Miracle-dz/UniFAR-FTUs huggingface dataset:
End-to-End Graph-Based TAG Parsing with Neural Networks

We present a graph-based Tree Adjoining Grammar (TAG) parser that uses BiLSTMs, highway connections, and character-level CNNs. Our best end-to-end parser, which jointly performs supertagging, POS tagging, and parsing, outperforms the previously reported best results by more than 2.2 LAS and UAS points. The graph-based parsing architecture allows for global inference and rich feature representations for TAG parsing, alleviating the fundamental trade-off between transition-based and graph-based parsing systems. We also demonstrate that the proposed parser achieves state-of-the-art performance in the downstream tasks of Parsing Evaluation using Textual Entailments (PETE) and Unbounded Dependency Recovery. This provides further support for the claim that TAG is a viable formalism for problems that require rich structural analysis of sentences.
Thermal Model of a Quench in Superconducting Undulators

Currently there are two 1.1 m long planar superconducting undulators (SCUs) in operation in the Advanced Photon Source storage ring. Their NbTi magnets are cooled with liquid Helium (LHe) penetrating through a channel in the magnet coil formers. In this scheme, the latent heat of LHe provides an effective energy buffer that allows the magnet to return to normal operation within minutes. An FEA-based dynamic thermal model of the SCU is being developed to analyze the behavior of the SCU cryogenic systems during a quench. In this paper, preliminary results of these FEA-based calculations and a comparison with the current operation of SCUs are presented.
Liveness Detection Using Implicit 3D Features

Spoofing attacks are a threat to modern face recognition systems. In this work we present a simple yet effective liveness detection approach to enhance 2D face recognition methods and make them robust against spoofing attacks. We show that the risk to spoofing attacks can be re- duced through the use of an additional source of light, for example a flash. From a pair of input images taken under different illumination, we define discriminative features that implicitly contain facial three-dimensional in- formation. Furthermore, we show that when multiple sources of light are considered, we are able to validate which one has been activated. This makes possible the design of a highly secure active-light authentication framework. Finally, further investigating the use of 3D features without 3D reconstruction, we introduce an approximated disparity-based implicit 3D feature obtained from an uncalibrated stereo-pair of cameras. Valida- tion experiments show that the proposed methods produce state-of-the-art results in challenging scenarios with nearly no feature extraction latency.
A novel relearning approach for remote sensing image classification post-processing

In this paper, we proposed a relearning method for classification post-processing (CPP). CPP can be viewed as a label refinement method to improve the classification accuracy. The proposed approach considers the frequency and spatial arrangements of the labels to enhance the classification performance by iteratively learning the classification map. Experiments conducted on a series of images obtained by different sensors show that, the proposed relearning approach present promising performances compared to the state-of-the-art techniques such as filtering, Markov random field (MRF) and object-based voting.
Application of Fuzzy Control in a Photovoltaic Grid-Connected Inverter

To realize the maximum power output of a grid-connected inverter, the MPPT (maximum power point tracking) control method is needed. The perturbation and observation (P&O) method can cause the inverter operating point to oscillate near the maximum power. In this paper, the fuzzy control P&O method is proposed, and the fuzzy control algorithm is applied to the disturbance observation method. The simulation results of the P&O method with fuzzy control and the traditional P&O method prove that not only can the new method reduce the power loss caused by inverter oscillation during maximum power point tracking, but also it has the advantage of speed. Inductive loads in the post-grid-connected stage cause grid-connected current distortion. A fuzzy control algorithm is added to the traditional deadbeat grid-connected control method to improve the quality of the system’s grid-connected operation. The fuzzy deadbeat control method is verified by experiments, and the harmonic current of the grid-connected current is less than 3%.
Insignificant influence of the matrix on the melting of ice confined in decorated mesoporous silica

Abstract For a critical examination of matrix effect on the melting of confined ice, mesoporous silica (SBA-15) are synthesised and decorated with n-Alkyl and aminopropyl groups to tune the surface hydrophobicity. Water contact angle to these decorated surfaces are estimated to be about 100° and 60°, respectively. By examining the melting of ice confined in these decorated samples, we find that the influence of the matrix is indeed not significant. The reported apparent matrix effect is more likely method effect in the determination of pore diameters as was demonstrated in our previous studies (Philos. Mag. 93 (2013), p. 1827).
SNP Regulation of microRNA Expression and Subsequent Colon Cancer Risk

Introduction MicroRNAs (miRNAs) regulate messenger RNAs (mRNAs) and as such have been implicated in a variety of diseases, including cancer. MiRNAs regulate mRNAs through binding of the miRNA 5’ seed sequence (~7–8 nucleotides) to the mRNA 3’ UTRs; polymorphisms in these regions have the potential to alter miRNA-mRNA target associations. SNPs in miRNA genes as well as miRNA-target genes have been proposed to influence cancer risk through altered miRNA expression levels. Methods MiRNA-SNPs and miRNA-target gene-SNPs were identified through the literature. We used SNPs from Genome-Wide Association Study (GWAS) data that were matched to individuals with miRNA expression data generated from an Agilent platform for colon tumor and non-tumor paired tissues. These samples were used to evaluate 327 miRNA-SNP pairs for associations between SNPs and miRNA expression levels as well as for SNP associations with colon cancer. Results Twenty-two miRNAs expressed in non-tumor tissue were significantly different by genotype and 21 SNPs were associated with altered tumor/non-tumor differential miRNA expression across genotypes. Two miRNAs were associated with SNP genotype for both non-tumor and tumor/non-tumor differential expression. Of the 41 miRNAs significantly associated with SNPs all but seven were significantly differentially expressed in colon tumor tissue. Two of the 41 SNPs significantly associated with miRNA expression levels were associated with colon cancer risk: rs8176318 (BRCA1), ORAA 1.31 95% CI 1.01, 1.78, and rs8905 (PRKAR1A), ORGG 2.31 95% CI 1.11, 4.77. Conclusion Of the 327 SNPs identified in the literature as being important because of their potential regulation of miRNA expression levels, 12.5% had statistically significantly associations with miRNA expression. However, only two of these SNPs were significantly associated with colon cancer.
Impact of dentine hypersensitivity on oral health-related quality of life in individuals receiving supportive periodontal care.

AIM To determine the prevalence and impact of dentine hypersensitivity (DH) on oral health-related quality of life (OHRQoL) in individuals receiving supportive periodontal care (SPC). MATERIALS AND METHODS One hundred and two adults receiving SPC were recruited for a cross-sectional study. Subjects were categorized into those who self-reported DH (DH1) or did not (DH0). Impact of DH on OHRQoL was assessed using the Chinese Condition-Specific Oral Impact on Daily Performance questionnaire (CS-OIDP). Evaluation of DH included tactile-stimulation followed by air-blast, and recorded using a Visual Analogue Scale (VAS). RESULTS Sixty-one (59.8%) subjects self-reported DH with mean air-blast VAS score of 29.4 ± 21.3 mm and mean tactile-stimulation VAS score of 10.9 ± 14.7 mm. Fifty (49%) subjects reported impact on OHRQoL (mean CS-OIDP score = 4.7 ± 6.3). The most affected performance was cleaning the mouth (35.3%). Positive expression of DH and worse OHRQoL were associated with higher air-blast and tactile-stimulation VAS scores, and use of desensitizing agents. The minimally important difference (MID) in CS-OIDP scores was 2.0 points. Approximately 30% of the subjects reported CS-OIDP scores above the MID. CONCLUSIONS Dentine hypersensitivity affects OHRQoL in patients undergoing SPC. The extent of impact was associated with severity of DH.
Building Entity-Centric Event Collections

Web archives preserve an unprecedented abundance of materials regarding major events and transformations in our society. In this paper, we present an approach for building event-centric sub-collections from such large archives, which includes not only the core documents related to the event itself but, even more importantly, documents describing related aspects (e.g., premises and consequences). This is achieved by 1) identifying relevant concepts and entities from a knowledge base, and 2) detecting their mentions in documents, which are interpreted as indicators for relevance. We extensively evaluate our system on two diachronic corpora, the New York Times Corpus and the US Congressional Record, and we test its performance on the TREC KBA Stream corpus, a large and publicly available web archive.
La compresión de frases: un recurso para la optimización de resumen automático de documentos

El objetivo de este trabajo de investigacion es confirmar si es adecuado emplear la compresion de frases como recurso para la optimizacion de sistemas de resumen automatico de documentos. Para ello, en primer lugar, creamos un corpus de resumenes de documentos especializados (articulos medicos) producidos por diversos sistemas de resumen automatico. Posteriormente realizamos dos tipos de compresiones de estos resumenes. Por un lado, llevamos a cabo una compresion manual, siguiendo dos estrategias: la compresion mediante la eliminacion intuitiva de algunos elementos de la oracion y la compresion mediante la eliminacion de ciertos elementos discursivos en el marco de la Rhetorical Structure Theory (RST). Por otro lado, realizamos una compresion automatica por medio de varias estrategias, basadas en la eliminacion de palabras de ciertas categorias gramaticales (adjetivos y adverbios) y una baseline de eliminacion aleatoria de palabras. Finalmente, comparamos los resumenes originales con los resumenes comprimidos, mediante el sistema de evaluacion Rouge. Los resultados muestran que, en ciertas condiciones, utilizar la compresion de frases puede ser beneficioso para mejorar el resumen automatico de documentos.
Design of a Photonic Crystal Defect Waveguide Biosensor Operating in Aqueous Solutions at 1.34 µm

A two-dimensional photonic crystal defect waveguide sensor based on CMOS-compatible silicon-on-insulator technology was designed for operation in aqueous solutions at a wavelength of 1.34 µm, by the use of the 3D Plane Wave Expansion and the Finite Difference Time Domain simulation method. An operation under water in this wavelength regime allows for a significantly smaller propagation loss in contrast to the state-of-the-art operation wavelength of photonic crystals at 1.55 µm. The sensor working principle is label-free and based on evanescent wave sensing exploiting the local refractive index change induced by the specific binding of target molecules to a capture molecules immobilized on the surface of the phontonic crystal structure. We experimentally proved the theoretical predications of our simulations and demonstrated the sensing functionality of the photonic crystal defect waveguide using the biotin-straptavidin binding system.
Assessment of features for automatic CTG analysis based on expert annotation

Cardiotocography (CTG) is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO) since 1960's used routinely by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the ever-used features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and the features are assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. Annotation derived from the panel of experts instead of the commonly utilized pH values was used for evaluation of the features on a large data set (552 records). We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. Number of acceleration and deceleration, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.
Grinding and polishing efficiency of a novel self-glazed zirconia versus the conventional dry-pressed and sintered zirconia ceramics

The grinding and polishing efficiency of self-glazed zirconia and Zenostar zirconia, prepared by wet and dry approaches, respectively, were evaluated. Each sample was divided into two subgroups (n = 5). One was ground, and the other was polished by following the clinical adjustment protocol. Statistics were analysed by independent t-test to a significance level of p < . 05. More material was ground off in self-glazed zirconia than in Zenostar zirconia (p < .05) during the same period, especially during the coarse grinding procedure (p < .05), whereas the grinding efficiency in fine grinding stage was not significantly different (p > .05). The polishing efficiency of the whole and of the fine polishing procedure of the two kinds of zirconia was significantly different (p < .05). It thus can be concluded that grinding and polishing efficiency of a novel self-glazed zirconia is significantly higher than that of the conventional Zenostar zirconia.
Sum-Product Networks for Hybrid Domains

While all kinds of mixed data -from personal data, over panel and scientific data, to public and commercial data- are collected and stored, building probabilistic graphical models for these hybrid domains becomes more difficult. Users spend significant amounts of time in identifying the parametric form of the random variables (Gaussian, Poisson, Logit, etc.) involved and learning the mixed models. To make this difficult task easier, we propose the first trainable probabilistic deep architecture for hybrid domains that features tractable queries. It is based on Sum-Product Networks (SPNs) with piecewise polynomial leave distributions together with novel nonparametric decomposition and conditioning steps using the Hirschfeld-Gebelein-R\'enyi Maximum Correlation Coefficient. This relieves the user from deciding a-priori the parametric form of the random variables but is still expressive enough to effectively approximate any continuous distribution and permits efficient learning and inference. Our empirical evidence shows that the architecture, called Mixed SPNs, can indeed capture complex distributions across a wide range of hybrid domains.
It's All about the Support: A New Perspective on the Satisfiability Problem

We study a new approach to the satisfiability problem, which we call the Support Paradigm. Given a CNF formula F and an assignment ψ to its variables we say that a literal x supports a clause C in F w.r. t. ψ if x is the only literal that evaluates to true in C. Our focus in this work will be on heuristics that obey the following general template: start at some assignment to the variables, then iteratively, using some predefined (greedy) rule, try to minimize the number of unsatisfied clauses (or the distance from some satisfying assignment) until a satisfying assignment is reached. We say that such a heuristic is part of the Support Paradigm if the greedy rule uses the support as its main criterion. We present a new algorithm in the Support Paradigm and rigorously prove its effectiveness for a certain distribution over satisfiable k-CNF formulas known as the planted distribution. One motivation for this work is recent experimental results showing that some simple variants of the RWalkSAT algorithm, which base their greedy rule on the support, seem to remain effective for random 3CNF formulas in the “hard” near-threshold regime, while for example RWalkSAT, which disregards the support, is already inefficient in a much earlier stage.
Novel Structuring Routines for Organic Photovoltaics

Organic photovoltaic devices are promising candidates for a future energy production at low-costs. In the framework of this thesis, fundamental aspects of organic solar cells based on different blend systems were investigated. X-ray scattering revealed a strong dependency of the inner film morphology of such devices on the layer thickness and the film composition. Applying optical methods, an enhanced photochemical degradation of blend films upon UV-irradiation was observed if compared to pure homopolymer samples. Furthermore, novel imprinting routines have been developed for the fabrication of structured polymer films with feature dimensions on the micro- and nanoscale. Making use of such textured films in organic photovoltaic devices, the power conversion efficiency was improved due to an diffraction-induced increase in optical absorption.
Mitonuclear discordance in wolf spiders: Genomic evidence for species integrity and introgression

Systematists and taxonomists have benefited greatly from the emergence of molecular methods. Species identification has become straightforward through DNA barcoding and the rapid build‐up of massive DNA barcode reference libraries. In animals, mitonuclear discordance can significantly complicate the process of species identification and delimitation. The causes of mitonuclear discordance are either biological (e.g., introgression, incomplete lineage sorting, horizontal gene transfer androgenesis) or induced by operational factors (e.g., human error with specimen misidentification or incorrect species delimitation). Moreover, endosymbionts may play an important role in promoting fixation of mitochondrial genomes. Here, we study the mitonuclear discordance of wolf spiders species (Lycosidae) (independent cases from Alopecosa aculeata and Pardosa pullata groups) that share identical COI DNA barcodes. We approached the case utilizing double‐digest restriction site‐associated DNA sequencing (ddRADseq) to obtain and analyse genomic‐scale data. Our results suggest that the observed cases of mitonuclear discordance are not due to operational reasons but result from biological processes. Further analysis indicated introgression and that incomplete lineage sorting is unlikely to have been responsible for the observed discrepancy. Additional survey of endosymbionts provided ideas on further research and their role in shaping mitochondrial DNA distribution patterns. Thus, ddRADseq grants an efficient way to study the taxonomy of problematic groups with insight into underlying evolutionary processes.
Privacy Preserving for Tagging Recommender Systems

Tagging recommender systems allow Internet users to annotate resources with personalized tags. The connection among users, resources and these annotations, often called afolksonomy, permits users the freedom to explore tags, and to obtain recommendations. Releasing these tagging datasets accelerates both commercial and research work on recommender systems. However, adversaries may re-identify a user and her/his sensitivity information from the tagging dataset using a little background information. Recently, several private techniques have been proposed to address the problem, but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes an private releasing algorithm to perturb users' profile in a strict privacy notion, differential privacy, with the goal of preserving a user's identity in a tagging dataset. The algorithm includes three privacy preserving operations: Private Tag Clustering is used to shrink the randomized domain and Private Tag Selection is then applied to find the most suitable replacement tags for the original tags. To hide the numbers of tags, the third operation, Weight Perturbation, finally adds Lap lace noise to the weight of tags We present extensive experimental results on two real world datasets, Delicious and Bibsonomy. While the personalization algorithmis successful in both cases.
Artistic mosaic generation

In this paper, a new approach to image processing in arts is presented in the domain of generating a series of artistic mosaic pictures. The mosaic pictures consist of the same elements as each other, but might be extremely different from the semantic contents. Some preliminary experimental results are given to show the impact of the proposed special techniques.
Interdependent Gibbs Samplers

Gibbs sampling, as a model learning method, is known to produce the most accurate results available in a variety of domains, and is a de facto standard in these domains. Yet, it is also well known that Gibbs random walks usually have bottlenecks, sometimes termed "local maxima", and thus samplers often return suboptimal solutions. In this paper we introduce a variation of the Gibbs sampler which yields high likelihood solutions significantly more often than the regular Gibbs sampler. Specifically, we show that combining multiple samplers, with certain dependence (coupling) between them, results in higher likelihood solutions. This side-steps the well known issue of identifiability, which has been the obstacle to combining samplers in previous work. We evaluate the approach on a Latent Dirichlet Allocation model, and also on HMM's, where precise computation of likelihoods and comparisons to the standard EM algorithm are possible.
Evaluation of a welfare assessment tool to examine practices for preventing, recognizing, and managing pain at companion-animal veterinary clinics.

Successful prevention, recognition, and treatment of pain are integral to ensuring veterinary patient welfare. A canine and feline welfare assessment tool, incorporating verbal interviews with veterinarians using open-ended questions, was developed to assess pain management practices that safeguard and improve patient welfare. The tool was evaluated in 30 companion- and mixed-animal veterinary clinics in Ontario in order to assess its reliability, feasibility, and validity, while also benchmarking current practices. Responses were analyzed according to a scoring scheme developed based on published literature and expert opinion. Based on weighted kappa statistics, interview scoring had substantial inter-observer (Kw = 0.83, 0.73) and near-perfect intra-observer (Kw = 0.92) agreement, which suggests that the tool reliably collects information about pain management practices. Interviews were completed at all recruited clinics, which indicates high feasibility for the methods. Validity could not be assessed, as participants were reluctant to share information about analgesic administration from their clinical records. Descriptive results indicated areas for which many veterinarians are acting in accordance with best practices for pain management, such as pre-emptive and post-surgical analgesia for ovariohysterectomy patients, and post-surgical care instructions. Areas that offer opportunity for enhancement were also highlighted, e.g., training veterinary staff to recognize signs of pain and duration of analgesia in ovariohysterectomy patients after discharge. Overall, based on this limited sample, most veterinarians appear to be effectively managing their patients' pain, although areas with opportunity for enhancement were also identified. Further research is needed to assess trends in a broader sample of participants.