Miracle-dz/UniFAR-FTUs huggingface dataset:
Spanish FreeLing Dependency Grammar

This paper presents the development of an open-source Spanish Dependency Grammar implemented in FreeLing environment. This grammar was designed as a resource for NLP applications that require a step further in natural language automatic analysis, as is the case of Spanish-to-Basque translation. The development of wide-coverage rule-based grammars using linguistic knowledge contributes to extend the existing Spanish deep parsers collection, which sometimes is limited. Spanish FreeLing Dependency Grammar, named EsTxala, provides deep and robust parse trees, solving attachments for any structure and assigning syntactic functions to dependencies. These steps are dealt with hand-written rules based on linguistic knowledge. As a result, FreeLing Dependency Parser gives a unique analysis as a dependency tree for each sentence analyzed. Since it is a resource open to the scientific community, exhaustive grammar evaluation is being done to determine its accuracy as well as strategies for its manteinance and improvement. In this paper, we show the results of an experimental evaluation carried out over EsTxala in order to test our evaluation methodology.
Object identity as a query language primitive

We demonstrate the power of object identities (oid's) as a database query language primitive. We develop an object-based data model, whose structural part generalizes most of the known complex-object data models: cyclicity is allowed in both its schemas and instances. Our main contribution is the operational part of the data model, the query language IQL, which uses oid's for three critical purposes: (1) to represent data-structures with sharing and cycles, (2) to manipulate sets and (3) to express any computable database query. IQL can be statically type checked, can be evaluated bottom-up and naturally generalizes most popular rule-based database languages. The model can also be extended to incorporate type inheritance, without changes to IQL. Finally, we investigate an analogous value-based data model, whose structural part is founded on regular infinite trees and whose operational part is IQL.
Combined Multidimensional Microscopy as a Histopathology Imaging Tool

Herein, we present a highly versatile bioimaging workflow for the multidimensional imaging of biological structures across vastly different length scales. Such an approach allows for the optimised preparation of samples in one go for consecutive X‐ray micro‐computed tomography, bright‐field light microscopy and backscattered scanning electron microscopy, thus, facilitating the disclosure of combined structural information ranging from the gross tissue or cellular level, down to the nanometre scale. In this current study, we characterize various aspects of the hepatic vasculature, ranging from such large vessels as branches of the hepatic portal vein and hepatic artery, down to the smallest sinusoidal capillaries. By employing high‐resolution backscattered scanning electron microscopy, we were able to further characterize the subcellular features of a range of hepatic sinusoidal cells including, liver sinusoidal endothelial cells, pit cells and Kupffer cells. Above all, we demonstrate the capabilities of a specimen manipulation workflow that can be applied and adapted to a plethora of functional and structural investigations and experimental models. Such an approach harnesses the fundamental advantages inherent to the various imaging modalities presented herein, and when combined, offers information not currently available by any single imaging platform. J. Cell. Physiol. 232: 249–256, 2017. © 2016 Wiley Periodicals, Inc.
An Empirical Study of Speech Recognition Errors in a Task-Oriented Dialogue System

The development of spoken dialogue systems is often limited by the performance of their speech recognition component. The impact of speech recognition errors on dialogue systems is often studied at the global level of task completion. In this paper, we carry an empirical study on the consequences of speech recognition errors on a fully-implemented dialogue prototype, based on a speech acts formalisms. We report the impact of speech recognition errors on speech act identification and discuss how standard control mechanisms can participate to robustness by assisting the user in repairing the consequences of speech recognition errors.
User Feedback System for Emergency Alarms in Mobile Health Networks

Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.
Soybean SAT1 (Symbiotic Ammonium Transporter 1) encodes a bHLH transcription factor involved in nodule growth and NH4+ transport

Significance The legume/rhizobia symbiosis involves a root-based exchange of bacterial fixed nitrogen for plant-derived photosynthetic carbon. The exchange takes place within the legume root nodule, which is a specialized root tissue that develops in response to plant and bacterial signal exchange. The bacteria reside within plant cells inside the nodule. In this study, we explore the activity of a membrane-bound soybean transcription factor, Glycine max basic–helix-loop–helix membrane 1, which is important for soybean nodule growth and is linked to the activity of a unique class of ammonium channels and to signaling cascades influencing a nodule circadian clock. Glycine max symbiotic ammonium transporter 1 was first documented as a putative ammonium (NH4+) channel localized to the symbiosome membrane of soybean root nodules. We show that Glycine max symbiotic ammonium transporter 1 is actually a membrane-localized basic helix–loop–helix (bHLH) DNA-binding transcription factor now renamed Glycine max bHLH membrane 1 (GmbHLHm1). In yeast, GmbHLHm1 enters the nucleus and transcriptionally activates a unique plasma membrane NH4+ channel Saccharomyces cerevisiae ammonium facilitator 1. Ammonium facilitator 1 homologs are present in soybean and other plant species, where they often share chromosomal microsynteny with bHLHm1 loci. GmbHLHm1 is important to the soybean rhizobium symbiosis because loss of activity results in a reduction of nodule fitness and growth. Transcriptional changes in nodules highlight downstream signaling pathways involving circadian clock regulation, nutrient transport, hormone signaling, and cell wall modification. Collectively, these results show that GmbHLHm1 influences nodule development and activity and is linked to a novel mechanism for NH4+ transport common to both yeast and plants.
Using Fano Plane and Image Centroids for Rotation, Scaling, or Translation Resistant Watermarking

Analyzing the contents of an image and retrieving corresponding semantics are important in semantic-based image retrieval system. In this paper, we apply the independent component analysis (ICA) to extract significant image features and then incorporated it with the proposed Two-phase Fuzzy Adaptive Resonance Theory Neural Network (Fuzzy-ARTNN) for image content classification. In general, Fuzzy-ARTNN is an unsupervised classifier. Meanwhile, the training patterns in image content analysis are labeled with corresponding categories. This category information is useful for supervised learning. Thus, a supervised learning mechanism is added to label the category of the cluster centers derived by the Fuzzy-ART. The experimental results show that the proposed method has a high accuracy for semantic-based photograph analysis, and the result of photograph analysis is similar to perception of the human eyes.
DNA methylation is a primary mechanism for silencing postmigratory primordial germ cell genes in both germ cell and somatic cell lineages

DNA methylation is necessary for the silencing of endogenous retrotransposons and the maintenance of monoallelic gene expression at imprinted loci and on the X chromosome. Dynamic changes in DNA methylation occur during the initial stages of primordial germ cell development; however, all consequences of this epigenetic reprogramming are not understood. DNA demethylation in postmigratory primordial germ cells coincides with erasure of genomic imprints and reactivation of the inactive X chromosome, as well as ongoing germ cell differentiation events. To investigate a possible role for DNA methylation changes in germ cell differentiation, we have studied several marker genes that initiate expression at this time. Here, we show that the postmigratory germ cell-specific genes Mvh, Dazl and Scp3 are demethylated in germ cells, but not in somatic cells. Premature loss of genomic methylation in Dnmt1 mutant embryos leads to early expression of these genes as well as GCNA1, a widely used germ cell marker. In addition, GCNA1 is ectopically expressed by somatic cells in Dnmt1 mutants. These results provide in vivo evidence that postmigratory germ cell-specific genes are silenced by DNA methylation in both premigratory germ cells and somatic cells. This is the first example of ectopic gene activation in Dnmt1 mutant mice and suggests that dynamic changes in DNA methylation regulate tissue-specific gene expression of a set of primordial germ cell-specific genes.
Signal Sampling and Recovery Under Dependent Errors

The paper examines the impact of the additive correlated noise on the accuracy of the signal reconstruction algorithm originating from the Whittaker-Shannon (WS) sampling interpolation formula. A class of band-limited signals as well as signals which are non-band-limited are taken into consideration. The proposed reconstruction method is a smooth post-filtering correction of the classical WS interpolation series. We assess both the point-wise and global accuracy of the proposed reconstruction algorithm for a broad class of dependent noise processes. This includes short and long-memory stationary errors being independent of the sampling rate. We also examine a class of noise processes for which the correlation function depends on the sampling rate. Whereas the short-memory errors have relatively small influence on the reconstruction accuracy, the long-memory errors can greatly slow down the convergence rate. In the case of the noise model depending on the sampling rate further degradation of the algorithm accuracy is observed. We give quantitative explanations of these phenomena by deriving rates at which the reconstruction error tends to zero. We argue that the obtained rates are close to be optimal. In fact, in a number of special cases they agree with known optimal min-max rates. The problem of the limit distribution of the L2 distance of the proposed reconstruction algorithm is also addressed. This result allows us to tackle an important problem of designing non- parametric lack-of-fit tests. The theory of the asymptotic behavior of quadratic forms of stationary sequences is utilized in this case.
Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data

Accurate prediction of the future trajectory of a disease is an important challenge in personalized medicine and population health management. However, many complex chronic diseases exhibit large degrees of heterogeneity, and furthermore there is not always a single readily available biomarker to quantify disease severity. Even when such a clinical variable exists, there are often additional related biomarkers that may help improve prediction of future disease state. To this end, we propose a novel probabilistic generative model for multivariate longitudinal data that captures dependencies between multivariate trajectories of clinical variables. We use a Gaussian process based regression model for each individual trajectory, and build oﬀ ideas from latent class models to induce dependence between their mean functions. We develop a scalable variational inference algorithm that we use to ﬁt our model to a large dataset of longitudinal electronic patient health records. Our model’s dynamic predictions have signiﬁcantly lower errors compared to a recent state of the art method for modeling disease trajectories, and they are being incorporated into a population health rounding tool to be used by clinicians at our local accountable care organization.
[Influence of huangqi on TGF-beta 1 inducing extracellular matrix secretion of human peritoneal mesothelial cell].

OBJECTIVE To study the effect of huangqi on peritoneal sclerosis and its possible mechanism. METHODS Isolated human peritoneal mesothelial cells (HPMC) was cultured. Cultured HPMC were treated with F12 without serum (control group), F12 with TGF-beta 1 (TGF-beta 1 group), F12 with TGF-beta 1 and huangqi 100 micrograms/ml (huangqi 1 group), F12 with TGF-beta 1 and huangqi 1 mg/ml (huangqi 2 group). Fibronectin(FN) and plasminogen activator inhibitor-1 (PAI-1) were detected by ELISA method. The expression of FN mRNA, PAI-1 mRNA and bFGF mRNA was detected by RT-PCR method. RESULTS 1. HPMC expressed FN, PAI-1, and bFGF. 2. Fn and PAI-1 significantly increased compared with control with 5 ng/ml TGF-beta 1 stimulated at 24 hours and 48 hours(P < 0.05); 3. The different concentration of huangqi decreased FN and PAI-1 expression compared with TGF-beta 1 group, especially 1 mg/ml huangqi at 24 hours(P < 0.05). 4. FN, PAI-1 and bFGF mRNA expression were higher in 12 hours after stimulation with TGF-beta 1 compared with control. FN, PAI-1 and bFGF mRNA expression were lower in 12 hours after stimulation with different concentration of huangqi (100 micrograms/ml and 1 mg/ml) than those in the TGF-beta 1 group. CONCLUSION TGF-beta 1 promotes extracellular matrix synthesis and secretion of HPMC. Huangqi partly counteracts the synthesis of human peritoneal mesothelial cell's extracellular matrix by the stimulation of TGF-beta 1.
Genomic Approaches to Lung Cancer

The last decade has seen remarkable success in clinical targeting of activated oncogenes in cancer. We have applied gene expression profiling, high-density single-nucleotide polymorphism arrays, and systematic resequencing of genes to identify novel oncogenes and signaling pathways in lung cancer that might represent therapeutic targets. Systematic resequencing of tyrosine kinase genes has led to the discovery of somatic mutations in the epidermal growth factor receptor (EGFR) gene in lung adenocarcinomas. These mutations range in frequency from 10% in Caucasian to 40% in East Asian patients. Lung cancer–derived EGFR mutations are oncogenic and are tightly associated with clinical response to the EGFR kinase inhibitors erlotinib and gefitinib. Furthermore, gene expression profiling has been shown to classify patients according to their clinical outcome, indicating that the application of this technique may help in guiding patient selection for therapy in the future. Finally, genome-wide analyses of copy number gains and losses were successfully applied to detect gene amplifications and deletions. Taken together, the application of genomics technologies has led to important discoveries with clinical implications in lung cancer that might help to improve clinical care for patients suffering from this highly fatal tumor.
User Intended Context Sensitive Mining Algorithm for Search String Composition

With ever growing data on Internet, use of search engines has increased tremendously to find information. It is experienced that current search engines give many irrelevant and redundant results for a query. Redundancy and irrelevance can be reduced by using user intent based context while composing a search string query. This research proposes an algorithm to improve the prediction of search string using context based on User Intent. User profiles are used in the experiment as one of the ways to predict the user intention. Context is chosen and added so as to optimize the keystroke saving while predicting the search string. Autocompleting queries have been attempted by search engines but making it more relevant by adding context is essential.
Supersymmetry reduction of N-extended supergravities in four dimensions.

We consider the possible consistent truncation of N-extended supergravities to lower N 0 theories. The truncation, unlike the case of N-extended rigid theories, is non trivial and only in some cases it is su-cient just to delete the extra N i N 0 gravitino multiplets. We explore difierent cases (starting with N = 8 down to N 0 ‚ 2) where the reduction implies restrictions on the matter sector. We perform a detailed analysis of the interesting case N = 2i! N = 1. This analysis flnds applications in difierent contexts of superstring and M-theory dynamics.
An Extracellular Serine/Threonine-Rich Protein from Lactobacillus plantarum NCIMB 8826 Is a Novel Aggregation-Promoting Factor with Affinity to Mucin

ABSTRACT Autoaggregation in lactic acid bacteria is directly related to the production of certain extracellular proteins, notably, aggregation-promoting factors (APFs). Production of aggregation-promoting factors confers beneficial traits to probiotic-producing strains, contributing to their fitness for the intestinal environment. Furthermore, coaggregation with pathogens has been proposed to be a beneficial mechanism in probiotic lactic acid bacteria. This mechanism would limit attachment of the pathogen to the gut mucosa, favoring its removal by the human immune system. In the present paper, we have characterized a novel aggregation-promoting factor in Lactobacillus plantarum. A mutant with a knockout of the D1 gene showed loss of its autoaggregative phenotype and a decreased ability to bind to mucin, indicating an adhesion role of this protein. In addition, heterologous production of the D1 protein or an internal fragment of the protein, characterized by its abundance in serine/threonine, strongly induced autoaggregation in Lactococcus lactis. This result strongly suggested that this internal fragment is responsible for the bioactivity of D1 as an APF. To our knowledge, this is the first report on a gene coding for an aggregation-promoting factor in Lb. plantarum.
Impaired Saccadic Eye Movement in Primary Open-angle Glaucoma

Purpose:Our study aimed at investigating the extent to which saccadic eye movements are disrupted in patients with primary open-angle glaucoma (POAG). This approach followed upon the discovery of differences in the eye-movement behavior of POAG patients during the exploration of complex visual scenes. Methods:The eye movements of 8 POAG patients and 4 healthy age-matched controls were recorded. Four of the patients had documented visual field scotoma, and 4 had no identifiable scotoma on visual field testing. The eye movements were monitored as the observers watched static and kinetic targets. The gain, latency, and velocity-peak latency of the saccades recorded were then analyzed. Results:In POAG patients, with abnormal visual fields, watching a static target, the saccades were delayed and their accuracy was reduced, compared with those of normal observers. In POAG patients, with normal and abnormal visual fields, watching a kinetic target, a task involving precise motion analysis, the latency and accuracy of the saccades were impaired, compared with those of normal observers. Conclusions:Our findings suggest that POAG alters saccade programming and execution particularly in the case of moving targets.
highlighted topics Molecular Biology of Thermoregulation Some historical perspectives on thermoregulation

this paper, selected historical aspects of thermoregulation and fever are pre- sented as background to the application of molecular biology to thermoregulation. Temperature-sensing mechanisms, coordination of thermal infor- mation, thermoregulatory circuitry, efferent responses to thermal stimuli, set point mechanisms, and some of the mechanisms and consequences of fever and hyperthermia are highlighted. Neurotransmitters used in thermoregulatory circuits are also discussed. An attempt is made to include information from comparative physiological sources. Possible future ave-nues of research in the light of recent new technologies are also presented. temperature; hypothalamus; temperature sensing; fever
Classification of segregation level in steel wires by image processing

This article describes a visual measurement system intended for an automatic determination of segregation level in steel wires. The suggested system is principally based on image processing methods for segmentation and classification of inhomogeneous regions inside an otherwise uniform wire. Until our automated inspection system has been deployed, the measurement of segregation level was performed by an inexact and subjective evaluation by a human inspector. The visual measuring system involves an image acquisition stage, image pre-processing, wires segmentation and finally wires classification. In the following text all these parts of evaluation process are described in-depth. Finally each wire is automatically classified into the one of several predefined classes by the mentioned sequence of image processing steps.
A Programming Language Approach to Fault Tolerance for Fork-Join Parallelism

When running big parallel computations on thousands of processors, the probability that an individual processor will fail during the execution cannot be ignored. Computations should be replicated, or else failures should be detected at runtime and failed subcomputations reexecuted. We follow the latter approach and propose a high-level operational semantics that detects computation failures, and allows failed computations to be restarted from the point of failure. We implement this high-level semantics with a lower-level operational semantics that provides a more accurate account of processor failures, and prove in Coq the correspondence between the high- and low-level semantics.
Tests on Effect of Gravity and Soil Density on Soil Cone Index

The cone index is one of the important indicators that can describe the comprehensive physical characteristics of lunar regolith. Its closely related to the sink and sideslip of lunar rover and also has widely used in prediction the trafficability, adhesion property, tractive performance of lunar rover. Based on component method, a kind of low gravity simulator, the tiltable test-bed has been built. This study has got the stable low gravity along axial direction and measured the penetration resistance characteristics of JLU-2 in different gravity through tests. The results shows that the gravity environment has an obvious impact on the cone index of lunar soil simulant, CI values reduce with the decreasing of gravity environment. Namely, in the low gravity condition, it shows weaker resistance ability for a foreign object to penetrate into. The result has important application value of prepare, optimize and risk assessment in walking mechanism of lunar rover and the sampling mechanism.