Quality Estimation for Automatically Generated Titles of eCommerce Browse Pages.

At eBay, we are automatically generating a large amount of natural language titles for eCommerce browse pages using machine translation (MT) technology. While automatic approaches can generate millions of titles very fast, they are prone to errors. We therefore develop quality estimation (QE) methods which can automatically detect titles with low quality in order to prevent them from going live. In this paper, we present different approaches: The first one is a Random Forest (RF) model that explores hand-crafted, robust features, which are a mix of established features commonly used in Machine Translation Quality Estimation (MTQE) and new features developed specifically for our task. The second model is based on Siamese Networks (SNs) which embed the metadata input sequence and the generated title in the same space and do not require hand-crafted features at all. We thoroughly evaluate and compare those approaches on in-house data. While the RF models are competitive for scenarios with smaller amounts of training data and somewhat more robust, they are clearly outperformed by the SN models when the amount of training data is larger

Wireless Connectivity of a Ground-and-Air Sensor Network

This paper shows that, when considering outdoor scenarios and wireless communications using the IEEE 802.11 protocol with dipole antennas, the ground reflection is a significant propagation mechanism. This way, the Two-Ray model for this environment allows predicting, with some accuracy, the received signal power. This study is relevant for the application in the communication between overflying Unmanned Aerial Vehicles (UAVs) and ground sensors. In the proposed Wireless Sensor Network (WSN) scenario, the UAVs must receive information from the environment, which is collected by sensors positioned on the ground, and need to maintain connectivity between them and the base station, in order to maintain the quality of service, while moving through the environment.Comment: 8 pages, 11 figure

Towards a Combination of Online and Multitask Learning for MT Quality Estimation: a Preliminary Study.

Quality estimation (QE) for machine translation has emerged as a promising way to provide real-world applications with methods to estimate at run-time the reliability of automatic translations. Real-world applications, however, pose challenges that go beyond those of current QE evaluation settings. For instance, the heterogeneity and the scarce availability of training data might contribute to significantly raise the bar. To address these issues we compare two alternative machine learning paradigms, namely online and multi-task learning, measuring their capability to overcome the limitations of current batch methods. The results of our experiments, which are carried out in the same experimental setting, demonstrate the effectiveness of the two methods and suggest their complementarity. This indicates, as a promising research avenue, the possibility to combine their strengths into an online multi-task approach to the problem

Compatibility studies of Olanzapine pre-formulated with excipients by thermal analysis: preliminary study

Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used to investigate drug-excipient interactions and, in consequence, their compatibility. For this purpose, binary mixtures of olanzapine drug substance and the excipients croscarmellose sodium, magnesium stearate and microcrystalline cellulose, were prepared and analysed. By the analysis of the binary mixtures DSC and TG curves it were observed changes on the temperature and enthalpy values of the drug melting and decomposition peak, with the likely formation of intermediate substances.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Proteomic analysis of total cellular proteins of human neutrophils

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Is there still room to explore cyclodextrin glycosyltransferase-producers in Brazilian biodiversity?

In the present work, different Brazilian biomes aiming to identify and select cyclodextrin glycosyltransferase-producer bacteria are explored. This enzyme is responsible for converting starch to cyclodextrin, which are interesting molecules to carry other substances of economic interest applied by textile, pharmaceutical, food, and other industries. Based on the enzymatic index, 12 bacteria were selected and evaluated, considering their capacity to produce the enzyme in culture media containing different starch sources. It was observed that the highest yields were presented by the bacteria when grown in cornstarch. These bacteria were also characterized by sequencing of the 16S rRNA region and were classified as Bacillus, Paenibacillus, Gracilibacillus and Solibacillus.publishersversionpublishe

Alpinia

Species of the genus Alpinia are widely used by the population and have many described biological activities, including activity against insects. In this paper, we describe the bioactivity of the essential oil of two species of Alpinia genus, A. zerumbet and A. vittata, against Rhodnius nasutus, a vector of Chagas disease. The essential oils of these two species were obtained by hydrodistillation and analyzed by GC-MS. The main constituent of A. zerumbet essential oil (OLALPZER) was terpinen-4-ol, which represented 19.7% of the total components identified. In the essential oil of A. vittata (OLALPVIT) the monoterpene β-pinene (35.3%) was the main constituent. The essential oils and their main constituents were topically applied on R. nasutus fifth-instar nymphs. In the first 10 min of application, OLALPVIT and OLALPZER at 125 μg/mL provoked 73.3% and 83.3% of mortality, respectively. Terpinen-4-ol at 25 μg/mL and β-pinene at 44 μg/mL provoked 100% of mortality. The monitoring of resistant insects showed that both essential oils exhibited antifeedant activity. These results suggest the potential use of A. zerumbet and A. vittata essential oils and their major constituents to control R. nasutus population

Regional differences of testicular artery blood flow in post pubertal and pre-pubertal dogs

Background Measurement of testicular artery blood flow is used in several species to evaluate reproductive function and testicular and scrotal pathology. In dogs there are inconsistent reports about normal flow in post-pubertal dogs and no information concerning pre-pubertal dogs. The aim of this study was to describe regional differences in testicular artery blood flow in clinically normal post-pubertal and pre-pubertal dogs with no history of reproductive tract disease. Results The post-pubertal dogs produced normal ejaculates throughout the study. In all dogs the three different regions of the artery were imaged and monophasic flow with an obvious systolic peak and flow throughout diastole was observed on every occasion. The highest peak systolic velocity (PSV) and end diastolic velocity (EDV) were measured within the distal supra-testicular artery and marginal artery whilst the lowest PSV and EDV were measured within the intra-testicular arteries. Flow measurements were not different between left and right testes and were consistent between dogs on different examination days. Calculated resistance index (RI) and pulsatility index (PI) were lowest in the intra-testicular arteries. The pre-pubertal dogs had significantly smaller testes than the post-pubertal dogs (p < 0.05) and were unable to ejaculate during the study. The three different artery regions were imaged at every examination time point, and flow profiles had a similar appearance to those of the post-pubertal dogs. PSV, EDV, RI and PI showed a similar trend to the post-pubertal dogs in that values were lowest in the intra-testicular arteries. Notably, values of PSV, EDV, RI and PI were significantly lower (p < 0.05) in pre-pubertal dogs compared with post-pubertal dogs. Conclusions This study demonstrated important regional and pubertal differences in testicular artery blood flow of dogs, and form the basis for establishing baseline reference values that may be employed for the purposes of clinical diagnosis

TMop: a Tool for Unsupervised Translation Memory Cleaning

We present TMop, the first open-source tool for automatic Translation Memory (TM) cleaning. The tool implements a fully unsupervised approach to the task, which allows spotting unreliable translation units (sentence pairs in different languages, which are supposed to be translations of each other) without requiring labeled training data. TMop includes a highly configurable and extensible set of filters capturing different aspects of translation quality. It has been evaluated on a test set composed of 1,000 translation units (TUs) randomly extracted from the English-Italian version of MyMemory, a large-scale public TM. Results indicate its effectiveness in automatic removing “bad” TUs, with comparable performance to a state-of-the-art supervised method (76.3 vs. 77.7 balanced accuracy)