Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding And Reasoning With Short Phrase Queries Over Large Knowledge Bases

The use of large Knowledge Bases (KBs) in modern semantic intensive applications is gradually becoming the norm. Entities from a KB can be used to annotate and semantically enrich data (e.g., holiday destinations or patient profiles) as well as build intelligent services (e.g., holiday booking or symptom checking engines). To access such information or services users usually form entity-centric queries expressed using noun phrases like “Small Mediterranean Islands”, “Cheap Pizza Restaurants”, or “I have a pain in my left leg”. Answering such queries or matching them to the annotated entities is a challenging task since it requires a deeper understanding of their semantics as well as taking into account the axioms defined in the KB (both hierarchy and relations). In the current paper we propose a framework for KB-based understanding and reasoning with such queries that is heavily based on formal Semantic Web technologies. First, we develop a method which given such short phrases it extracts a Description Logic concept in an attempt to formally capture their semantics. Second, we develop a novel reasoning algorithm which given two concepts constructed using entities from a KB compares them by possibly also exploiting information that is encoded in their text labels. The latter is necessary due to possible “underspecification” of KBs which hinders recall of formal reasoning methods. We demonstrate the feasibility and practical relevance of our approach by testing it in a real-world industrial strength application in Anonymous which develops an AI-based symptom checking dialogue system. Our approach coupled with sentence embeddings as a fall-back is used to activate Anonymous’s symptom checking engine and provides the best combination of precision and recall compared to any other method used alone.
Non-entailed subsequences as a challenge for natural language inference

Neural network models have shown great success at natural language inference (NLI), the task of determining whether a premise entails a hypothesis. However, recent studies suggest that these models may rely on fallible heuristics rather than deep language understanding. We introduce a challenge set to test whether NLI systems adopt one such heuristic: assuming that a sentence entails all of its subsequences, such as assuming that "Alice believes Mary is lying" entails "Alice believes Mary. " We evaluate several competitive NLI models on this challenge set and find strong evidence that they do rely on the subsequence heuristic.
Effect of (0001) Strain on the Electronic and Magnetic Properties of the Half-Metallic Ferromagnet Fe2Si

The electronic and magnetic properties of the half-metallic ferromagnet Fe2Si under (0001) strain have been evaluated by the first-principles density functional theory method. The spin-up band structure shows that bulk Fe2Si has metallic character, whereas the spin-down band structure shows that bulk Fe2Si is an S-L indirect band gap of 0.518 eV in the vicinity of Fermi surface. Indirect-to-direct band gaps and an unstable-to-stable transition are observed in bulk Fe2Si as strain is applied. In the range −11% to 11% (excluding zero strain), bulk Fe2Si has stable half-metallic ferromagnetism, the spin polarization at the Fermi surface is 100%, and the magnetic moment of the Fe2Si unit cell is 4.0 μB. The density distribution shows that the spin states of bulk Fe2Si mainly come from the Fe1-3d and Fe3-3d states, indicating that bulk Fe2Si has spin-polarized ferromagnetism. The half-metallic ferromagnetism of bulk Fe2Si is mainly caused by d–d exchange and p–d hybridization, which are not sensitive to strain. It is very important to investigate the effect of changes in the lattice constant on the half-metallic ferromagnetic properties of bulk Fe2Si.
On the relation between parameters and discharge data for a lumped karst aquifer model

Hydrological models of karst aquifers are generally semi distributed and physical processes such as infiltration and spring discharge generation are described in a lumped way. Several works previously addressed the problems associated with the calibration of such models, highlighting in particular the issue of model equifinalty and the importance of multi-objective optimization. In this work, we investigate the problem of model calibration from a different point of view. We apply the active subspace method, to investigate how the parameters of a newly proposed hydrological model for karst aquifers (LuKARS, Land use change modeling in KARSt systems) are informed by discharge data. We showed that each one of the three hydrotopes (i.e. distinct landscape units characterized by homogeneous hydrological properties as a result of similar land use and soil types) used in the model are similarly informed by the data. We found that all the 21 model parameters are informed by the measured data and therefore it is not immediately possible to apply any model reduction scheme. The full-dimensional inverse problem is formulated and solved to identify local optima for the misfit function.
Association Between GSTM 1 Polymorphism and Nasopharyngeal Cancer Susceptibility : a Meta-analysis

Nasopharyngeal cancer (NPC) is one of the most common otolaryngological cancers, characterized by a high frequency of nodal and distant metastasis at diagnosis (Chan, 2011). Although it is rare in many areas of the world, NPC still causes serious damage to public health (Chan, 2011). The exact pathogenesis of NPC has not yet been understood up till now. Apart from epstein-barr virus (EBV) infection and endogenous/exogenous carcinogens, genetic susceptibility seems to be a risk factor playing an crucial role in the development of NPC (O’Neil et al., 2008). Many published studies have revealed that polymorphisms of carcinogen-metabolizing genes encoding detoxifying enzymes contribute to the variation of individual susceptibility to NPC (Chang et al., 2006; Guo et al., 2008; Zhuo et al., 2009). Glutathione S-transferase M1 (GSTM1) is a detoxifying enzyme, which plays a critical role in the detoxification of varieties of carcinogenic metabolites (Moaven et al., 2010). Genetic variation of GSTM1 results in loss of its enzymatic activity and consequently affects an
TITLE : A Practical Coding Scheme For Broadcast Channel

In this thesis, a practical superposition coding scheme based on multilevel low-density parity-check (LDPC) codes is proposed for discrete memoryless broadcast channels. The simulation results show that the performance of the proposed scheme approaches the information-theoretic limits. We also propose a method for optimizing the degree distribution of multilevel LDPC codes based on the analysis of EXIT functions.
GAIN ENHANCEMENT AND WIDEBAND RCS REDUCTION OF A MICROSTRIP ANTENNA USING TRIPLE-BAND PLANAR ELECTROMAGNETIC BAND-GAP STRUCTURE

A triple-band planar electromagnetic band-gap (EBG) structure used for gain enhancement and wideband radar cross section reduction (RCSR) of antenna is presented in this paper. Three bandgaps of an EBG structure are realized by introducing two planar spiral inductances on a planar EBG structure. An equivalent model of EBG is given to further understand the formation of three band-gaps. The proposed EBG is placed around antenna units and arrays to calculate the affection of the RCS and the gain. Due to the band-gaps of the EBG structure, RCS of antennas is reduced, and the gain of antennas is enhanced. Results show that the RCS is reduced as much as 20 dB from 9 GHz to 21 GHz, and both of bandwidth and gain of antennas can be slightly enhanced. Two antenna units operating at 8.6 GHz are fabricated and measured to verify the correctness of simulation. Measured and simulated results are in good agreement.
Turning the tide: Registered nurses' job withdrawal intentions in a Finnish university hospital

Orientation: Given the global shortage of registered nurses, it is important to investigate the intentions for job withdrawal of nurses, and resolve these, in order to retain nurses in the field. Research purpose: The objective was to examine the intentions for job withdrawal of ageing and younger nurses, and the antecedents of these intentions, with special reference to job control and perceived development opportunities. The age of 45 was adopted as a starting point when referring to ageing employees. Motivation for the study: Different forms of job withdrawal have rarely been studied together and associated. Research design, approach and method: A quantitative study was applied with logistic regression analyses. Respondents were registered nurses working in a university hospital in Finland. The response rate was 46.1% ( N = 343). Main findings: A quarter (25%) of the nurses had frequently thought about leaving the profession and 19% of the nurses had thought about taking early retirement. Factors that increased the likelihood of intentions for occupational turnover were young age, low job satisfaction, low organisational commitment, low work ability and skills in balance with or above present work demands. The intention to take early retirement was increased with older age, being male, working shifts, low work ability, low job satisfaction and poor job control. Practical/managerial implications: A nurse’s job satisfaction and work ability should be regularly monitored and opportunities should be offered them, to apply their skills and to control their work, in order to retain them. Contribution/value–added: The article added information about the factors that contribute to a nurse’s intentions for job withdrawal.
Evolving Fuzzy Neural Networks for On-line Knowledge Discovery

The Department of Information Science is one of six departments that make up theSchool of Business at the University of Otago. The department offers courses of studyleading to a major in Information Science within the BCom, BA and BSc degrees. Inaddition to undergraduate teaching, the department is also strongly involved in post-graduate research programmes leading to MCom, MA, MSc and PhD degrees. Re-search projects in spatial information processing, connectionist-based information sys-tems, software engineering and software development, information engineering anddatabase, software metrics, distributed information systems, multimedia informationsystems and information systems security are particularly well supported.The views expressed in this paper are not necessarily those of the department as awhole. The accuracy of the information presented in this paper is the sole responsibil-ity of the authors.
Tool-Body Assimilation Model Based on Body Babbling and Neurodynamical System

We propose the new method of tool use with a tool-body assimilation model based on body babbling and a neurodynamical system for robots to use tools. Almost all existing studies for robots to use tools require predetermined motions and tool features; the motion patterns are limited and the robots cannot use novel tools. Other studies fully search for all available parameters for novel tools, but this leads to massive amounts of calculations. To solve these problems, we took the following approach: we used a humanoid robot model to generate random motions based on human body babbling. These rich motion experiences were used to train recurrent and deep neural networks for modeling a body image. Tool features were self-organized in parametric bias, modulating the body image according to the tool in use. Finally, we designed a neural network for the robot to generate motion only from the target image. Experiments were conducted with multiple tools for manipulating a cylindrical target object. The results show that the tool-body assimilation model is capable of motion generation.
Fracture Toughness Determination of Heat Treated AISI D2 Tool Steel Using AE Technique

In this study, acoustic emission behavior of a tool steel during fracture toughness tests was investigated. Selected steel (AISI D2 cold-work tool steel) was heat treated at 5 different conditions (austenitized at 1 010°C and tempered at 0, 300, 450, 525 and 575°C) and its properties were characterized using standard metallographic examinations, hardness and tensile tests. Compact specimen testing according to ASTM standard E 399 and acoustic emission technique were used to determine the fracture toughness value (K IC ) and fracture process. Determination of fracture toughness using AE technique was carried out according to classical and two modified methods. Results showed that: (a) by increasing tempering temperature, plain strain fracture toughness (K IC ) values and the fraction of ductile fibrous fracture increase except at 525°C when tempering process leads to secondary hardening, (b) fracture toughness values determined, using AE technique is lower than standard ASTM E399, (c) estimation of K IC values, using modified methods (AECR and AEER), is more accurate in comparison with the classical AE method and (d) the effect of tempering temperature on AE characteristics during fracture toughness test is similar to its effect on hardness.
Breast Cancer Diagnosis based on Genetic Algorithms and Neural Networks

This paper proposes to use of hybrid genetic algorithm with artificial neural networks technique for diagnosing the Breast Cancer in order to give more accuracy than using neural network, since the performance of hybrid genetic algorithm with artificial neural networks for diagnosis of the Breast Cancer can measure by the value of fitness function. The number of hidden layers in the neural network has a significant effect on the classification performance and the best diagnoses performance average is attained when the number of layers equal three. The result by the using of GANN technique up to 94%.
Cytological behaviour of the somatic hybrids Passiflora edulis f. flavicarpa + P. cincinnata

Meiosis and pollen viability of interspecific somatic hybrids, i.e. Passiflora edulis f. flavicarpa, the yellow passion fruit + P. cincinnata, a wild species, were examined and compared with their corresponding diploid fusion parents. Firstly, the cybrid nature of these hybrids was confirmed by leaf-stomatal measurements and RFLP analyses using four mitochondrial genes as probes. The meiotic behaviour revealed relatively high stability, with most of the hybrid cells showing 18 bivalents. Some instability, such as a quadrivalent configuration was also recorded which has been interpreted as an interchange that occurred in the progenitors more than as a result of in vitro culture or chromosome reorganization in the new genome. Even in low frequencies, the occurrence of univalents resulted in mis-division, laggard and micronucleus formation. High values of pollen viability (>70%) were found in the diploid parents as well as in the hybrid plants. The results are discussed in relation to the possibilities of applying somatic hybridization for improving passion fruit varieties.
X-ray source brightness comparison: Rigaku rotating anode source vs. Kevex microfocus tube

In 2007, we began to explore alternative x-ray sources for application to refraction-enhanced (phase contrast) x-ray radiography of cryogenic NIF ignition capsules containing frozen deuterium-tritium (D-T) ice layers. These radiographs are currently obtained using Kevex microfocus tubes as backlights, and for these sources the x-ray source size is approximately 5 {micro}m. As part of this exploration, we obtained refraction-enhanced radiographs of empty plastic capsules using the Janus laser facility at LLNL, demonstrating that even large ({approx} 100 {micro}m) sources can be utilized in refraction-enhanced radiography provided the source/sample distance is sufficiently large, and provided the final x-ray detector has sufficient spatial resolution. Essentially, in the current geometry, we rely on a small source to provide spatial resolution and on the source/sample distance to provide refraction contrast, but an equally useful alternative geometry is to use a large source and rely on fine detector spatial resolution to provide spatial resolution and on the sample/detector distance to provide refraction contrast.
Coupled Oscillator Model for Nonlinear Gravitational Perturbations

Motivated by the gravity/fluid correspondence, we introduce a new method for characterizing nonlinear gravitational interactions. Namely we map the nonlinear perturbative form of the Einstein equation to the equations of motion of a collection of nonlinearly-coupled harmonic oscillators. These oscillators correspond to the quasinormal or normal modes of the background spacetime. We demonstrate the mechanics and the utility of this formalism within the context of perturbed asymptotically anti-de Sitter black brane spacetimes. We confirm in this case that the boundary fluid dynamics are equivalent to those of the hydrodynamic quasinormal modes of the bulk spacetime. We expect this formalism to remain valid in more general spacetimes, including those without a fluid dual. In other words, although borne out of the gravity/fluid correspondence, the formalism is fully independent and it has a much wider range of applicability. In particular, as this formalism inspires an especially transparent physical intuition, we expect its introduction to simplify the often highly technical analytical exploration of nonlinear gravitational dynamics.
A review on graph optimization and algorithmic frameworks

In this report, we make a review of optimization problems involving graphs and state-of-the-art algorithms to solve them. First, we present a set of discrete optimization problems and resolution methods for edge selection problems. Then, we address the matrix optimization problems involved in the estimation of precision or covariance matrices given observations from multivariate Gaussian distribution.
Ontology and E-Learning

In the last decade the evolution on educational technologies forced an extraordinary interest in new methods for delivering learning content to learners. Distance education represents today an effective way for supporting and sometimes substituting the traditional formative processes, thanks to the technological improvements achieved in the field in recent years. However the role of technology has often been overestimated and on the other hand the amount of information students can obtain from the Internet is huge and they can easily be confused. Teachers can also be disconcerted by this quantity of contents and they are often unable to suggest the correct contents to their students. In the open scientific literature, it is widely recognized that an important factor of this success is related with the capability of customizing the learning process for the specific needs of a given learner. This feature is still far to have been reached and there is a real interest for investigating new approaches and tools to adapt the formative process on specific individual needs. In this scenario, the introduction of ontology formalism can improve the quality of formative process, allowing the introduction of new and effective services. Ontologies can lead to important improvements in the definition of courses knowledge domain, in the generation of adapted learning path and in the assessment phase. This paper provides an initial discussion of the role of ontologies in the context of e-learning. We discuss such improvements related to the introduction of ontologies formalism in the E-Learning field and we present a novel algorithm for ontology building through the use of Bayesian Networks. Finally, we show its application in the assessment process and some experimental results.
A New Time Stepping Method for Solving One Dimensional Burgers' Equations

In this paper, we present a simple explicit type numerical method for discretizations in time for solving one dimensional Burgers' equations. The proposed method does not need an iteration process that may be required in most implicit methods and have good convergence and efficiency in computational sense compared to other known numerical methods. For evidences, several numerical demonstrations are also provided.
Analysis of variation of neutral point potential in neutral-point-clamped voltage source PWM inverters

The authors present the analysis of the neutral-point potential variation of the neutral-point-clamped voltage source PWM (pulse-width-modulation) inverter (NPC-VSI) for AC motor drives and static VAr compensators (SVC). The potential variation is analyzed with the focus on the current flowing out of or into the neutral point of the DC link. The theoretical minimum capacity of the DC link capacitors is discussed for its application to both a vector-controlled induction motor system of 2.2 kW and a SVC system of 10 MVA, 6.6 kV, 60 Hz. It is shown that the proposed control scheme makes it possible to suppress the neutral-point potential variation within a few percent, so that the total capacity of the DC link capacitors in the NPC-VSI is almost the same as that in the conventional voltage source inverter. <<ETX>>
Polymorphism of Myostatin ( MSTN ) Promoter Gene and its Association with Growth and Muscling Traits in Bali Cattle

Myostatin (MSTN) gene plays a key role in skletal muscle homeostasis such as inducing muscle athrophy, poliferation of myoblast, increasing ubiquitin-proteasomal, downregulating IGF pathway, and glucolysis. Myostatin gene expression is controled by CpG island located in promoter region. The objectives of this research were to identify polymorphism of MSTN promoter gene and to associate the polymorphism of SNP with growth and muscling traits in Bali cattle. A total of 48 Bali cattle from BPTU-HMT Bali island was screened to identify genetic polymorphisms in MSTN promoter region using sequencing method. The growth and muscling traits were measured at 12 months of age. The muscling traits were evaluated using ultrasound console with linear transducer having frequency 6.5 Hz and scaning we conducted at 130 mm in deep. Analysis of polymorphism was conducted by using PopGen 1.32 software. The association of MSTN with growth and muscling traits were analyzed by using General Linear Model (GLM) procedure. This result showed that a total of 20 polymorphic SNPs (seven SNPs in CpG island) were detected in this region. Although, only 3 SNPs (g.-8078C>T, g.-7996G>C, and g.-7930A>G) had equilibrium condition in Hardy-Weinberg analysis. The association result showed that 2 SNPs (g.-7799T>C and g.-7941C>T) were significantly associated with intramuscular fat percentage (P≤0.05) in Bali cattle. Although the 2 SNPs were nominally significant at nominal P≤0.05 threshold, they were not significant after Bonferroni correction for multiple testing. It could be concluded that MSTN promoter gene was polymorphic in Bali cattle and there were 2 SNPs associated with carcass quality.