Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Unsupervised Parsing Beyond English

Recently, neural network models which automatically infer syntactic structure from raw text have started to achieve promising results. However, earlier work on unsupervised parsing shows large performance differences between non-neural models trained on corpora in different languages, even for comparable amounts of data. With that in mind, we train instances of the PRPN architecture (Shen et al., 2018)—one of these unsupervised neural network parsers—for Arabic, Chinese, English, and German. We find that (i) the model strongly outperforms trivial baselines and, thus, acquires at least some parsing ability for all languages; (ii) good hyperparameter values seem to be universal; (iii) how the model benefits from larger training set sizes depends on the corpus, with the model achieving the largest performance gains when increasing the number of sentences from 2,500 to 12,500 for English. In addition, we show that, by sharing parameters between the related languages German and English, we can improve the model’s unsupervised parsing F1 score by up to 4% in the low-resource setting.
Image Search in Social Websites Using Tags and Re-Ranking Method

In recent years, we have observed the achievement of social media websites. This image search method by using tags and re ranking is a technique, which is used for easy access for images. Online networking sites like Flickr will allow the users to comment on images along with the label. This will improve the web image discovery and affiliation. In this paper we introduce a social re-positioning framework for tag-based images with image importance and high quality. We give the position of images by taking their visual data, semantic data, and social signs into consideration. This will result in an appropriate manner for the social clients. Every user will share some images, here we sort these images between the users by repositioning them. Users who have higher commitment will be ranked high. In this point we successfully tell about intra-client re-positioning on the user’s set of images. The most pertinent images will be chosen from every user and these images will be put as an image dataset to quicken the procedure. Test on this dataset demonstrate that our social re-positioning technique is successful and effective.
The role of personality and attentional control in a brief mindfulness intervention for subclinical anxiety

Past research has shown that mindfulness as a long-term treatment can reduce clinical anxiety, but less is known about the efficacy of short-term mindfulness interventions for subclinical anxiety. The current study investigated the efficacy of a brief mindfulness intervention in an unselected college sample. We hypothesized that our mindfulness intervention would reduce anxiety, and that this effect would be mediated by improvement in attentional control. In addition, we hypothesized that personality would impact the efficacy of mindfulness training. Specifically, we expected that neuroticism would moderate the effect of mindfulness training on changes in anxiety, whereas conscientiousness would reduce anxiety by increasing improvements in mindfulness. Thirty-six college students completed a week of at-home mindfulness training. Before and after training, participants completed a laboratory session involving assessment of state anxiety, anxious reactivity to an auditory stressor, mindfulness, and attentional control. The short-term mindfulness training appeared efficacious, as participants showed increases in mindfulness and reductions in anxious reactivity from preto posttraining. Further, there was a dose-response relationship between improvements in mindfulness and reductions in anxiety that was partially mediated by improvements in attentional control. No significant effects of personality on the effectiveness of training were found. Results imply that short-term mindfulness treatment may be beneficial for everyday anxiety in college students. Findings are also discussed in terms of possible implications for prophylactic mindfulness treatments on college campuses.
A Label Informative Wide & Deep Classifier for Patents and Papers

In this paper, we provide a simple and effective baseline for classifying both patents and papers to the well-established Cooperative Patent Classification (CPC). We propose a label-informative classifier based on the Wide & Deep structure, where the Wide part encodes string-level similarities between texts and labels, and the Deep part captures semantic-level similarities via non-linear transformations. Our model trains on millions of patents, and transfers to papers by developing distant-supervised training set and domain-specific features. Extensive experiments show that our model achieves comparable performance to the state-of-the-art model used in industry on both patents and papers. The output of this work should facilitate the searching, granting and filing of innovative ideas for patent examiners, attorneys and researchers.
Finite Sample and Optimal Inference in Possibly Nonstationary ARCH Models with Gaussian and Heavy-Tailed Errors

Most of the literature on testing ARCH models focuses on the null hypothesis of no-ARCH effects. In this paper, we consider the general problem of testing any possible set of coefficient values in ARCH models, which may be non-stationary, with Gaussian and non-Gaussian errors, as well as with any number exogenous regressors in the mean equation. Both Engle-type and point-optimal tests are studied. Special problems considered include the hypothesis of no-ARCH effects and IARCH structure. We propose exact inference based on pivotal Monte Carlo tests [as in Dufour and Kiviet (1996, 1998) and Dufour, Khalaf, Bernard and Genest (2004)] and maximised Monte Carlo tests [Dufour (2004))], depending on whether nuisance parameters are present. This will allow the introduction of dynamics in the mean equation as well. We show that the method suggested provides provably valid tests in both finite and large samples, in cases where standard asymptotic and bootstrap methods may fail in the presence of heavy-tailed errors [as shown by Hall and Yao (2003)]. The performance of the proposed procedures with both Gaussian and non-Gaussian errors is analyzed in a simulation experiment. Our results show that the proposed procedures work well from the viewpoints of size and power. The powers gains provided by the point optimal procedures are in many cases spectacular. The tests also exhibit good behaviour outside the stationarity region [following the work of Jensen and Rahbek (2004)]. Finally, the technique is applied to the US inflation
Supplementary Materials for Two-variable Block Dual Coordinate Descent Methods for Large-scale Linear Support Vector Machines

This is clearly more complicated. To reduce the number of accesses of data, we find that combining both (i) and (ii) with (iii) can reduce the computational time. The following setting computes (i)-(iii) all together. while t1 < n or t2 < n then if t1 = t2 then wxi ← wxi +wt1(xi)t1 wxj ← wxj +wt2(xj)t2 xi xj ← xi xj + (x1)t1(xj)t2 t1 ← next(xi), t2 ← next(xj) else if t1 > t2 then wxj ← wxj +wt2(xj)t2 t2 ← next(xj) else wxi ← wxi +wt1(xi)t1
Effect of chelated minerals supplementation on growth and reproductive performance of Murrah buffalo heifers

Title of Thesis : Effect of Chelated Minerals Supplementation on Growth and Reproductive Performance of Murrah Buffalo Heifers Full Name of the Degree Holder : Anuradha Verma Admission Number : 2015V13M Title of the Degree : Master of Veterinary Science in Livestock Production Management Name of Discipline : Livestock Production Management Name and Address of Major Advisor : Dr.S. K.Chikkara, Principal Scientist, Deptt. of, Livestock Production Management LUVAS, Hisar, Haryana (India). 125004 Degree Awarding University LUVAS, Hisar Year of Award of Degree : 2017 Major Subject : Livestock Production Management Total Number of Pages in Thesis : 48 + vii Number of Words in Abstract : 337
Genetic Approaches for the Identification of Genes Involved in the Pathogenesis of Bacterial Infections in Fish

Over the last 15 years new approaches have been developed for the identification and study of the functions of genes and proteins involved in the virulence mechanisms of bacteria. Some of these approaches are based on the identification of genes required by the bacteria to survive and grow inside the host. Most of these techniques have recently been applied to bacterial fish pathogens successfully. Some of these techniques involve the “In vivo expression technology (IVET)”, which identifies specific promoters expressed in bacteria grown inside the fish body but not in conventional culture media; “Signature-tagged mutagenesis (STM)”, a useful tool for the screening of null mutants which show a decreased virulence capability in the host; and “Suppression Subtractive Hybridisation (SSH)”, a genomewide technology, which enables the identification of genes present only in virulent strains of bacteria or the identification of genes expressed only inside the fish host. This paper reviews the application of these techniques to important pathogenic bacteria for the aquaculture field. _____________________________________________________________________________________________________________
Defining and using novel milk composition based heat stress resilience traits in the context of genomic selection for more robust dairy cows in Wallonia

Recent research showed the usefulness of using estimated breeding values (EBV) for mid-infrared (MIR) based biomarkers in genetic improvement. A novel class of biomarkers was defined based on modelling responses of milk composition (e.g., mid-infrared (MIR) based) to stress expressed on continuous scales using reaction norm models. Heat stress is an important aspect of dairy production even in temperate climates as shown in recent studies. Implementation of genomic selection for tolerance to heat stress is therefore not only an issue for Australian dairy cattle, a country that recently introduced such an evaluation. The question remains open if using milk composition based heat stress resilience genomically enhanced EBV (GEBV) is not a viable option. Genetic parameters were estimated for production, udder health, and milk composition traits. Data included 155,977 test-day records for milk, fat, and protein yields, fat and protein percentages, 9 individual milk fatty acids (FA), 7 FA groups, 5 minerals, and 3 ketone bodies predicted by mid-infrared spectrometry, and 7 FA groups. Data were from 21,375 first-lactation Holstein cows in 473 herds in the Walloon region of Belgium and were collected between 2008 and 2014. Test-day records were merged with daily temperature-humidity index (THI) values based on meteorological records from public weather stations. The maximum distance between each farm and its corresponding weather station was 13 km. Linear reaction norm models were used to estimate the intercept and slope responses of 23 traits to increasing THI values. Most yield and FA traits had phenotypic and genetic declines as THI increased, whereas C18:0, C18:1 cis-9, and 4 FA groups (unsaturated FA, monounsaturated FA, polyunsaturated FA, and long-chain FA) increased with THI. Moreover, the latter traits had the largest slope-to-intercept genetic variance ratios, which indicate that they are more affected by heat stress at high THI levels, and therefore good candidate traits. Among all traits, C18:1 cis-9 was the most sensitive to heat stress. As this trait is known to reflect body reserve mobilization, using its response to THI could be a very affordable milk biomarker of heat stress for dairy cattle, expressing the equilibrium between intake and mobilization, and therefore adaptation, under warm conditions. By including novel milk based composition traits to traditional production traits, correlations between EBVs and GEBVs of those milk based traits and udder health, fertility and longevity increased considerably. This study demonstrated that milk composition resilience heat stress traits could be used
On the three‐dimensional instability of elliptical vortex subjected to stretching

It is known that two‐dimensional vortices are subject to generic three‐dimensional instabilities. This phenomenon is located near the core of vortices and depends on the eccentricity of their streamlines. In this paper we are concerned with the modification of this instability when stretching is applied to such vortices. We describe this instability by linearizing the Navier–Stokes equations around a basic state, which is an exact time‐dependent solution. The complete system for the perturbations is reduced to a single equation for the perturbed velocity along the vortex span. In the limit of weak stretching, a perturbation theory can be performed and leads to a WKBJ approximation for the solution. This procedure demonstrates that a small amount of stretching is able to prevent the appearance of three‐dimensional instabilities for vortices with a low enough eccentricity. Since most vortices are slightly elliptical in turbulent flows, the above computations are expected to cover a wide range of experimental cases. In particular, it is tentatively argued that this mechanism may explain recent experimental observations [Phys. Fluids 7, 630 (1995)].
NONHOLONOMIC MOTION PLANNING USING TRIGONOMETRIC SWITCH INPUTS

Abstract In this paper we present a local motion planning law called trigonometric switch inputs which can steer the chained form system to the final positions, at least locally, around the initial positions. This method steers the system step by step instead of steering all states in one step. The advantages of trigonometric switch inputs law are that the motion trajectories are quite smooth and have less oscillation and lower computational costs, all of which is beneficial for the application of the time scale transformation technique and improvement of motion efficiency of the system. A two-wheeled mobile robot system is steered by this new motion planning law to illustrate the practical application. Finally, simulations with the time scale transformation technique and experiments with the mobile robot verify the feasibility and effectiveness of trigonometric switch inputs law. (Received, processed and accepted by the Chinese Representative Office.)
Training Simulator for Rolling Mill Maintenance

The development of a real-time simulation for operator training is presented. The operation of a rolling mill incorporates the procedure of the roll exchange, which is performed autonomously under the control of the automation system. In exception situations, the maintenance personnel have to finish the complex procedure. To enhance the training skills independently from the real machine, a training simulator was developed. The structure of the hardware and software system is presented, and a way to estimate the development effort is given. The system proved its suitability for training in practice and brought remarkable benefits for the rolling mill maintenance.
AWARD NUMBER: W81XWH-14-1-0255 TITLE: BIOENERGETICS OF STROMAL CELLS AS A PREDICTOR OF AGGRESSIVE PROSTATE CANCER

Mitochondrial function is influenced by alterations in oncogenes and tumor suppressor genes and changes in the microenvironment occurring during tumorigenesis. Therefore, we hypothesized that mitochondrial function will be stably and dynamically altered at each stage of the prostate tumor development. We tested this hypothesis in RWPE-1 cells and its tumorigenic clones with progressive malignant characteristics (RWPE-1 < WPE-NA22 < WPE-NB14 < WPE-NB11 < WPE-NB26) using high-throughput respirometry. Our studies demonstrate that mitochondrial content do not change with increasing malignancy. In premalignant cells (WPE-NA22 and WPE-NB14), OXPHOS is elevated in presence of glucose or glutamine alone or in combination compared to RWPE-1 cells and decreases with increasing malignancy. Glutamine maintained higher OXPHOS than glucose and suggests that it may be an important substrate for the growth and proliferation of prostate epithelial cells. Glycolysis significantly increases with malignancy and follow a classical Warburg phenomenon. Fatty acid oxidation (FAO) is significantly lower in tumorigenic clones and invasive WPE-NB26 does not utilize FAO at all. In this paper, we introduce for the first time the mitochondrial oncobioenergetic index (MOBI), a mathematical representation of oncobioenergetic profile of a cancer cell, which increases significantly upon transformation into localized premalignant form and rapidly falls below the normal as they become aggressive in prostate tumorigenesis. We have validated this in five prostate cancer cell lines and MOBI appears to be not related to androgen dependence or mitochondrial content, but rather dependent on the stage of the cancer. Altogether, we propose that MOBI could be a potential biomarker to distinguish aggressive cancer from that of indolent disease.
University of Groningen Sentiment Recognition in Egocentric Photostreams

Lifelogging is a process of collecting rich source of information about daily life of people. In this paper, we introduce the problem of sentiment analysis in egocentric events focusing on the moments that compose the images recalling positive, neutral or negative feelings to the observer. We propose a method for the classification of the sentiments in egocentric pictures based on global and semantic image features extracted by Convolutional Neural Networks. We carried out experiments on an egocentric dataset, which we organized in 3 classes on the basis of the sentiment that is recalled to the user (positive, negative or neutral).
WST 50.6-098 corr

Reetha (Sapindus trifoliata) seed extract and Chitosan were used as additives in the sludge bed of a UASB reactor treating low strength wastewater to enhance granulation. Five parallel laboratory scale UASB reactors were operated for 250 days with synthetic wastewater feed containing COD in the range of 600–800 mg/L. The reactors were seeded with spent sludge from a full-scale 5MLD UASB treatment plant at Jajmau, Kanpur, India. The seed sludge contained little or no granules. Different additives in the five reactors were as follows: control with no additive, cationic part of Reetha extract as additive, anionic part of Reetha extract as additive, bulk Reetha extract as additive and Chitosan as additive. The granulation rapidly increased in all the reactors beyond the 90th day of operation. The mean granule sizes as well as the fraction of granular sludge (particle size ≥ 100 μm) were more in the presence of some of the additives compared to the control reactor. Chitosan significantly enhanced granulation followed by the cationic and anionic fractions of the Reetha extract. The bulk Reetha extract did not show enhancement of granulation. The ESEM/EDAX results showed that the bigger granules (3–4 mm) had porous structure and appeared as conglomerates of smaller granules.
Important features of talent coaches for talent development in sports

Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. Important features of talent coachers for talent development in sports Autor(es): Ark, Mathijs van; Elferink-Gemser, Marije T; Roskam, Ad; Visscher, Chris Publicado por: Imprensa da Universidade de Coimbra URL persistente: URI:http://hdl.handle. net/10316.2/31714 DOI: DOI:http://dx.doi. org/10.14195/978-989-26-0506-7_12
Learning to Order Graph Elements with Application to Multilingual Surface Realization

Recent advances in deep learning have shown promises in solving complex combinatorial optimization problems, such as sorting variable-sized sequences. In this work, we take a step further and tackle the problem of ordering the elements of sequences that come with graph structures. Our solution adopts an encoder-decoder framework, in which the encoder is a graph neural network that learns the representation for each element, and the decoder predicts the ordering of each local neighborhood of the graph in turn. We apply our framework to multilingual surface realization, which is the task of ordering and completing sentences with their dependency parses given but without the ordering of words. Experiments show that our approach is much better for this task than prior works that do not consider graph structures. We participated in 2019 Surface Realization Shared Task (SR’19), and we ranked second out of 14 teams while outperforming those teams below by a large margin.
VEGF-A and Tenascin-C produced by S100A4[superscript +] stromal cells are important for metastatic colonization

Increased numbers of S100A4 + cells are associated with poor prognosis in patients who have cancer. Although the metastatic capabil- itiesofS100A4 + cancercells havebeen examined,the functionalrole of S100A4 + stromal cells in metastasis is largely unknown. To study the contribution of S100A4 + stromal cells in metastasis, we used transgenic mice that express viral thymidine kinase under control of the S100A4 promoter to speci ﬁ cally ablate S100A4 + stromal cells. Depletion of S100A4 + stromal cells signi ﬁ cantly reduced metastatic colonization without affecting primary tumor growth. Multiple bone marrow transplantation studies demonstrated that these effects of S100A4 + stromal cells are attributable to local non – bone marrow-derived S100A4 + cells, which are likely ﬁ broblasts in this setting. Reduction in metastasis due to the loss of S100A4 + ﬁ broblasts correlated with a concomitant decrease in the expression of several ECM molecules and growth factors, particularly Tenascin-C and VEGF-A. The functional importance of stromal Tenascin-C and S100A4 + ﬁ broblast-derived VEGF-Ain metastasis was established by examining Tenascin-C null mice and transgenic mice expressing Cre recombinase under control of the S100A4 promoter crossed with mice carrying VEGF-A alleles ﬂ anked by loxP sites, which exhibited a signi ﬁ cant decrease in metastatic colonization without effects on primary tumor growth. In particular, S100A4 + ﬁ broblast-derived VEGF-A plays an important role in the establishment of an angio- genic microenvironment at the metastatic site to facilitate colonization, whereas stromal Tenascin-C may provide protection from apoptosis. Our study demonstrates a crucial role for local S100A4 + ﬁ broblasts in providing the permissive “ soil ” for metastatic colonization, a challenging step in the metastatic cascade.