Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Inference Based on Label Propagation on Wikidata Graph for DST

One of the major problems in Dialog State Tracking (DST) is the large size of user intention space, and thus data preparation for statistical models is hard. In this paper, we propose a method to estimate reliable features of utterances based on creation of a knowledge graph and inference of features on the graph. For the knowledge graph, Wikidata, a large knowledge base consists of concepts and their relations on web, applied to construct a task-domain dependent graph structure. On the created graph, the label propagation algorithm is used to infer features. This inference algorithm propagates of unobserved word nodes from observed words in user utterances. In addition, dialog history words in previous turns is considered as inputs of label propagation. A large vector is created with the inference algorithm, and it is used as a feature of machine learning model. Multi-layer perceptron is adopted as machine learning model of the dialog state tracker, which predicts user intentions. Experimental results show that the proposed method obtain various and stable features, and the results achieve higher scores than the prepared baseline tracker, which does not use the inferred features from the knowledge graph.
Laser Photoablation of Endometrial Cysts : A Review of 55 Cases ( 2000 – 2001 )

Endometrial cysts have been previously described as originating from uterine glands or from lymphatic lacunae. Glandular cysts have been described as being 10 mm in diameter, with a significance that is largely unknown. Lymphatic cysts, however, are lymphatic lacunae that can be significantly larger than 10 mm in diameter. Ragon reported that these cysts could be found in the endometrium or myometrium. The cysts may appear as unilocular or multilocular, be round or elongated, and their presence is associated with both normal and chronically inflamed endometria. Ragon also stated the prevalence of glandular cysts is unknown, but regardless of the population of mares studied (fertile or subfertile), the incidence of lymphatic cysts increases with age. In one study, 73.1% of mares over 14 yr of age had endometrial cysts. In a study of mares acquired from a slaughter-house market, the mean age of mares with endometrial cysts was reported to be 13.4 yr of age. Uterine cysts are most commonly diagnosed by ultrasonography. Prior to the advent of trans-rectal ultrasound, postmortem examination was the most common method of diagnosis. Recently hysteroscopy has become more common in equine practice. Hysteroscopy allows for a thorough visual inspection of the uterus and potential pathology, which other diagnostic procedures cannot provide. Hysteroscopy has been found to be a useful diagnostic technique, and has been used on a routine basis at Equine Services since 1977. The effect of uterine cysts on fertility has been debated. McKinnon et al suggested that the relationship between infertility and uterine cysts was axiomatic. These authors also stated that later in pregnancy, contact between the cyst wall and yolk sac or allantois may prevent absorption of nutrients. Ragon noted in her review that the presence of uterine cysts has been associated with decreased conception rates, increased early embryonic death, and decreased foaling rates. It has also been shown that endometrial cysts are closely associated with increasing age and biopsy scores. This makes the specific effect of uterine cysts on infertility difficult to predict. The purpose of this study was to determine the conception rate in a group of previously barren mares, after photoablation of endometrial lymphatic cysts with Nd:YAG laser.
OF COATED BIODEGRADABLE POLYMER SCAFFOLDS AND THEIR EFFECTS ON MURINE EMBRYONIC STEM CELLS

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science FABRICATION OF COATED BIODEGRADABLE POLYMER SCAFFOLDS AND THEIR EFFECTS ON MURINE EMBRYONIC STEM CELLS By Michael H. Tollon May 2005 Chair: Christopher Batich Major Department: Materials Science and Engineering In the past decade, tissue engineering has become a great interest in materials science research. Embryonic stem (ES) cell transplantation has become one of the most researched therapies for restoring tissue and organ function. Many studies have investigated the use of porous biodegradable scaffolds to promote cell adhesion, growth, proliferation, differentiation, and to help steer the course of tissue development. Research has shown that extracellular matrices and the basement membranes affect various cell types and cellular behaviors. However, the effects of these materials on ES cell behavior are currently understudied and poorly understood. In this study, the synthetic biodegradable polymers polycaprolactone (PCL) and poly(lactic-co-glycolic acid) (PLGA) were chosen to create an interconnected foam structure. A phase separated scaffold method was developed and compared to previously designed salt-leached scaffolds. In vitro degradation studies were conducted on saltleached scaffolds at 37C, while submerged in a phosphate buffered saline solution.
Wastewater Effluent Flow Control Using Multilayer Neural Networks

This paper presents the development of neural networks for prediction of pump control actions responsible for distribution and flow control of wastewater in a lift station plant. The input to the neural network is historical wastewater effluent and reservoir level data from City of Houston’s Clinton lift station. The network output predicts the future state of 14 pump control actions of a wastewater lift station operation. Seven multilayer neural networks are tested with varying number of layers and neurons to obtain the best performing architectures. The average correct prediction rate of the seven trained networks over 14 pump status is over 96% in most cases.
Evaluation for morphologically rich language: Russian NLP

RU-EVAL is a biennial event organized in order to estimate the state of the art in Russian NLP resources, methods and toolkits and to compare various methods and principles implemented for Russian. Russian could be treated as an under-resourced language due to the lack of free distributable gold standard corpora for different NLP tasks (each team tried to work out their own standards). Thus, our goal was to work out the uniform basis for comparison of systems based on different theoretical and engineering approaches, to build evaluation resources, to provide a flexible system of evaluation in order to differentiate between non-acceptable and linguistically “admissible” errors. The paper reports on three events devoted to morphological tagging, dependency parsing and anaphora resolution, respectively.
Tribulations to Appreciation : Experiencing Adversity in the Past Predicts Greater Savoring in the

Can experiencing adversity enhance people’s appreciation for life’s small pleasures? To examine this question, we asked nearly 15,000 adults to complete a vignette-based measure of savoring. In addition, we presented participants with a checklist of adverse events (e.g., divorce, death of a loved one) and asked them to indicate whether they had experienced any of these events and, if so, to specify whether they felt they had emotionally dealt with the negative event or were still struggling with it. Although people who were currently struggling with adversity reported a diminished proclivity for savoring positive events, individuals who had dealt with more adversity in the past reported an elevated capacity for savoring. Thus, the worst experiences in life may come with an eventual upside, by promoting the ability to appreciate life’s small pleasures.
The Effect of Two Types of Tapering on Cortisol, Testosterone and Testosterone/Cortisol Ratio in Male Soccer Players

The present study aimed to investigate the effect of two types of tapering on cortisol, testosterone and the ratio of testosterone to Cortisol in male soccer players. 30 semiprofessional soccer players (age=26.54±3.2, height=176.90±5.90, weight=72.56+3.63) members of ShahinSazeh team of Farsan county, after eight weeks of selected training were randomly in three equal groups of tapering 1 (decrease 25% of training volume), tapering 2 (decrease 50% of exercise volume) and control. After eight weeks soccer training, tapering (decline in exercise volume without changing exercise intensity) was performed during two weeks. Blood sample was drawn in three stages, before start of eight weeks selected training, before and after tapering. Mean and standard deviation were used for statistical data description and one analysis of variance with repeated measures and Bonferroni test was used for inference analysis. Significance level of p<0.05 was considered. Present study results showed that testosterone and the ratio of testosterone to cortisol had significant increase in 25% and 50% groups after two weeks of tapering (P≤0.05). Cortisol value had significant decrease in 25% and 50% groups (P≤0.05). Totally, it seems that two weeks tapering resulted in significant increase in testosterone and the ratio of testosterone to cortisol and significant decrease in cortisol. Also, 50% tapering had more increase in testosterone and the ratio of testosterone to cortisol and more decrease in cortisol value to 25% tapering. However, tapering is a suitable approach for improving performance of hormone system after a period of high pressure training in soccer players.
The Effect of Electromagnetic Waves on Photosynthetic Pigments and Antioxidant Enzyme in Zea Mays L

In order to investigate effects of electromagnetic wavelengths on content of antioxidant photosynthetic pigment in Zea mays L, petri dishes containing seeds soaked in water for 5 hours together with wet seeds were irradiated by electromagnetic waves (200 Gus intensity) every 8 hours and each time for about half an hour. After treatment the seeds were transferred to perlit and pitmass. 13 days old leaves were studied. Chemical analysis of acetone extract resulted from leaves, showed a decrease in the amount of chlorophyll a and b of under treatment samples compared to control. The difference between control and wet treatment samples was meaningful but there was not any significant difference between control and dry treatment samples. Under treatment samples revealed great increase in the amount of carotenoids and non-enzymatic antioxidants such as phenolic compounds, flavonoids and proline compared to control samples. In addition significant increase was observed in the activity of enzymatic antioxidants such as catalase, ascorbate peroxidase and superoxide dismutase related to wet treatment samples compare to control. However there was no significant difference between Off system treatment samples and control.
Phenotyping for Genetic Improvement of Feed Efficiency in Fish: Lessons From Pig Breeding

Feed incurs most of the cost of aquaculture production, so feed efficiency (FE) improvement is of great importance. Our aim is to use work done in pigs to formulate a logical framework for assessing the most useful component traits influencing feed intake (FI) and efficiency in farmed fish – either to identify traits that can together be used for genetic improvement of FE, or as substitute traits for FI recording. Improvement of gross FE in growing fish can be accomplished by selection for increased growth rate. However, the correlation of growth with FE is typically only modest, and hence there is room for further improvement of FE through methods other than growth selection. Based on a literature review we propose that the most effective additional methods are selection for reduced body lipid content and for reduced residual FI (RFI). Both methods require more or less sophisticated recording equipment; in particular, the estimation of RFI requires recording of FI which is a challenge. In mammals and birds, both these approaches have been effective, and despite the high costs of FI recording, the RFI approach can be cost-efficient because maintenance requirements are high and therefore RFI variation covers a large part of FI variance. Maintenance requirements of fish are lower and therefore RFI variation covers a smaller part of FI variance. Moreover, accurate high-volume routine individual FI recording is much more challenging in fish than in mammals or birds. It follows that selection for reduced body fat content is likely a more effective (and certainly more cost-efficient) way to improve feed conversion ratio in fish than selection for reduced RFI. As long as body fat content is dealt with as an explicit selection criterion, the only valid reason for FI recording would be the requirement of RFI reduction. So, if RFI reduction is not required, there would be no need for the expense and effort of individual FI recording – and in fish breeding that would be a very desirable situation. Solid evidence for these propositions is still scarce, and their generality still needs to be confirmed.
Real-time motion tracking using 3D ultrasound

Three-dimensional (3D) ultrasound is ideally suited to monitor internal organ motion since it offers real-time volumetric imaging without exposing the patient to radiation. We extend a two dimensional (2D) region-tracking algorithm, which was originally used in computer vision, to monitor internal organ motion in 3D. A volume of interest is first selected in an ultrasound volume as a reference. The sum of squared differences is used as the similarity measure to register the reference to each successive volume frame. A transformation model is used to describe the motion and geometric deformation of the reference. The Gauss-Newton method is used to solve the optimization problem. In order to improve the algorithm's efficiency, the Jacobian matrix is decomposed as a product of a time-varying matrix and a constant matrix. The constant matrix is pre-computed to reduce the load of online computation. The algorithm was tested on targets under respiratory motion and cardiac motion. The experimental results show that the transformation model of the algorithm can approximate the geometric distortion of the reference template. With a properly selected reference with rich texture information, the algorithm is sufficiently accurate and robust to follow target motion, and fast enough to be used in real time.
A new phylogenetic reconstruction method based on invariants

An attempt to use phylogenetic invariants for tree reconstruction was made at the end of the 80s and the beginning of the 90s by several authors (the initial idea due to Lake [Lake, 1987] and Cavender and Felsenstein [Cavender and Felsenstein, 1987]). However, the e±ciency of methods based on invariants is still in doubt ([Huelsenbeck, 1995], [Jin and Nei, 1990]), probably because these methods only used few generators of the set of phylogenetic invariants. The method studied in this paper was first introduced in [Casanellas et al., 2005] and it is the first method based on invariants that uses the whole set of generators for DNA data. The simulation studies performed in this paper prove that it is a very competitive and highly e±cient phylogenetic reconstruction method, especially for non-homogeneous phylogenetic trees.
A Consistent Model Specification Test with Mixed Discrete and Continuous Data

In this paper we propose a nonparametric kernel-based model specification test that can be used when the regression model contains both discrete and continuous regressors. We employ discrete variable kernel functions and we smooth both the discrete and continuous regressors using least squares cross-validation (CV) methods. The test statistic is shown to have an asymptotic normal null distribution. We also prove the validity of using the wild bootstrap method to approximate the null distribution of the test statistic, the bootstrap being our preferred method for obtaining the null distribution in practice. Simulations show that the proposed test has significant power advantages over conventional kernel tests which rely upon frequency-based nonparametric estimators that require sample splitting to handle the presence of discrete regressors.
Silencing of Rieske Iron-Sulfur Protein Impacts Upon the Development and Reproduction of Spodoptera exigua by Regulating ATP Synthesis

Rieske iron-sulfur protein (RISP) is a key protein subunit of mitochondrial complex III which plays an important role in the respiratory electron transport chain. The complete cDNA of RISP was cloned from Spodoptera exigua by real time quantitative PCR and rapid-amplification of cDNA ends (RACE) technology and named as SeRISP (GenBank Accession Number: JN992290). Multiple alignments and the creation of a phylogenetic tree revealed that RISPs are highly conserved among different insects, and the highly conserved region of RISPs is mainly located at the C-terminal which serves as the functional domain. Expression pattern analysis demonstrated that SeRISP is expressed in all developmental stages of S. exigua; the expression levels increased during larval growth, remained stable during development from fourth instar to pupa and reached a peak in the adult. In addition, SeRISP was significantly suppressed at both the mRNA and protein levels by feeding the instar stage with dsRNA; levels of suppression increased with increasing dsRNA concentration and continuous treatment time. The silencing of SeRISP in larvae led to the significant inhibition of ATP synthesis and larval growth, which could result in energy reserve deficiency in pupae and the suppression of fecundity and hatchability in adults. Our findings confirmed that it is possible to silence target genes in S. exigua by simple dsRNA feeding, and provided evidence of the essential role of RISP in the process of ATP synthesis, growth and reproduction.
Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models

Latent variable models (LVMs) learn probabilistic models of data manifolds lying in an \emph{ambient} Euclidean space. In a number of applications, a priori known spatial constraints can shrink the ambient space into a considerably smaller manifold. Additionally, in these applications the Euclidean geometry might induce a suboptimal similarity measure, which could be improved by choosing a different metric. Euclidean models ignore such information and assign probability mass to data points that can never appear as data, and vastly different likelihoods to points that are similar under the desired metric. We propose the wrapped Gaussian process latent variable model (WGPLVM), that extends Gaussian process latent variable models to take values strictly on a given ambient Riemannian manifold, making the model blind to impossible data points. This allows non-linear, probabilistic inference of low-dimensional Riemannian submanifolds from data. Our evaluation on diverse datasets show that we improve performance on several tasks, including encoding, visualization and uncertainty quantification.
Episodic Memory in Healthy Older Adults The Role of Prefrontal and Parietal Cortices

Healthy aging is associated with deficits in episodic memory. These deficits may be related to changes in neural systems important for mediating episodic memory‐ specific processes (i.e., encoding and retrieval) and/or to deficits in neural systems implicated in other higher‐order cognitive processes, which indirectly impact one’s episodic memory abilities – such as attention, working memory, and cognitive control processes (Zacks et al., 2000). With the advancement and increased availability of brain imaging technologies there has been a marked increase in the number of neuroimaging studies investigating the neural correlates of episodic memory decline in healthy aging. Several studies have found age‐related declines in gray matter volume and functional activity of the medial temporal lobes (MTL) that have been associated with deficits in older adults’ episodic memory. Chapters 5, 6, and 18 in this volume discuss the role of the MTL in episodic memory in healthy young and older adults. In the current chapter we review the functional neuroimaging studies published from 2003 to spring 2012 that have examined how age‐related changes in prefrontal and parietal cortex impact episodic memory in healthy aging. The majority of studies in this field have used visual stimuli. Two functional neuroimaging studies published since 2003 examined age‐related dif ferences in episodic memory that did not employ visual stimuli, one focusing on olfactory–visual associations (Cerf‐Ducastel and Murphy, 2009) and the other on auditory verbal memory (Fernandes et al., 2006). These studies have not been included in the current chapter. Also, in our review of the literature we grouped studies based on whether subsequent retrieval performance was matched between age groups, or was not matched and young adults exhibited significantly better retrieval accuracy than older adults. We did this since assessing brain activity in the context of behavior can be particularly important when there is age-related increase in brain activity in older adults. For example, when performance is matched, increased activation with age might reflect inefficient use of neural resources, but it could also indicate compensatory plasticity in older adults.
Atomic Arrangement in Two-Dimensional Silica: From Crystalline to Vitreous Structures

The atomic structure of vitreous and crystalline regions of a thin silica film on Ru(0001) was investigated using noncontact atomic force microscopy (nc-AFM) and scanning tunneling microscopy (STM). We were able to resolve the atomic arrangement of the Si and the O atoms in the crystalline and the vitreous structures. We discuss characteristic structural properties of the films, such as distances, orientations, and angles, and we compare our results to experiments and simulations of bulk vitreous silica networks. It was found that order in two-dimensional vitreous networks can extend up to 2 nm.
Quantum classification of the MNIST dataset via Slow Feature Analysis

Quantum machine learning carries the promise to revolutionize information and communication technologies. While a number of quantum algorithms with potential exponential speedups have been proposed already, it is quite difficult to provide convincing evidence that quantum computers with quantum memories will be in fact useful to solve real-world problems. Our work makes considerable progress towards this goal. We design quantum techniques for Dimensionality Reduction and for Classification, and combine them to provide an efficient and high accuracy quantum classifier that we test on the MNIST dataset. More precisely, we propose a quantum version of Slow Feature Analysis (QSFA), a dimensionality reduction technique that maps the dataset in a lower dimensional space where we can apply a novel quantum classification procedure, the Quantum Frobenius Distance (QFD). We simulate the quantum classifier (including errors) and show that it can provide classification of the MNIST handwritten digit dataset, a widely used dataset for benchmarking classification algorithms, with $98.5\%$ accuracy, similar to the classical case. The running time of the quantum classifier is polylogarithmic in the dimension and number of data points. We also provide evidence that the other parameters on which the running time depends (condition number, Frobenius norm, error threshold, etc.) scale favorably in practice, thus ascertaining the efficiency of our algorithm.
1 Methane Emissions from Natural Gas Systems

Methane is the second largest contributor to human-caused global warming after carbon dioxide. Hansen and Sato (2004) and Hansen et al. (2007) suggested that a warming of the Earth to 1.8o C above the 1890-1910 baseline may trigger a large and rapid increase in the release of methane from the arctic due to melting of permafrost. While there is a wide range in both the magnitude and timing of projected carbon release from thawing permafrost in the literature (e.g. Schaefer et al., 2011), warming consistently leads to greater release. This release will therefore in turn cause a positive feedback of accelerated global warming (Zimov et al. 2006).