Real-Time Statistical Speech Translation

This research investigates the Statistical Machine Translation approaches to translate speech in real time automatically. Such systems can be used in a pipeline with speech recognition and synthesis software in order to produce a real-time voice communication system between foreigners. We obtained three main data sets from spoken proceedings that represent three different types of human speech. TED, Europarl, and OPUS parallel text corpora were used as the basis for training of language models, for developmental tuning and testing of the translation system. We also conducted experiments involving part of speech tagging, compound splitting, linear language model interpolation, TrueCasing and morphosyntactic analysis. We evaluated the effects of variety of data preparations on the translation results using the BLEU, NIST, METEOR and TER metrics and tried to give answer which metric is most suitable for PL-EN language pair.Comment: machine translation, polish englis

SemEval-2017 Task 1: semantic textual similarity - multilingual and cross-lingual focused evaluation

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a venue for assessing the current state-of-the-art. The 2017 task focuses on multilingual and cross-lingual pairs with one sub-track exploring MT quality estimation (MTQE) data. The task obtained strong participation from 31 teams, with 17 participating in all language tracks. We summarize performance and review a selection of well performing methods. Analysis highlights common errors, providing insight into the limitations of existing models. To support ongoing work on semantic representations, the STS Benchmark is introduced as a new shared training and evaluation set carefully selected from the corpus of English STS shared task data (2012-2017)

Effect of a single dose of Saccharomyces cerevisiae var. boulardii on the occurrence of porcine neonatal diarrhoea

Piglet neonatal diarrhoea is an important issue in modern pig production and is linked to increased mortality and poor growth rates, affecting long-term pig health, increasing use of medication and cost of production. Saccharomyces cerevisiae var. boulardii (SB) is a probiotic yeast with documented clinical efficacy in the prevention and treatment of diarrhoeal diseases in humans. The objectives of the current study were to evaluate the effect of SB on occurrence and severity of neonatal diarrhoea in piglets, mortality and growth rate. Forty-six litters (606 piglets) were randomly allocated to a control or SB treatment (n=23 per treatment). Within 24 h of farrowing, piglets assigned to the SB treatment received a single oral dose of a paste containing 3.3×109 CFU of SB CNCM I-1079. Piglets from the control litters received a placebo paste. Piglet weight, mortality and diarrhoea were recorded up to day 7 of age. It was shown that numbers of diarrhoea days were significantly correlated with increased mortality rate and reduced weight gain (P<0.05). SB treatment had no effect on growth or mortality in diarrhoeic litters. However, SB-supplemented litters had significantly lower faecal scores, indicating firmer faeces (P<0.01) and fewer numbers of diarrhoeic days (P<0.01) during the 1st week of life. Reduction in the number of diarrhoeic litters compared with the control group was observed following the probiotic administration (P<0.05). These results highlight the detrimental effects of neonatal diarrhoea on pre-weaning performance and suggest that SB, by reducing diarrhoea duration and severity, has the potential of improving enteric health in the early stages of life in pigs

Phrasal: A Toolkit for New Directions in Statistical Machine Translation

We present a new version of Phrasal, an open-source toolkit for statistical phrase-based machine translation. This revision includes features that support emerging re-search trends such as (a) tuning with large feature sets, (b) tuning on large datasets like the bitext, and (c) web-based interactive ma-chine translation. A direct comparison with Moses shows favorable results in terms of decoding speed and tuning time.

Complete experimental toolbox for alignment-free quantum communication

Quantum communication employs the counter-intuitive features of quantum physics to perform tasks that are im- possible in the classical world. It is crucial for testing the foundations of quantum theory and promises to rev- olutionize our information and communication technolo- gies. However, for two or more parties to execute even the simplest quantum transmission, they must establish, and maintain, a shared reference frame. This introduces a considerable overhead in communication resources, par- ticularly if the parties are in motion or rotating relative to each other. We experimentally demonstrate how to circumvent this problem with the efficient transmission of quantum information encoded in rotationally invariant states of single photons. By developing a complete toolbox for the efficient encoding and decoding of quantum infor- mation in such photonic qubits, we demonstrate the fea- sibility of alignment-free quantum key-distribution, and perform a proof-of-principle alignment-free entanglement distribution and violation of a Bell inequality. Our scheme should find applications in fundamental tests of quantum mechanics and satellite-based quantum communication.Comment: Main manuscript: 7 pages, 3 figures; Supplementary Information: 7 pages, 3 figure

A dimensional summation account of polymorphous category learning

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Data and code availaibility: The data and code for all analyses for all experiments are available at the OSF addresses given in each Results section. The stimuli are available at the same locations.Polymorphous concepts are hard to learn, and this is perhaps surprising because they, like many natural concepts, have an overall similarity structure. However, the dimensional summation hypothesis (Milton & Wills, 2004) predicts this difficulty. It also makes a number of other predictions about polymorphous concept formation, which are tested here. In Experiment 1 we confirm the theory’s prediction that polymorphous concept formation should be facilitated by deterministic pretraining on the constituent features of the stimulus. This facilitation is relative to an equivalent amount of training on the polymorphous concept itself. In Experiments 2–4, the dimensional summation account of this single feature pretraining effect is contrasted with some other accounts, including a more general strategic account (Experiment 2), seriality of training and stimulus decomposition accounts (Experiment 3), and the role of errors (Experiment 4). The dimensional summation hypothesis provides the best account of these data. In Experiment 5, a further prediction is confirmed — the single feature pretraining effect is eliminated by a concurrent counting task. The current experiments suggest the hypothesis that natural concepts might be acquired by the deliberate serial summation of evidence. This idea has testable implications for classroom learning.Biotechnology and Biological Sciences Research Council (BBSRC

Drivers for international innovation activities in developed and emerging countries

This paper aims to shed light on firm specific drivers that lead firms to internationalise their innovation activities. The paper draws a comprehensive picture of driving forces by including firm capabilities, characteristics of the firm’s competitive environment and the influence of innovation obstacles in the home country. In particular, the role of the potential driving forces is tested on the probability to carry out different innovative activities abroad (R&D, design/conception of new products, manufacturing of innovative products and implementation of new processes). In a second step these driving forces are used to observe their impact on the decision to locate innovation activities in various countries and regions (China, Eastern Europe, Western Europe and North America) as well as in groups of countries with similar levels of knowledge (country clubs). The analysis is based on the Mannheim Innovation Panel survey which represents the German CIS (Community Innovation Survey) contribution. Two survey waves are combined and result in a sample of about 1400 firms. The results show that the decision to perform innovation activities abroad is mainly driven by organisational capabilities such as absorptive capacities, international experience and existing technological competences of the respective firm. Innovation barriers at the German home base such as lack of labour and high innovation costs foster the set up of later-stage innovation activities abroad while the lack of demand demonstrates a barrier to the internationalisation decision for the development and manufacturing of new products. Location decisions receive the strongest influencing effects from the international experience of the firm. Firms which innovate in developing countries seem to require a more extensive level of international experience by international R&D cooperation

Biogeographical survey of soil microbiomes across sub-Saharan Africa:structure, drivers, and predicted climate-driven changes

BACKGROUND: Top-soil microbiomes make a vital contribution to the Earth’s ecology and harbor an extraordinarily high biodiversity. They are also key players in many ecosystem services, particularly in arid regions of the globe such as the African continent. While several recent studies have documented patterns in global soil microbial ecology, these are largely biased towards widely studied regions and rely on models to interpolate the microbial diversity of other regions where there is low data coverage. This is the case for sub-Saharan Africa, where the number of regional microbial studies is very low in comparison to other continents. RESULTS: The aim of this study was to conduct an extensive biogeographical survey of sub-Saharan Africa’s top-soil microbiomes, with a specific focus on investigating the environmental drivers of microbial ecology across the region. In this study, we sampled 810 sample sites across 9 sub-Saharan African countries and used taxonomic barcoding to profile the microbial ecology of these regions. Our results showed that the sub-Saharan nations included in the study harbor qualitatively distinguishable soil microbiomes. In addition, using soil chemistry and climatic data extracted from the same sites, we demonstrated that the top-soil microbiome is shaped by a broad range of environmental factors, most notably pH, precipitation, and temperature. Through the use of structural equation modeling, we also developed a model to predict how soil microbial biodiversity in sub-Saharan Africa might be affected by future climate change scenarios. This model predicted that the soil microbial biodiversity of countries such as Kenya will be negatively affected by increased temperatures and decreased precipitation, while the fungal biodiversity of Benin will benefit from the increase in annual precipitation. CONCLUSION: This study represents the most extensive biogeographical survey of sub-Saharan top-soil microbiomes to date. Importantly, this study has allowed us to identify countries in sub-Saharan Africa that might be particularly vulnerable to losses in soil microbial ecology and productivity due to climate change. Considering the reliance of many economies in the region on rain-fed agriculture, this study provides crucial information to support conservation efforts in the countries that will be most heavily impacted by climate change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01297-w

The importance of interacting climate modes on Australia’s contribution to global carbon cycle extremes

The global carbon cycle is highly sensitive to climate-driven fluctuations of precipitation, especially in the Southern Hemisphere. This was clearly manifested by a 20% increase of the global terrestrial C sink in 2011 during the strongest sustained La Niña since 1917. However, inconsistencies exist between El Niño/La Niña (ENSO) cycles and precipitation in the historical record; for example, significant ENSO-precipitation correlations were present in only 31% of the last 100 years, and often absent in wet years. To resolve these inconsistencies, we used an advanced temporal scaling method for identifying interactions amongst three key climate modes (El Niño, the Indian Ocean dipole, and the southern annular mode). When these climate modes synchronised (1999-2012), drought and extreme precipitation were observed across Australia. The interaction amongst these climate modes, more than the effect of any single mode, was associated with large fluctuations in precipitation and productivity. The long-term exposure of vegetation to this arid environment has favoured a resilient flora capable of large fluctuations in photosynthetic productivity and explains why Australia was a major contributor not only to the 2011 global C sink anomaly but also to global reductions in photosynthetic C uptake during the previous decade of drought

Assay platform for clinically relevant metallo-beta-lactamases

Metallo-β-lactamases (MBLs) are a growing threat to the use of almost all clinically used β-lactam antibiotics. The identification of broad-spectrum MBL inhibitors is hampered by the lack of a suitable screening platform, consisting of appropriate substrates and a set of clinically relevant MBLs. We report procedures for the preparation of a set of clinically relevant metallo-β-lactamases (i.e., NDM-1 (New Delhi MBL), IMP-1 (Imipenemase), SPM-1 (São Paulo MBL), and VIM-2 (Verona integron-encoded MBL)) and the identification of suitable fluorogenic substrates (umbelliferone-derived cephalosporins). The fluorogenic substrates were compared to chromogenic substrates (CENTA, nitrocefin, and imipenem), showing improved sensitivity and kinetic parameters. The efficiency of the fluorogenic substrates was exemplified by inhibitor screening, identifying 4-chloroisoquinolinols as potential pan MBL inhibitors