time-steps and the testing will be developed in real-world scenarios., (© The Author(s) 2020.)