New aspects in cationization of lignocellulose materials. IX. Flame retardancy effect of modification with nitrogen and sulfur containing groups

Lignocellulose materials were modified with 3-chlor-2-hydroxypropyltrimethylammoniumchloride, 1,3-bis(3-chlor-2-hydroxypropyl)imidazoliumhydrogensulphate, and 2-chlorethyl-sodiumsulphonate and the flame-retardant properties of materials obtained were studied. The flame-retardant effect was proved using the limited oxygen index (LOI) method and values up to 32.8 vol % of oxygen were determined. The LOI values were higher when the modification was done without using NaOH for activation, but in that case the alkylating groups were not chemically bonded to the material. The NaOH activation was necessary to obtain material with flame-retardant properties stable against washing. No synergistic effects were observed when the material was modified with both nitrogen- and sulfur-containing groups.     

Influence of anionic form on thermooxidation of TMAHP–cellulose

With the help of DTA, DTG elementary analysis of carbonized residues and ESR spectroscopy the influence of anionic form on thermooxidation of trimethylammoniumhydroxyprophyl (TMAHP)–cellulose was studied. At 300°C the percentage of carbon in carbonized residue thermolyzed in oxidative atmosphere is higher than for the sample degraded in inert atmosphere. The percentage of hydrogen decreases simultaneously. The concentration of free radicals in thermolyzed residue also increases due to the presence of oxygen. We propose that oxygen is abstracting the hydrogen atoms from polysaccharide and unpaired electrons on carbon atoms are produced. At 400°C the percentage of carbon in residues prepared at inert atmosphere is higher than for residue formed at oxidative atmosphere. Also the concentration of free radicals in thermolyzed residues obtained in inert atmosphere is greater than for those from oxidative ones. That is why suppose that at this temperature oxygen is bonded to polysaccharide residue and free radicals are terminated. From the semiquantitative DTA we can make the following sequence of samples according to their increasing thermooxidative effect: unmodified cellulose < A–HSO < A–Br^? < A–I^? < A–NO < A–H₂PO < A–CH₃COO^? < A–HCO < A–F^? < A–Cl^?1 < A–OH^p?.     

Making a Clean Sweep of Cultural Heritage

Digitization brings about new ways of analyzing data from cultural heritage areas. Automatic error detection, as input to semiautomatic error correction, is one type of analysis that can be found high on the priority list of cultural heritage data managers and researchers. We describe a general approach to cleaning cultural heritage databases. We present four case studies on databases from different cultural heritage institutions, and describe an information system in which we embed our error detector in a larger framework, enabling researchers to access, check, and correct their data more easily than before.     

Creating a reference data set for the summarization of discussion forum threads

In this paper we address extractive summarization of long threads in online discussion fora. We present an elaborate user evaluation study to determine human preferences in forum summarization and to create a reference data set. We showed long threads to ten different raters and asked them to create a summary by selecting the posts that they considered to be the most important for the thread. We study the agreement between human raters on the summarization task, and we show how multiple reference summaries can be combined to develop a successful model for automatic summarization. We found that although the inter-rater agreement for the summarization task was slight to fair, the automatic summarizer obtained reasonable results in terms of precision, recall, and ROUGE. Moreover, when human raters were asked to choose between the summary created by another human and the summary created by our model in a blind side-by-side comparison, they judged the model’s summary equal to or better than the human summary in over half of the cases. This shows that even for a summarization task with low inter-rater agreement, a model can be trained that generates sensible summaries. In addition, we investigated the potential for personalized summarization. However, the results for the three raters involved in this experiment were inconclusive. We release the reference summaries as a publicly available dataset.     

Parameters of TSMG Process for Y1.5Ba2Cu3O x System with CeO2 Addition

The TSMG process of YBCO bulk superconductors with Y_1.5Ba₂Cu₃O _x composition and 1 wt% CeO₂ addition has been studied. It is shown that the window for isothermal growth of single-crystalline sample grown from Sm123 seed is between 988 ^°C and 1003 ^°C. At lower temperatures of this window, Y123 crystals grow with higher growth rate but the quality of crystals is worse due to the formation of steps at the growth front. During an isothermal dwell at the optimized temperature, the growth of Y123 single-crystal stops due to decreasing peritectic temperature with increasing CuO concentration in the melt. Additional slow cooling 1 ^°C/hour from the temperature of isothermal growth leads to epitaxial growth of Y123 crystal over the entire sample. Only very narrow part at the rim of the sample contains CuO phase and blocky Y123 crystals are formed there due to self-nucleation.     

An ensemble-based system for microaneurysm detection and diabetic retinopathy grading

Reliable microaneurysm detection in digital fundus images is still an open issue in medical image processing. We propose an ensemble-based framework to improve microaneurysm detection. Unlike the well-known approach of considering the output of multiple classifiers, we propose a combination of internal components of microaneurysm detectors, namely preprocessing methods and candidate extractors. We have evaluated our approach for microaneurysm detection in an online competition, where this algorithm is currently ranked as first, and also on two other databases. Since microaneurysm detection is decisive in diabetic retinopathy (DR) grading, we also tested the proposed method for this task on the publicly available Messidor database, where a promising AUC 0.90 ± 0.01 is achieved in a "DR/non-DR"-type classification based on the presence or absence of the microaneurysms.     

Forgetting Exceptions is Harmful in Language Learning

We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for generalization accuracy. We investigate this phenomenon empirically on a selection of benchmark natural language processing tasks: grapheme-to-phoneme conversion, part-of-speech tagging, prepositional-phrase attachment, and base noun phrase chunking. In a first series of experiments we combine memory-based learning with training set editing techniques, in which instances are edited based on their typicality and class prediction strength. Results show that editing exceptional instances (with low typicality or low class prediction strength) tends to harm generalization accuracy. In a second series of experiments we compare memory-based learning and decision-tree learning methods on the same selection of tasks, and find that decision-tree learning often performs worse than memory-based learning. Moreover, the decrease in performance can be linked to the degree of abstraction from exceptions (i.e., pruning or eagerness). We provide explanations for both results in terms of the properties of the natural language processing tasks and the learning algorithms.