Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of educational use of games and simulations.

Number Title WP D 1 Review of educational use of games and simulations 1 This work has been carried out under the IST fifth framework programme. This study examines the theoretical analyses and empirical results from research in the area of instructional use of games and simulations. It mainly focuses on approaches taken in designing game(like) learning environments and distils a list of characteristics of games from the instructional theory. It also tries to find evidence concerning the appropriate learning approaches and measures which can optimise the learning effects of games and simulations. In this analysis we also look at a related instructional methods: the use of case studies, a method that is very common in the training of management techniques. A second analysis that is made in this study concerns solving ill-defined or wicked problems. In the KITS context the knowledge management situations can be characterised as being ill-defined. Both analyses result in a set of requirements for the KITS learning environment. The starting points of the KITS project are shortly introduced in Chapter 1. Chapter 2 starts by defining the concept of 'game' and gives a list of characteristics of 'games' based on a literature study. This resulted in the following definition: Games are competitive, situated (learning) environments based on a set of rules and/or an underlying model , in which, under certain constraints, some goal state must be reached. Games are situated in a specific context that make them (more or less) realistic, appealing and motivating for the players. Important elements that are related to the situatedness of games are validity/fidelity, complexity, risk, uncertainty, surprise, unexpected events, role-play, access to information, and the representation form of the game. Games as learning environments are closely related to simulations, microworlds, adventures and case studies. The definitions of these environments partially overlap. For instance, the distinction between simulation and games is often blurred, and many recent articles in this area refer to a single " simulation game " entity. The educational goals of games depend on the setting in which they are used and can be very diverse like: development of consciousness and motivation, training of skills, development of knowledge and insight, training in communication and cooperation , integration of learning experiences, and assessment. Much of the work on the evaluation of games has been anecdotal, descriptive or judgmental, but there are some indications that they are effective and are …
Information-theoretically optimal sparse PCA

Sparse Principal Component Analysis (PCA) is a dimensionality reduction technique wherein one seeks a low-rank representation of a data matrix with additional sparsity constraints on the obtained representation. We consider two probabilistic formulations of sparse PCA: a spiked Wigner and spiked Wishart (or spiked covariance) model. We analyze an Approximate Message Passing (AMP) algorithm to estimate the underlying signal and show, in the high dimensional limit, that the AMP estimates are information-theoretically optimal. As an immediate corollary, our results demonstrate that the posterior expectation of the underlying signal, which is often intractable to compute, can be obtained using a polynomial-time scheme. Our results also effectively provide a single-letter characterization of the sparse PCA problem.
In and out of the loop: external and internal modulation of the olivo-cerebellar loop

Cerebellar anatomy is known for its crystal like structure, where neurons and connections are precisely and repeatedly organized with minor variations across the Cerebellar Cortex. The olivo-cerebellar loop, denoting the connections between the Cerebellar cortex, Inferior Olive and Cerebellar Nuclei (CN), is also modularly organized to form what is known as the cerebellar module. In contrast to the relatively organized and static anatomy, the cerebellum is innervated by a wide variety of neuromodulator carrying axons that are heterogeneously distributed along the olivo-cerebellar loop, providing heterogeneity to the static structure. In this manuscript we review modulatory processes in the olivo-cerebellar loop. We start by discussing the relationship between neuromodulators and the animal behavioral states. This is followed with an overview of the cerebellar neuromodulatory signals and a short discussion of why and when the cerebellar activity should be modulated. We then devote a section for three types of neurons where we briefly review its properties and propose possible neuromodulation scenarios.
The Arabidopsis RESURRECTION 1 Gene Regulates a Novel Antagonistic Interaction in Plant Defense to Biotrophs and Necrotrophs 1 [ W ] [ OA ]

Department of Horticulture and Landscape Architecture (H.G.M., E.P.P., D.K.K., B.R.C., H.C.P., R.A.B., M.A.J.) and Department of Botany and Plant Pathology (K.A.L., S.A., T.M.), Purdue University, West Lafayette, Indiana 47907–2054; Department of Plant Protection, Università degli Studi Della Tuscia, 01100 Viterbo, Italy (C.B., G.C.); Department of Plant Biology and Crop Science, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (S.M., H.J.B.); Consiglio Nazionale delle Ricerche-Istituto di Genetica Vegetale, Institute of Plant Genetics, 80055 Portici, Italy (F.C.); and Division of Applied Life Science, Gyeongsang National University, Jinju 660–701, Korea (R.A.B.)
Facial Image Hallucination Through Coupled-Layer Neighbor Embedding

As the facial image captured by a low-cost camera is typically very low resolution (LR), blurring, and noisy, traditional neighbor-embedding-based facial image hallucination methods from one single manifold (i.e., the LR image manifold) fail to reliably estimate the intention geometrical structure, consequently leading to a bias to the image reconstruction result. In this paper, we introduce the notion of neighbor embedding (NE) from the LR and the high-resolution (HR) image manifolds simultaneously and propose a novel NE model, termed the coupled-layer NE (CLNE), for facial image hallucination. CLNE differs substantially from other NE models in that it has two layers: the LR and the HR layers. The LR layer in this model is the local geometrical structure of the LR patch manifold, which is characterized by the reconstruction weights of the LR patches; the HR layer is the intrinsic geometry that can geometrically constrain the reconstruction weights. With this coupled-constraint paradigm between the adaptation of the LR layer and the HR one, CLNE can achieve a more robust NE through iteratively updating the LR patch reconstruction weights and the estimated HR patch. The experimental results in simulation and real conditions confirm that the proposed method outperforms the related state-of-the-art methods in both quantitative and visual comparisons.
Crashes, Volatility, and the Equity Premium: Lessons from S&P 500 Options

We use a novel pricing model to imply time series of diffusive volatility and jump intensity from S&P 500 index options. These two measures capture the ex ante risk assessed by investors. Using a simple general equilibrium model, we translate the implied measures of ex ante risk into an ex ante risk premium. The average premium that compensates the investor for the ex ante risks is 70 higher than the premium for realized volatility. The equity premium implied from option prices is shown to significantly predict subsequent stock market returns.
Speech Enhancement using a Deep Mixture of Experts

In this study we present a Deep Mixture of Experts (DMoE) neural-network architecture for single microphone speech enhancement. By contrast to most speech enhancement algorithms that overlook the speech variability mainly caused by phoneme structure, our framework comprises a set of deep neural networks (DNNs), each one of which is an 'expert' in enhancing a given speech type corresponding to a phoneme. A gating DNN determines which expert is assigned to a given speech segment. A speech presence probability (SPP) is then obtained as a weighted average of the expert SPP decisions, with the weights determined by the gating DNN. A soft spectral attenuation, based on the SPP, is then applied to enhance the noisy speech signal. The experts and the gating components of the DMoE network are trained jointly. As part of the training, speech clustering into different subsets is performed in an unsupervised manner. Therefore, unlike previous methods, a phoneme-labeled database is not required for the training procedure. A series of experiments with different noise types verified the applicability of the new algorithm to the task of speech enhancement. The proposed scheme outperforms other schemes that either do not consider phoneme structure or use a simpler training methodology.
Nanomedicine applications in orthopedic medicine: state of the art

The technological and clinical need for orthopedic replacement materials has led to significant advances in the field of nanomedicine, which embraces the breadth of nanotechnology from pharmacological agents and surface modification through to regulation and toxicology. A variety of nanostructures with unique chemical, physical, and biological properties have been engineered to improve the functionality and reliability of implantable medical devices. However, mimicking living bone tissue is still a challenge. The scope of this review is to highlight the most recent accomplishments and trends in designing nanomaterials and their applications in orthopedics with an outline on future directions and challenges.
Certainty-Enhanced Active Learning for Improving Imbalanced Data Classification

In active learning algorithms, informative samples are usually queried for true labels according to the disagreement of existing hypotheses. However we observed that, when the streaming dataset has skewed class membership, the imbalanced data classification problem is caused in active learning. The Minority class is overwhelmed by the majority class in generating the hypotheses. In this paper, for each unlabeled sample we propose to utilize only local behavior in the certainty-enhanced neighborhood, rather than the entire dataset, to generate the error minimization hypotheses. Consequently, our proposed method enhances the prediction of hypotheses and is able to determine the query probabilities properly. In our experiments, synthetic and real-world datasets are used for presenting the effectiveness of our active learning approach. It is shown that the proposed approach decreases the probability of querying a certain (majority) sample and has the ability of dealing with the imbalanced data classification problem in active learning.
Universal Dependencies for Persian

The Persian Universal Dependency Treebank (Persian UD) is a recent effort of treebanking Persian with Universal Dependencies (UD), an ongoing project that designs unified and cross-linguistically valid grammatical representations including part-of-speech tags, morphological features, and dependency relations. The Persian UD is the converted version of the Uppsala Persian Dependency Treebank (UPDT) to the universal dependencies framework and consists of nearly 6,000 sentences and 152,871 word tokens with an average sentence length of 25 words. In addition to the universal dependencies syntactic annotation guidelines, the two treebanks differ in tokenization. All words containing unsegmented clitics (pronominal and copula clitics) annotated with complex labels in the UPDT have been separated from the clitics and appear with distinct labels in the Persian UD. The treebank has its original syntactic annotation scheme based on Stanford Typed Dependencies. In this paper, we present the approaches taken in the development of the Persian UD.
On the Problem of Moving Objects With Autonomous Robots: A Unifying High-Level Planning Approach

Moving objects with autonomous robots is a wide topic that includes single-arm pick-and-place tasks, object regrasping, object passing between two or more arms in the air or using support surfaces such as tables and similar. Each task has been extensively studied and many planning solutions are already present in the literature. In this letter, we present a planning scheme which, based on the use of pre-defined elementary manipulation skills, aims to unify solutions which are usually obtained by means of different planning strategies rooted on hard-coded behaviors. Both robotic manipulators and environment fixed support surfaces are treated as end-effectors of movable and non-movable types, respectively. The task of the robot can thus be broken down into elementary building blocks, which are end-effector manipulation skills, that are then planned at the kinematic level. Feasibility is ensured by propagating unforeseen low-level failures at the higher level and by synthesizing different behaviors. The validity of the proposed solution is shown via experiments on a bimanual robot setup and in simulations involving a more complex setup similar to an assembly line.
Loss of viral genomes from hamster tumor cells and nonrandom alterations in patterns of methylation of integrated adenovirus type 12 DNA

The insertion stability and DNA methylation patterns of integrated adenovirus type 12 (Ad12) genomes were investigated in Ad12-induced tumors and in tumor cell lines established from them as a function of time of passage under culture conditions. Upon subcultivation of cells from some of the tumors, the viral genomes were eliminated, apparently in a stepwise process with segments of the left termini of Ad12 DNAs persisting the longest. Morphological variants of these tumor cells lost all viral DNA and yet retained the oncogenic phenotype. All 13 independently isolated clones from one revertant line were devoid of Ad12 DNA. It could not be ruled out that very short sequence elements of viral DNA, such as promoters or enhancing sequences, could have persisted in these variants. The extent of viral DNA methylation was minimal in Ad12-induced tumors, although the viral genome was not extensively expressed, if at all. Upon passage in culture, the levels of viral DNA methylation increased. It was interesting that establishment of the final methylation pattern of integrated Ad12 DNAs required many cell generations after the fixation of foreign DNA in the host genome. The shift in methylation was nonrandom. The late parts of the inserted viral genomes became methylated more extensively than did the early gene segments.
Visible difference predicator for high dynamic range images

Since new imaging and rendering systems commonly use physically accurate lighting information in the form of high-dynamic range data, there is a need for an automatic visual quality assessment of the resulting images. In this work we extend the visual difference predictor (VDP) developed by Daly to handle HDR data. This let us predict if a human observer is able to perceive differences for a pair of HDR images under the adaptation conditions corresponding to the real scene observation.
A Single-Chip 125-MHz to 32-GHz Signal Source in 0.18-$\mu$m SiGe BiCMOS

We present a 4.4-mm2 single-chip synthesized signal source with 125 MHz to 32 GHz continuous frequency coverage with a minimum frequency step smaller than 10 Hz. The chip is fabricated in a 0.18-μm SiGe BiCMOS 1P6M technology. A core fractional-N synthesizer using a 20-MHz reference frequency has four LC-VCOs and a 4- to 8-GHz synthesizable range. Post-synthesis blocks extend the frequency coverage up to 32 GHz and down to 125 MHz through frequency multiplication and division. In different operation modes, the chip, including a balanced 50-ohm load driver, consumes from 284 to 498 mW. The phase noise performance achieves -117.6 dBc/Hz at 1-MHz offset from a 6-GHz output frequency and -83 dBc/Hz in-band noise. The integrated phase noise is -28 dBc and the absolute jitter is 1.05 psRMS at 6-GHz output. The jitter is maintained nearly constant (between 0.9 and 1.2 psRMS) across the whole output frequency range.
PRACTICAL APPLICATION OF ENVIRONMENTAL RISK MANAGEMENT-GORGON LNG PROJECT CASE STUDY

Stoklosa Engineering has been working with the petroleum industry to develop an environmental risk management methodology that can be generally applied to petroleum industry activities. In particular, the methodology is for assessing and managing ecological risk in sensitive marine environments. This paper introduces a management and technical methodology for the risk assessment process that has been applied to planning scenarios for the Gorgon LNG Project. The methodology has evolved from earlier efforts by petroleum operators and government in Western Australia to quantify ecological risk. The principles of Standards Australia risk management publications, State risk management initiatives and international approaches have been preserved in the methodology. The basis for a quantitative analysis of the likelihood of an incident is described, with a qualitative or semiquantitative analysis of the severity of the potential consequences. The technical approach adopts the principles of AS/NZS 4360 for risk management, and characterises risk for decision makers in an unambiguous manner. The methodology leads to a clear understanding of the benefits of risk management, and allows proponents the opportunity to reduce risk to acceptable levels. The risks of development should be interpreted in the context of naturally occurring hazards to environmental systems (e.g. cyclones and coral spawning slicks), human activities (e.g. recreation, fisheries and aquaculture), and the natural variability of ecosystems. The Gorgon LNG Project case study characterises risk in terms of credible incident scenarios and baseline operational activities from project planning scenarios. The inputs to the risk assessment are release scenarios, fate and transport modelling, response mechanisms in sensitive species, and recovery mechanisms following exposure. The methodology can be broadly applied to offshore and onshore development projects and environmental management programs, as it is presented as a repeatable process that can incorporate various types of risk analysis methods.
Ultra wideband wireless serial data communication at 10Gb/s in CMOS 90nm

This paper presents a novel transmitter structure serving as a bridge between high-speed serial data and low power ultra wideband (UWB) communication. A current mode logic (CML) based finite impulse response (FIR) structure is used to spectrally shape the data at the rate of 10 Gb/s with 5.36 pJ energy/bit consumption in CMOS 90 nm technology. Stacked inductors are used for wireless chip-to-chip transmission.
A Dynamic Emotion Representation Model within a Facial Animation System

This paper presents the Dynamic Emotion Representation (DER), and demonstrates how an instance of this model can be integrated into a facial animation system. The DER model has been implemented to enable users to create their own emotion representation. Developers can select which emotions they include and how these interact. The instance of the DER model described in this paper is composed of three layers, each representing states changing over different time scales: behavior activations, emotions and moods. The design of this DER is discussed with reference to emotion theories and to the needs of a facial animation system. The DER is used in our Emotionally Expressive Facial Animation System (EE-FAS) to produce emotional expressions, to select facial signals corresponding to communicative functions in relation to the emotional state of the agent and also in relation to the comparison between the emotional state and the intended meanings expressed through communicative functions.
Device-to-device content distribution: Optimal caching strategies and performance bounds

Content distribution using direct device-to-device (D2D) communication is a promising approach for optimizing the utilization of air-interface resources in 5G network. To achieve the best utilization of network resources, the network should bias the distribution of cached content. The optimal caching distribution depends on the content demand distribution. In this paper, we model the locations of transmitting and receiving devices by a homogeneous Poisson Point Process (PPP), and use results from stochastic geometry to derive the probability of successful content delivery in the presence of D2D interference and noise. We formulate an optimization problem to maximize the total probability of content delivery, assuming user demands are modeled by a Zipf distribution. We also develop strategies to optimize content caching, and bound the total coverage probability for multiple file caching scenarios.
Towards multi-scale query processing

This paper discusses our ongoing research efforts in regards to processing multi-scale queries in service-oriented environments. A multi-scale query is a query over traditional datasets in conjunction with streaming data and that may involve spatio-temporal aspects. In a service-oriented environment, classic and streaming data are made available and processed through services, which we refer to as data providers. We present an approach based on applying service composition techniques to data providers along with traditional database operators, resulting in query evaluation plans which, complemented by optimization and adaptation mechanisms, will enable flexible query processing and data integration among a diverse range of data sources in dynamic environments.
Post-Genomic Update on a Classical Candidate Gene for Coronary Artery Disease

Background— After age, sex is the most important risk factor for coronary artery disease (CAD). The mechanism through which women are protected from CAD is still largely unknown, but the observed sex difference suggests the involvement of the reproductive steroid hormone signaling system. Genetic association studies of the gene-encoding Estrogen Receptor &agr; (ESR1) have shown conflicting results, although only a limited range of variation in the gene has been investigated. Methods and Results— We exploited information made available by advanced new methods and resources in complex disease genetics to revisit the question of ESR1's role in risk of CAD. We performed a meta-analysis of 14 genome-wide association studies (CARDIoGRAM discovery analysis, N=≈87 000) to search for population-wide and sex-specific associations between CAD risk and common genetic variants throughout the coding, noncoding, and flanking regions of ESR1. In addition to samples from the MIGen (N=≈6000), WTCCC (N=≈7400), and Framingham (N=≈3700) studies, we extended this search to a larger number of common and uncommon variants by imputation into a panel of haplotypes constructed using data from the 1000 Genomes Project. Despite the widespread expression of ER&agr; in vascular tissues, we found no evidence for involvement of common or low-frequency genetic variation throughout the ESR1 gene in modifying risk of CAD, either in the general population or as a function of sex. Conclusions— We suggest that future research on the genetic basis of sex-related differences in CAD risk should initially prioritize other genes in the reproductive steroid hormone biosynthesis system.
AlÃ-eleLoss at the c-Ha-rasl Locus in Human Ovarian Cancer

Recent reports have shown alÃ-eleloss at the i--Ilu-n/. vl locus on the short arm of chromosome 11 in some types of tumors. To determine whether loss of heterozygosity occurs at the c-Ha-ras 1 locus in uncultured human ovarian carcinomas we used Southern blot analysis to study DNA from 17 pairs of ovarian tumors and matched white blood cell samples from the same patients. In one of these 17 tumors, the c-Ha-rail locus was rearranged, and in five tumor DNAs from ten informative patients, a c-Ha-rasl alÃ-ele was lost. This loss, of relatively high incidence, appears to be an important characteristic of human ovarian cancer and may provide a useful tool for understanding its biological behavior.