Miracle-dz/UniFAR-FTUs huggingface dataset:
ODELO: an ontology-driven model for the evaluation of learning ontologies

Trying out or updating an existing learning ontology and providing evaluation tools to assess its quality are essential steps before putting an e-learning system online. Ontology evaluation is a crucial task and it is usually the output of an automatic process. This paper proposes an ontology-driven model, called Ontology-Driven model for the Evaluation of Learning Ontologies (ODELO), for the evaluation of ontologies representing learning resources with respect to syntactic, semantic, pragmatic, social and cohesion metrics. Syntax deals with the formal relations between signs (e.g., words, phrases, sentences) and the production of new ones. Semantics is the study of the relationships between the system of signs and their meanings. Pragmatics is the study of natural language understanding. Social metrics reflect the fact that software agents and ontologies coexist and communicate in communities. Ontology cohesion metrics refer to the degree of relatedness of ontology classes. ODELO is a deductive evaluation model that identifies the elements of ontological quality for learning ontologies. In this paper we propose a framework for assessing the quality of learning ontologies, which constitute the basis for intelligent educational Adaptive Hypermedia (AH) systems. We introduce a new pragmatic quality metric for assessing the quality of learning ontologies.
Upgrading short-read animal genome assemblies to chromosome level using comparative genomics and a universal probe set

Most recent initiatives to sequence and assemble new species’ genomes de novo fail to achieve the ultimate endpoint to produce contigs, each representing one whole chromosome. Even the best-assembled genomes (using contemporary technologies) consist of subchromosomal-sized scaffolds. To circumvent this problem, we developed a novel approach that combines computational algorithms to merge scaffolds into chromosomal fragments, PCR-based scaffold verification, and physical mapping to chromosomes. Multigenome-alignment-guided probe selection led to the development of a set of universal avian BAC clones that permit rapid anchoring of multiple scaffolds to chromosomes on all avian genomes. As proof of principle, we assembled genomes of the pigeon (Columbia livia) and peregrine falcon (Falco peregrinus) to chromosome levels comparable, in continuity, to avian reference genomes. Both species are of interest for breeding, cultural, food, and/or environmental reasons. Pigeon has a typical avian karyotype (2n = 80), while falcon (2n = 50) is highly rearranged compared to the avian ancestor. By using chromosome breakpoint data, we established that avian interchromosomal breakpoints appear in the regions of low density of conserved noncoding elements (CNEs) and that the chromosomal fission sites are further limited to long CNE “deserts. ” This corresponds with fission being the rarest type of rearrangement in avian genome evolution. High-throughput multiple hybridization and rapid capture strategies using the current BAC set provide the basis for assembling numerous avian (and possibly other reptilian) species, while the overall strategy for scaffold assembly and mapping provides the basis for an approach that (provided metaphases can be generated) could be applied to any animal genome.
CEVO: Comprehensive EVent Ontology Enhancing Cognitive Annotation

While the general analysis of named entities has received substantial research attention on unstructured as well as structured data, the analysis of relations among named entities has received limited focus. In fact, a review of the literature revealed a deficiency in research on the abstract conceptualization required to organize relations. We believe that such an abstract conceptualization can benefit various communities and applications such as natural language processing, information extraction, machine learning, and ontology engineering. In this paper, we present Comprehensive EVent Ontology (CEVO), built on Levin's conceptual hierarchy of English verbs that categorizes verbs with shared meaning, and syntactic behavior. We present the fundamental concepts and requirements for this ontology. Furthermore, we present three use cases employing the CEVO ontology on annotation tasks: (i) annotating relations in plain text, (ii) annotating ontological properties, and (iii) linking textual relations to ontological properties. These use-cases demonstrate the benefits of using CEVO for annotation: (i) annotating English verbs from an abstract conceptualization, (ii) playing the role of an upper ontology for organizing ontological properties, and (iii) facilitating the annotation of text relations using any underlying vocabulary. This resource is available at this https URL using this https URL namespace.
Performance analysis of locality preserving image hash

Bit extraction is an essential component of an image hashing system. A good bit extraction scheme should preserve the performance achieved at the feature representation level. In other words the robustness discrimination tradeoff measured by ROC analysis should be preserved. This is dependent on several factors such as, the encountered noise and the number of bits that can be extracted per sample. This paper investigates the relationship between these parameters and proposes some theoretical bounds in achieving a good tradeoff. The analysis primarily focuses on the bit extraction method proposed in [1] and its performance is compared with a scalar quantization based hashing method.
The origin of glutamatergic synaptic inputs controls synaptic plasticity and its modulation by alcohol in mice nucleus accumbens

It is widely accepted that long-lasting changes of synaptic strength in the nucleus accumbens (NAc), a brain region involved in drug reward, mediate acute and chronic effects of alcohol. However, our understanding of the mechanisms underlying the effects of alcohol on synaptic plasticity is limited by the fact that the NAc receives glutamatergic inputs from distinct brain regions (e.g., the prefrontal cortex (PFCx), the amygdala and the hippocampus), each region providing different information (e.g., spatial, emotional and cognitive). Combining whole-cell patch-clamp recordings and the optogenetic technique, we examined synaptic plasticity, and its regulation by alcohol, at cortical, hippocampal and amygdala inputs in fresh slices of mouse tissue. We showed that the origin of synaptic inputs determines the basic properties of glutamatergic synaptic transmission, the expression of spike-timing dependent long-term depression (tLTD) and long-term potentiation (LTP) and long-term potentiation (tLTP) and their regulation by alcohol. While we observed both tLTP and tLTD at amygadala and hippocampal synapses, we showed that cortical inputs only undergo tLTD. Functionally, we provide evidence that acute Ethyl Alcohol (EtOH) has little effects on higher order information coming from the PFCx, while severely impacting the ability of emotional and contextual information to induce long-lasting changes of synaptic strength.
Detection of Node Replication Attack using Distributed Multicast Approach in Wireless Sensor Networks

— Wireless sensor network (WSN) has become a growing research area due to its tremendous number of applications which can benefit from it. WSN are often deployed in unfavourable environments where an attacker can capture various nodes and replicate them to take over the network. The defence against node replication attacks are few and suffer from high overhead with respect to computation cost and memory. To find the replicas in the network, distributed detection approach is employed. The basic challenge of this approach is to minimize the communication and per node memory costs. With the use of distributed approach the node replicas can be captured efficiently. The results are expected to compare the different variants with respect to communication cost and memory.
From Patches to Images: A Nonparametric Generative Model

We propose a hierarchical generative model that captures the self-similar structure of image regions as well as how this structure is shared across image collections. Our model is based on a novel, variational interpretation of the popular expected patch log-likelihood (EPLL) method as a model for randomly positioned grids of image patches. While previous EPLL methods modeled image patches with finite Gaussian mixtures, we use nonparametric Dirichlet process (DP) mixtures to create models whose complexity grows as additional images are observed. An extension based on the hierarchical DP then captures repetitive and self-similar structure via imagespecific variations in cluster frequencies. We derive a structured variational inference algorithm that adaptively creates new patch clusters to more accurately model novel image textures. Our denoising performance on standard benchmarks is superior to EPLL and comparable to the state-ofthe-art, and we provide novel statistical justifications for common image processing heuristics. We also show accurate image inpainting results.
Please Scroll down for Article Connection Science Developmental Robotics: a Survey Developmental Robotics: a Survey

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Abstract. Developmental robotics is an emerging field located at the intersection of robotics, cognitive science and developmental sciences. This paper elucidates the main reasons and key motivations behind the convergence of fields with seemingly disparate interests, and shows why developmental robotics might prove to be beneficial for all fields involved. The methodology advocated is synthetic and two-pronged: on the one hand, it employs robots to instantiate models originating from developmental sciences; on the other hand, it aims to develop better robotic systems by exploiting insights gained from studies on ontogenetic development. This paper gives a survey of the relevant research issues and points to some future research directions. 1. Introduction Developmental robotics is an emergent area of research at the intersection of robotics and developmental sciences—in particular developmental psychology and developmental neuroscience. It constitutes an interdisciplinary and two-pronged approach to robotics, which on one side employs robots to instantiate and investigate models originating from developmental sciences, and on the other side seeks to design better robotic systems by applying insights gained from studies on ontogenetic development.
Modelling mitral valvular dynamics–current trend and future directions

Dysfunction of mitral valve causes morbidity and premature mortality and remains a leading medical problem worldwide. Computational modelling aims to understand the biomechanics of human mitral valve and could lead to the development of new treatment, prevention and diagnosis of mitral valve diseases. Compared with the aortic valve, the mitral valve has been much less studied owing to its highly complex structure and strong interaction with the blood flow and the ventricles. However, the interest in mitral valve modelling is growing, and the sophistication level is increasing with the advanced development of computational technology and imaging tools. This review summarises the state‐of‐the‐art modelling of the mitral valve, including static and dynamics models, models with fluid‐structure interaction, and models with the left ventricle interaction. Challenges and future directions are also discussed.
Short pulse development and debris mitigation studies for the HELEN laser

AWE has operated lasers for studying the properties of materials at high temperatures and pressures since the early 1970s [1]. A brief review of those facilities will be given along with a description of the changes to HELEN in the period 2003 - 2005 to enable it to provide both chirped pulse amplification [CPA] pulses and nanosecond pulses to laser targets simultaneously. The CPA beam is now giving laser pulses of typically 70 Joules in 500 femtoseconds. As a necessary part of operating such a system it has been necessary to study how laser-target debris is distributed from both long and short pulse interactions so that the contamination or degradation of focussing optics during operational activities is minimised. The short pulse experiments and the characteristics of debris fields emanating from laser targets will be described. Damage thresholds were established for coated and uncoated debris shields with millimetre to centimetre size beams. Future developments of the laser facilities at AWE in this decade will also be described as well as possible debris mitigation options that may be employed.
Differential expression of odorant receptor genes involved in the sexual isolation of two Heliothis moths

Moth sexual communication systems are highly diverse, but the mechanisms underlying their evolutionary diversification remain unclear. Recently, genes coding for odorant receptors (ORs) OR6, OR14, OR15 and OR16 have been genetically associated with species‐specific male response to female pheromone blends in Heliothis virescens (Hv) and Heliothis subflexa (Hs). Quantitative real‐time PCR analysis indicates that expression of HvOR6, HsOR6, HvOR14, HsOR14, HvOR15 and HsOR15 is male biased, which supports the hypothesis that they have a role in mediating female sex pheromone detection. The genes HvOR14, HvOR15 and HvOR16 are expressed at higher levels than their corresponding orthologues HsOR14, HsOR15 and HsOR16 in male antennae, while HvOR6 and HsOR6 transcripts are equally abundant in male antennae. The lack of higher expression of any of the receptor genes in H. subflexa antennae suggests that interspecific sequence differences, rather than gene regulation differences, underly the species‐specific male response to pheromone components.
Link adaptation and power control for streaming services in EGPRS wireless networks

Using the MPEG-4 advanced audio coder (AAC) music as an example of streaming applications, we investigate the improvement of error performance for the streaming service by link adaptation and power control techniques in an enhanced general packet radio services (EGPRS) cellular network. A low packet error rate and variability are essential in providing a short error-burst length so that error concealment techniques can be effectively applied to music packets. We study the effects of a combined link adaptation and power control scheme (referred to as the error-based scheme) for achieving a target error rate and reducing error variability. By simulation, we compare the error performance of the error-based scheme at both the EGPRS block and AAC frame level with another adaptation algorithm (referred to as the throughput-based scheme) with a goal of maximizing overall network throughput. It is found that when offered with a similar traffic load, the former scheme can provide noticeable improvement of music quality over the throughput-based scheme. To achieve a similar AAC frame error rate, our results also show that the error-based scheme can increase the link throughput over the throughput-based scheme by 66.7% in one of our examples. These results reveal that by aiming at required error targets and thus reducing error variability, the error-based scheme for link adaptation and power control are helpful in improving quality and capacity for streaming applications.
Transcript Assembly and Quantification by RNA-Seq Reveals Differentially Expressed Genes between Soft-Endocarp and Hard-Endocarp Hawthorns

Hawthorn (Crataegus spp.) is an important pome with a long history as a fruit, an ornamental, and a source of medicine. Fruits of hawthorn are marked by hard stony endocarps, but a hawthorn germplasm with soft and thin endocarp was found in Liaoning province of China. To elucidate the molecular mechanism underlying the soft endocarp of hawthorn, we conducted a de novo assembly of the fruit transcriptome of Crataegus pinnatifida and compared gene expression profiles between the soft-endocarp and the hard-endocarp hawthorn varieties. De novo assembly yielded 52,673 putative unigenes, 20.4% of which are longer than 1,000 bp. Among the high-quality unique sequences, 35,979 (68.3%) had at least one significant match to an existing gene model. A total of 1,218 genes, represented 2.31% total putative unigenes, were differentially expressed between the soft-endocarp hawthorn and the hard-endocarp hawthorn. Among these differentially expressed genes, a number of lignin biosynthetic pathway genes were down-regulated while almost all the flavonoid biosynthetic pathway genes were strongly up-regulated, concomitant with the formation of soft endocarp. In addition, we have identified some MYB and NAC transcription factors that could potentially control lignin and flavonoid biosynthesis. The altered expression levels of the genes encoding lignin biosynthetic enzymes, MYB and NAC transcription factors were confirmed by quantitative RT-PCR. This is the first transcriptome analysis of Crataegus genus. The high quality ESTs generated in this study will aid future gene cloning from hawthorn. Our study provides important insights into the molecular mechanisms underlying soft endocarp formation in hawthorn.
Chinese in the Grammatical Framework: Grammar, Translation, and Other Applications Anonymous

Grammatical Framework (GF) is a grammar formalism based on type theory and functional programming. It is also a platform for multilingual applications such as translation, localization, and information retrieval. To enable non-linguist programmers to build linguistically precise applications, GF provides a Resource Grammar Library (RGL), which defines the basic syntax, morphology, and lexicon of languages in the form of easily usable software libraries. The RGL is an open-source collaborative project, which currently covers 30 languages with a shared tree structure. Chinese, in addition to basic RGL, has a translation lexicon of over 30,000 lemmas and a mobile translation app. This paper gives an overview of GF, emphasizing applications where Chinese is related to other languages. We also address the theoretical question how Chinese fits into the framework with a shared tree structure.
Realtime 3D position detection of human pupil

A real time 3D pupil position detection system necessary for non-contact and remote eye gaze detection allowing head displacement was developed. So far, methodology had been proposed that estimates 3D positions of eyes from their 2D positions detected from the face images captured by two stereo cameras. However, using eye position detection is not prospective for precise and stable eye gaze detection. In the method proposed in the present study, several near-infrared LEDs were arranged around the apertures of two cameras. These two sets of light sources were alternately switched on and off synchronously with the even/odd signal. After differentiating the bright and dark pupil images obtained from each of the two cameras, the center coordinates of the two pupils were detected. An image processing algorithm for precise and stable pupil detection, including the pupil detection method utilizing a blink, is described. In one of the experiments, the 3D position of the pupil of one eye was measured by the two stereo cameras. Another narrow camera, which detects the centers of both pupil and corneal reflection images necessary for eye gaze direction determination, placed on a pan-tile unit could be automatically directed toward the 3D pupil position.
Cluster Analysis for Outlier Detection

For many applications in knowledge discovery in databases finding outliers, rare events, is of importance. Outliers are observations, which deviate significantly from the rest of the data, so that it seems they are generated by another process (Hawkins, 1980). Such outlier objects often contain information about an untypical behavior of the system. However, outliers bias the results of many data mining methods like the mean value, the standard deviation or the positions of the prototypes of k-means clustering (Estivill-Castro, 2004; Keller, 2000). Therefore, before further analysis or processing of data is carried out with more sophisticated data mining techniques, identifying outliers is a crucial step. Usually, data objects are considered as outliers, when they occur in a region of extremely low data density. Many clustering techniques like possibilistic clustering (PCM) (Krishnapuram & Keller, 1993; Krishnapuram & Keller, 1996) or noise clustering (NC) (Dave, 1991; Dave & Krishnapuram, 1997) that deal with noisy data and can identify outliers, need good initializations or suffer from lack of adaptability to different cluster sizes (Rehm, Klawonn & Kruse, 2007). Distance-based approaches (Knorr, 1998; Knorr, Ng & Tucakov, 2000) have a global view on the data set. These algorithms can hardly treat data sets containing regions with different data density (Breuning, Kriegel, Ng & Sander, 2000). In this work we present an approach that combines a fuzzy clustering algorithm (Hoppner, Klawonn, Kruse & Runkler, 1999) (or any other prototype-based clustering algorithm) with statistical distribution-based outlier detection.
A Cognitive Hierarchy Model of Games

Players in a game are "in equilibrium" if they are rational, and accurately predict other players' strategies. In many experiments, however, players are not in equilibrium. An alternative is "cognitive hierarchy" (CH) theory, where each player assumes that his strategy is the most sophisticated. The CH model has inductively defined strategic categories: step 0 players randomize; and step k thinkers best-respond, assuming that other players are distributed over step 0 through step k - 1. This model fits empirical data, and explains why equilibrium theory predicts behavior well in some games and poorly in others. An average of 1.5 steps fits data from many games.
Cryogenic Fiber Optic Temperature Sensors Based on Fiber Bragg Gratings

Results for several cryogenic fiber optic sensors based on fiber Bragg gratings (FBG) will be presented. Bragg gratings are periodic changes in the index of refraction in the fiber core that reflect light at a specific wavelength. The peak wavelength also depends on the strain in the FBG. A shift in the peak position can be used to measure strain or temperature. Temperature sensitivity is directly related to the thermal coefficient of expansion (TCE). Results of different high‐TCE materials including Polypropylene (PP), PMMA (polymethyl methacrylate), and Teflon (PFA) will be presented. We will present results from LN2 thermal cycling, calibration from 10 K to 300 K, and dynamic fatigue tests at ambient and LN2. Calibration results demonstrated PP coated FBG with sensitivity greater than 40 pm/K at 77 K. Sensitivity at 20 K was approximately 7 pm/K. A wavelength resolution of 10 pm would translate to a temperature resolution of +/−0.5 K at 77 K and +/− 1.5 K at 20 K. The FBG sensors were tested for dynami.