Miracle-dz/UniFAR-FTUs huggingface dataset:
Citation for Published Item: Use Policy Measuring the Effect of Gaming Experience on Virtual Environment Navigation Tasks

or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that: • a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders. Please consult the full DRO policy for further details. ABSTRACT Virtual environments are synthetic 3D worlds typically viewed from a first-person point of view with many potential applications within areas such as visualisation, entertainment and training simulators. To effectively develop and utilise virtual environments, user-centric evaluations are commonly performed. Anecdotal evidence suggests that factors such as prior experience with computer games may affect the results of such evaluations. This paper examines the effects of previous computer gaming experience, user perceived gaming ability and actual gaming performance on navigation tasks in a virtual environment. Two computer games and a virtual environment were developed to elicit performance metrics for use within a user study. Results indicated that perceived gaming skill and progress in a First-Person-Shooter (FPS) game were the most consistent metrics showing significant correlations with performance in time-based navigation tasks. There was also strong evidence that these relations were significantly intensified by the inclusion of participants who play FPS games. In addition, it was found that increased gaming experience decreased spatial perception performance.
Deep autoencoders augmented with phone-class feature for reverberant speech recognition

This paper addresses reverberant speech recognition based on front-end processing using DAE (Deep AutoEncoder) coupled with DNN (Deep Neural Network) acoustic model. DAE can effectively and flexibly learn mapping from corrupted speech to the original clean speech based on the deep learning scheme. While this mapping is conventionally conducted only with the acoustic information, we presume the mapping is also dependent on the phone information. Therefore, we propose a new scheme (pDAE), which augments a phone-class feature to the standard acoustic features as input. Two types of the phone-class feature are investigated. One is the hard recognition result of monophones, and the other is a soft representation derived from the posterior outputs of monophone DNN. In the evaluation on the Reverb Challenge 2014 task, the augmented feature in either type results in a significant improvement (7-8% relative) from the standard DAE. It is also shown that using the soft representation in the training phase is critical.
Haplotype reconstruction for scnp DNA: a consensus vote approach with extensive sequence data from populations of the migratory locust (Locusta migratoria)

Single copy nuclear polymorphic (scnp) DNA is potentially a powerful molecular marker for evolutionary studies of populations. However, a practical obstacle to its employment is the general problem of haplotype determination due to the common occurrence of heterozygosity in diploid organisms. We explore here a ‘consensus vote’ (CV) approach to this question, combining statistical haplotype reconstruction and experimental verification using as an example an indel‐free scnp DNA marker from the flanking region of a microsatellite locus of the migratory locust. The raw data comprise 251‐bp sequences from 526 locust individuals (1052 chromosomes), with 71 (28.3%) polymorphic nucleotide sites (including seven triallelic sites) and 141 distinct genotypes (with frequencies ranging from 0.2 to 25.5%). Six representative statistical haplotype reconstruction algorithms are employed in our CV approach, including one parsimony method, two expectation–maximization (EM) methods and three Bayesian methods. The phases of 116 ambiguous individuals inferred by this approach are verified by molecular cloning experiments. We demonstrate the effectiveness of the CV approach compared to inferences based on individual statistical algorithms. First, it has the unique power to partition the inferrals into a reliable group and an uncertain group, thereby allowing the identification of the inferrals with greater uncertainty (12.7% of the total sample in this case). This considerably reduces subsequent efforts of experimental verification. Second, this approach is capable of handling genotype data pooled from many geographical populations, thus tolerating heterogeneity of genetic diversity among populations. Third, the performance of the CV approach is not influenced by the number of heterozygous sites in the ambiguous genotypes. Therefore, the CV approach is potentially a reliable strategy for effective haplotype determination of nuclear DNA markers. Our results also show that rare variations and rare inferrals tend to be more vulnerable to inference error, and hence deserve extra surveillance.
Towards uncovering the roles of switchgrass peroxidases in plant processes

Herbaceous perennial plants selected as potential biofuel feedstocks had been understudied at the genomic and functional genomic levels. Recent investments, primarily by the U.S. Department of Energy, have led to the development of a number of molecular resources for bioenergy grasses, such as the partially annotated genome for switchgrass (Panicum virgatum L.), and some related diploid species. In its current version, the switchgrass genome contains 65,878 gene models arising from the A and B genomes of this tetraploid grass. The availability of these gene sequences provides a framework to exploit transcriptomic data obtained from next-generation sequencing platforms to address questions of biological importance. One such question pertains to discovery of genes and proteins important for biotic and abiotic stress responses, and how these components might affect biomass quality and stress response in plants engineered for a specific end purpose. It can be expected that production of switchgrass on marginal lands will expose plants to diverse stresses, including herbivory by insects. Class III plant peroxidases have been implicated in many developmental responses such as lignification and in the adaptive responses of plants to insect feeding. Here, we have analyzed the class III peroxidases encoded by the switchgrass genome, and have mined available transcriptomic datasets to develop a first understanding of the expression profiles of the class III peroxidases in different plant tissues. Lastly, we have identified switchgrass peroxidases that appear to be orthologs of enzymes shown to play key roles in lignification and plant defense responses to hemipterans.
Decentralized algorithms for collision avoidance in airspace

The paper proposes decentralized deconfliction algorithms deployed on multiple autonomous aerial vehicles in freeflight operations. The paper provides two separate algorithms for collision avoidance - one based on the iterative peer-to-peer negotiation solving a singular collision and second based on multi-party negotiation about a cluster of collisions. The presented decentralized algorithms allow the vehicles operating in the same area to utilize the given airspace more efficiently. The algorithms have been developed and tested on a multi-agent prototype and the properties of both algorithms are discussed on a set of large scale experiments.
Automated Prediction of Preferences Using Facial Expressions

We introduce a computer vision problem from social cognition, namely, the automated detection of attitudes from a person's spontaneous facial expressions. To illustrate the challenges, we introduce two simple algorithms designed to predict observers’ preferences between images (e.g., of celebrities) based on covert videos of the observers’ faces. The two algorithms are almost as accurate as human judges performing the same task but nonetheless far from perfect. Our approach is to locate facial landmarks, then predict preference on the basis of their temporal dynamics. The database contains 768 videos involving four different kinds of preferences. We make it publically available.
A numerical investigation on oil mist behavior used in Minimum Quantity Lubrication milling process

This paper predicts MQL projection on cutting inserts for different rotating velocities of a milling tool. The numerical model is based on a steady Reynolds-Average Navier-Stokes (RANS) formulation and multiphase Eularian-Lagrangian model to predict the air-oil flows. Pressure configurations and the orientation of the oil particles are studied. This study leads to a better understanding of the oil mist behavior in order to get the optimized design of the tool leading to various lubrication configurations taking into account the type of machining.
A time-scale decomposition approach to optimize wireless packet resource allocation and scheduling

Wireless channels are error-prone and susceptible to several kinds of interference from different time scales. This paper investigates the resource optimization and scheduling of wireless networks through a time-scale decomposition approach. We decompose the dynamics of time-varying wireless channel conditions into two random processes in different time scales: a slow time-varying process in a larger time scale, called frame-scale, and a stationary random process with high variation in a smaller time scale, called slot-scale. This results in two different algorithms dealing with each time-scale: the resource optimizer optimize the sum of utilities in the slowly changed time scale, and the slot scheduler exploits the efficiency in the highly variable time scale. Our scheme can obtain a high utilization while providing service guarantee. Simulation results show our scheme can improve the performance and efficiency substantially.
A system for real-time deformable terrain

Terrain constitutes an important part of many virtual environments. In computer games or simulations it is often useful to allow the user to modify the terrain since this can help to foster immersion. Unfortunately, real-time deformation schemes can be expensive and most game engines simply substitute proxy geometry or use texturing to create the illusion of deformation. We present a new terrain deformation framework which is able to produce persistent, real-time deformation by utilising the capabilities of current generation GPUs. Our method utilises texture storage, a terrain level-of-detail scheme and a tile-based terrain representation to achieve high frame rates. To accommodate a range of hardware, we provide deformation schemes for hardware with and without geometry tessellation units. Deformation using the fragment shader (no tessellation) is significantly faster than the geometry shader (tessellation) approach, although this does come at the cost of some high resolution detail. Our tests show that both deformation schemes consume a comparatively small proportion of the GPU per frame budget and can thus be integrated into more complex virtual environments.
The Metal Cation Chelating Capacity of Astaxanthin. Does This Have Any Influence on Antiradical Activity?

In this Density Functional Theory study, it became apparent that astaxanthin (ASTA) may form metal ion complexes with metal cations such as Ca+2, Cu+2, Pb+2, Zn+2, Cd+2 and Hg+2. The presence of metal cations induces changes in the maximum absorption bands which are red shifted in all cases. Therefore, in the case of compounds where metal ions are interacting with ASTA, they are redder in color. Moreover, the antiradical capacity of some ASTA-metal cationic complexes was studied by assessing their vertical ionization energy and vertical electron affinity, reaching the conclusion that metal complexes are slightly better electron donors and better electron acceptors than ASTA.
How to exploit large image data in the fields of texture classification: A case study with local binary patterns

In the fields of texture classification, the sizes of images significantly vary according to the respective classification scenario. Whereas quite small image patches mostly lead to good classification accuracies, increasing the image size sometimes even has a negative effect. In this work, we focus on derivatives of Local Binary Patterns as these feature extraction methods offer a high discriminative power and efficiency on the one hand an can be effectively analyzed on the other hand. The aim is to get new insight and furthermore to explore strategies which can help to increase the classification performance. We investigate these strategies which exploit the obviously high distinctiveness of small image patches and simultaneously the redundancy available in large image patches. Finally it can be concluded that the traditionally applied strategies for texture classification should be reconsidered in case of sufficiently large image data.
Gene Knock-Outs of Inositol 1,4,5-Trisphosphate Receptors Types 1 and 2 Result in Perturbation of Cardiogenesis

Background Inositol 1,4,5-trisphosphate receptors (IP3R1, 2, and 3) are intracellular Ca2+ release channels that regulate various vital processes. Although the ryanodine receptor type 2, another type of intracellular Ca2+ release channel, has been shown to play a role in embryonic cardiomyocytes, the functions of the IP3Rs in cardiogenesis remain unclear. Methodology/Principal Findings We found that IP3R1−/−-IP3R2−/− double-mutant mice died in utero with developmental defects of the ventricular myocardium and atrioventricular (AV) canal of the heart by embryonic day (E) 11.5, even though no cardiac defect was detectable in IP3R1−/− or IP3R2−/− single-mutant mice at this developmental stage. The double-mutant phenotype resembled that of mice deficient for calcineurin/NFATc signaling, and NFATc was inactive in embryonic hearts from the double knockout-mutant mice. The double mutation of IP3R1/R2 and pharmacologic inhibition of IP3Rs mimicked the phenotype of the AV valve defect that result from the inhibition of calcineurin, and it could be rescued by constitutively active calcineurin. Conclusions/Significance Our results suggest an essential role for IP3Rs in cardiogenesis in part through the regulation of calcineurin-NFAT signaling.
Fine-Grained Categorization for 3D Scene Understanding

Fine-grained categorization of object classes is receiving increased attention, since it promises to automate classification tasks that are difficult even for humans, such as the distinction between different animal species. In this paper, we consider fine-grained categorization for a different reason: following the intuition that fine-grained categories encode metric information, we aim to generate metric constraints from fine-grained category predictions, for the benefit of 3D scene-understanding. To that end, we propose two novel methods for fine-grained classification, both based on part information, as well as a new fine-grained category data set of car types. We demonstrate superior performance of our methods to state-of-the-art classifiers, and show first promising results for estimating the depth of objects from fine-grained category predictions from a monocular camera.
Software Engineering in the Embedded Software and Mobile Robot Software Development: A Systematic Mapping

Currently, embedded software have been required more and more by a diversity of new products. As a consequence, an increase in the software complexity can be observed, requiring more attention to the software quality. Initiatives of exploring software engineering knowledge to develop this type of software can be identified, resulting in the Embedded Software Engineering (ESE) research area. However, there is a lack of a complete panorama about researches conducted in the context of ESE. This paper intends to present a view about how software engineering has been currently used in the embedded software development. For this, we have used systematic mapping, a technique based on the Evidence-Based Software Engineering (EBSE). Achieved results point out that in spite of the increase in the interest of applying software engineering to develop embedded software, there are still important lines of research that must receive attention.
HumanRcoarseR poseRdiscretization ( labels ) 3 DRModelRfine poseRdiscretization ( angles ) AnnotationRimage 45 °

The quality of learning-based pose estimation still heavily relies on manual training data annotations. However, the manual labeling of large datasets is costly and frequently limited to a few coarse viewpoint annotations of varying accuracy. In this work, we propose to refine such coarse pose annotations with a domain adaptation approach, where the source domain consists of fine-grained pose annotations generated from synthetic computer graphics models, and the target domain of coarse manual pose annotations of a real dataset. Our domain adaptation step computes a linear map which aligns corresponding samples from the two domains and allows for the refinement of the manual pose labels using the transformed synthetic ones. Experiments show that we significantly improve pose estimation on several state-of-the-art car datasets.
Aging behavior of cellulosic materials in presence of mineral oil and ester liquids under various conditions

This paper is aimed at the study of aging behavior of cellulosic materials in different dielectric liquids under air and nitrogen atmospheres. Paper for copper conductor and high density transformer board were aged at 130°C up to 1128 h in sealed vessels in presence of mineral oil (MO), natural ester (VO) and synthetic ester (SE). The influence of thermal aging on cellulose and oil characteristics are investigated and compared. It's observed that the paper degradation is associated with the generation of CO2 and CO gases. Whatever the type of oil, this generation is more important with vessel under air atmosphere than that under nitrogen gap indicating a protective effect of nitrogen. In mineral oil, the degree of polymerization (DPv) reaches the end of life criteria at around 200 whereas it remains around 400 with ester oils. This is mainly due to the higher water solubility of esters compared to mineral oil. The measured degree of polymerization in MO is comparable to that calculated through 2-FAL (Furanic compounds) content using Vuarchex equation whereas for esters oil, there is no agreement between the measured and calculated DPv through 2-FAL content. This can constitute a limitation in the use of 2-FAL for the diagnosis of ester-filled transformers. Overall, the insulation cellulose/oil behavior seems better under nitrogen atmosphere.
Restoration of axon conduction and motor deficits by therapeutic treatment with glatiramer acetate

Glatiramer acetate (GA; Copaxone) is an approved drug for the treatment of multiple sclerosis (MS). The underlying multifactorial anti-inﬂammatory, neuroprotective effect of GA is in the induction of reactive T cells that release immunomodulatory cytokines and neurotrophic factors at the injury site. These GA-induced cytokines and growth factors may have a direct effect on axon function. Building on previous ﬁndings that suggest a neuroprotective effect of GA, we assessed the therapeutic effects of GA on brain and spinal cord pathology and functional correlates using the chronic experimental autoimmune encephalomyelitis (EAE) mouse model of MS. Therapeutic regimens were uti-lized based on promising prophylactic efﬁcacy. More spe-ciﬁcally, C57BL/6 mice were treated with 2 mg/mouse/day GA for 8 days beginning at various time points after EAE post-induction day 15, yielding a thorough, clinically relevant assessment of GA efﬁcacy within the context of severe progressive disease. Therapeutic treatment with GA signiﬁcantly decreased clinical scores and improved rotorod motor performance in EAE mice. These functional improvements were supported by an increase in myelinated axons and fewer amyloid precursor protein-positive axons in the spinal cords of GA-treated EAE mice. Further-more, therapeutic GA decreased microglia/macrophage and T cell inﬁltrates and increased oligodendrocyte numbers in both the spinal cord and corpus callosum of EAE mice. Finally, GA improved callosal axon conduction and nodal protein organization in EAE. Our results demonstrate that therapeutic GA treatment has signiﬁcant beneﬁcial effects in a chronic mouse model of MS, in which its posi-tive effects on both myelinated and non-myelinated axons results in improved axon function.
Stability of equilibria in quantitative genetic models based on modified-gradient systems

ABSTRACT Motivated by questions in biology, we investigate the stability of equilibria of the dynamical system which arise as critical points of f, under the assumption that is positive semi-definite. It is shown that the condition , where is the smallest eigenvalue of , plays a key role in guaranteeing uniform asymptotic stability and in providing information on the basis of attraction of those equilibria.
Advanced Glycation End-products Enhance Calcification in Vascular Smooth Muscle Cells

Advanced glycation end-products (AGEs), senescent macroprotein derivatives formed at an accelerated rate in diabetes, are closely associated with vascular calcification in humans. In this study, the hypothesis that AGEs enhance calcification in cultured vascular smooth muscle cells (VSMCs) was tested. Using real-time polymerase chain reaction (PCR) and specific protein assays, it was demonstrated that rat aortic VSMCs incubated with AGEs exhibited an increased expression of the AGE receptor (RAGE) and typical bone proteins, such as osteopontin and alkaline phosphatase. Incubation with AGEs also enhanced calcium accumulation in VSMCs in time-and dose-dependent manners. These AGEs-mediated changes in VSMCs were partially attenuated by a neutralizing antibody to RAGE. The results suggest that AGEs that accumulate in diabetes could elicit the osteoblastic differentiation of VSMCs, thereby contributing to vascular calcification via the RAGE pathway. Interruption of the AGE-RAGE interaction might be a promising target for therapeutic intervention to prevent diabetic vascular calcification.
Degassing of reduced carbon from planetary basalts

Degassing of planetary interiors through surface volcanism plays an important role in the evolution of planetary bodies and atmospheres. On Earth, carbon dioxide and water are the primary volatile species in magmas. However, little is known about the speciation and degassing of carbon in magmas formed on other planets (i.e., Moon, Mars, Mercury), where the mantle oxidation state [oxygen fugacity (fO2)] is different from that of the Earth. Using experiments on a lunar basalt composition, we confirm that carbon dissolves as carbonate at an fO2 higher than -0.55 relative to the iron wustite oxygen buffer (IW-0.55), whereas at a lower fO2, we discover that carbon is present mainly as iron pentacarbonyl and in smaller amounts as methane in the melt. The transition of carbon speciation in mantle-derived melts at fO2 less than IW-0.55 is associated with a decrease in carbon solubility by a factor of 2. Thus, the fO2 controls carbon speciation and solubility in mantle-derived melts even more than previous data indicate, and the degassing of reduced carbon from Fe-rich basalts on planetary bodies would produce methane-bearing, CO-rich early atmospheres with a strong greenhouse potential.