Large language models in machine translation

This paper reports on the benefits of largescale statistical language modeling in machine translation. A distributed infrastructure is proposed which we use to train on up to 2 trillion tokens, resulting in language models having up to 300 billion n-grams. It is capable of providing smoothed probabilities for fast, single-pass decoding. We introduce a new smoothing method, dubbed Stupid Backoff, that is inexpensive to train on large data sets and approaches the quality of Kneser-Ney Smoothing as the amount of training data increases.

An incremental approach to automated protein localisation

Tscherepanow M, Jensen N, Kummert F. An incremental approach to automated protein localisation. BMC Bioinformatics. 2008;9(1): 445.Background: The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results: We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion: We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments

Mental health of refugees following state-sponsored repatriation from Germany

von Lersner U, Elbert T, Neuner F. Mental health of refugees following state-sponsored repatriation from Germany. BMC Psychiatry. 2008;8(1): 88.BACKGROUND: In recent years, Voluntary Assisted Return Programmes (VARPs) have received increasing funding as a potential way of reducing the number of refugees in EU member states. A number of factors may affect the mental well-being of returnees. These include adjustment to the home country following return, difficult living conditions, and long-term effects resulting from the severe traumatic stress that had originally driven the affected out of their homes. Little is known about the extent to which these and other factors may promote or inhibit the willingness of refugees to return to their country of origin. The present pilot study investigated refugees who returned to their country of origin after having lived in exile in Germany for some 13 years. METHODS: Forty-seven VARP participants were interviewed concerning their present living conditions, their views of their native country, and their attitudes towards a potential return prior to actually returning. 33 participants were interviewed nine months after returning to their country of origin. Mental health and well-being were assessed using the questionnaires Posttraumatic Stress Diagnostic Scale (PDS) and EUROHIS and the structured Mini International Neuropsychiatric Interview (M.I.N.I.).Our objectives were to examine the mental health status of refugees returning to their home country following an extended period of exile. We also aimed to assess the circumstances under which people decided to return, the current living conditions in their home country, and retrospective returnee evaluations of their decision to accept assisted return. RESULTS: Prior to returning to their home country, participants showed a prevalence rate of 53% for psychiatric disorders. After returning, this rate increased to a sizeable 88%. Substantial correlations were found between the living situation in Germany, the disposition to return, and mental health. For two thirds of the participants, the decision to return was not voluntary. CONCLUSION: Psychological strain among study participants was of a considerable magnitude. As a result of traumatic stress experienced during war and refuge, victims were vulnerable and not well equipped to cope with either post-migration stressors in exile or with a return to their country of origin. It is noteworthy that the majority returned under pressure from immigration authorities. Living conditions after return (such as housing, work, and health care) were poor and unstable. Participants also had great difficulty readapting to the cultural environment after having lived abroad for an average of 13 years. Current VARPs do not take these factors into account and are therefore not able to assist in a humanitarian reintegration of voluntary returnees

Wolbachia endobacteria depletion by doxycycline as antifilarial therapy has macrofilaricidal activity in onchocerciasis: a randomized placebo-controlled study

In a randomized, placebo-controlled trial in Ghana, 67 onchocerciasis patients received 200-mg/day doxycycline for 4–6 weeks, followed by ivermectin (IVM) after 6 months. After 6–27 months, efficacy was evaluated by onchocercoma histology, PCR and microfilariae determination. Administration of doxycycline resulted in endobacteria depletion and female worm sterilization. The 6-week treatment was macrofilaricidal, with >60% of the female worms found dead, despite the presence of new, Wolbachia-containing worms acquired after the administration of doxycycline. Doxycycline may be developed as second-line drug for onchocerciasis, to be administered in areas without transmission, in foci with IVM resistance and in areas with Loa co-infections

Searching the Web by Voice

Spoken queries are a natural medium for searching the Web in settings where typing on a keyboard is not practical. This paper describes a speech interface to the Google search engine. We present experiments with various statistical language models, concluding that a unigram model with collocations provides the best combination of broad coverage, predictive power, and real-time performance. We also report accuracy results of the prototype system

Improving Word Alignment with Bridge Languages

We describe an approach to improve Statistical Machine Translation (SMT) performance using multi-lingual, parallel, sentence-aligned corpora in several bridge languages. Our approach consists of a simple method for utilizing a bridge language to create a word alignment system and a procedure for combining word alignment systems from multiple bridge languages. The final translation is obtained by consensus decoding that combines hypotheses obtained using all bridge language word alignments. We present experiments showing that multilingual, parallel text in Spanish, French, Russian, and Chinese can be utilized in this framework to improve translation performance on an Arabic-to-English task.