Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensory Biology: Echolocation from Click to Call, Mouth to Wing

in a distinct room. Crystal and Smith [3] argue that keeping separate in memory multiple episodes that share similar components is a central feature of bound memory representations. If the rats instead had just remembered each of the unbound aspects of each event, then performance would have suffered because the two events shared some of these aspects. Rats would have struggled to find the preferred chocolates in the correct locations when revisiting the mazes. But the authors found that rats were likely to go to maze arms that held chocolate, taking into account which room they were in, and how they had found chocolate in that room previously. This suggests that they remembered each experience (in each room) as an event with multiple, bound features. Whether these results indicate that the rats’ bound memories meet everyone’s definition of episodic memory (for example [1,2,16,17]) should not be the main issue. Perhaps they do not, but that makes these results no less important. Questions about whether animals do or do not show ‘mental time travel’ [16–18] sometimes can distract us from the equally important (and perhaps more immediately pressing) goal of establishing just how accurate and flexible thememories of animals can be when those memories are needed to generate intelligent behaviors (or, for those studying prospective cognition, just what kinds of anticipatory behaviors we can find in nonhuman animals). Certainly, consideration of whether these kinds of experiences have the qualities that are critical for human mental time travel will highlight aspects of the nature of animal consciousness, and can offer insights into the evolution of human cognitive abilities and consciousness. But there is at least equal importance in comparative cognitive science in documenting where and why success and failure occur in memory tasks, and how bound the components are for personal memories of the past, along with how episodic memories may serve an adaptive function in future oriented behaviors such as prospectivememory and planning [19,20]. Crystal and Smith [3] have provided compelling new data in this debate, showing that the binding of features is likely a widespread aspect of animal memory and one that is potentially of high translational value in terms of understanding some of the fundamental aspects of human memory.
ALEXANDER PYATTAEV SYSTEM LEVEL PERFORMANCE EVALUATION OF CLIENT COOPERATION IN WIRELESS CELLULAR NETWORKS Master’s thesis

TAMPERE UNIVERSITY OF TECHNOLOGY Master’s Degree Programme in Information Technology PYATTAEV, ALEXANDER: ”SYSTEM LEVEL PERFORMANCE EVALUATION OF CLIENT COOPERATION IN WIRELESS CELLULAR NETWORKS” Master of Science Thesis, 48 pages, 15 appended pages November, 2011 Major subject: Communications Engineering Examiners: Professor Yevgeni Koucheryavy, Researcher Sergey Andreev. Growing demand for bandwidth dictates the use of smaller wireless cells, which results in increased inter-cell interference. In most contemporary cellular systems, the clients at the cell edge typically have the worst chance of successful uplink transmission due to interference from the neighboring cells using the same frequency. Cooperative communications are believed to be a promising technique to enhance the performance of cell-edge users by allowing them to exploit other users as relay nodes and thus improve their throughput by reducing the number of retransmissions. This thesis presents in-depth system-level evaluation of client relay technique in stateof-the-art wireless cellular networks (IEEE 802.16, LTE release 10). Several important scenarios are considered, including opportunistic client relay behavior and various network layouts. It is demonstrated that client cooperation may considerably improve system performance in terms of cell-edge user performance for the cost of some increase in energy consumption of cell-center user.
Two-Stages Bidding Strategies for Residential Microgrids Based Peer-to-Peer Energy Trading

With the promoting of residential Microgrids and transactive energy system, peer-to-peer (P2P) energy transactive mechanism among small household entities have emerged, which allows residents to actively trade energy with their neighbors has appeared in the residential Microgrid. In order to ensure the success of this trading mode, designing an effective bidding strategy in the P2P energy trading has been a hot topic in recent studies. However, in current studies, limitation still exsited such as lack of flexibility and unfair constraints on trading. To solve these problems, this paper proposes a two-stage bidding strategy in the residential Microgrid. In this mechanism, the equilibrim among fair competition in market, economic benefits in participants, and self-sufficiency in Mircogird is achieved. Besides, aiming to help residents make better decisions about their through bidding process, a trading price predictor and a tool for risk analysis, “Value at Risk” (VaR) are also offered in this process. Moreover, case studies with multiple households involved in a residential Microgrid verifed the effectiveness of the proposed method.
Multiquark Hadrons. I. Phenomenology of Q Q Mesons*

The spectra and dominant decay couplings of Q'Q' mesons are presented as calculated in the quark-bag model. Certain known 0+ mesons [a(700), S~,S,K] are assigned to the lightest cryptoexotic Q Q nonet. The usual quark-model 0+ nonet (QQ L = 1) must lie higher in mass. All other Q'Q' mesons are predicted to be broad, heavy, and usually inelastic in formation processes. Other Q Q states which may be experimentally prominent are discussed.
Dielectric Properties of (Mg(1-x)Cox)2SnO4 for Application in Dielectric Resonator Temperature Sensor

The microwave dielectric properties of (Mg1-xCox)2SnO4 were investigated by X-ray diffraction (XRD) patterns, Rietveld refinement, Raman spectroscopy, and microstructural observation. The ceramic was prepared using the conventional solid-state reaction method. (Mg<inf>0.95</inf>Co<inf>0.05</inf>)<inf>2</inf>SnO<inf>4</inf> ceramic that was sintered at 1550 °C for 4 h had a dielectric constant ( ) of 8.3, a quality factor (ε<inf>r</inf>) of 8.3, a quality factor (Q×f) of 120,200 GHz (at 17.6 GHz), and a temperature coefficient of resonant frequency (τ<inf>f</inf>) of -63 ppm/°C. The development process and test results of dielectric resonator antenna temperature sensor composed of (Mg<inf>0.95</inf>Co<inf>0.05</inf>)<inf>2</inf>SnO<inf>4</inf>ceramics were recorded. The resonant frequency and 3 dB bandwidth measured at room temperature were 17.566 GHz and 17.0 MHz, respectively. The sensitivity of -1.1 MHz/°C was successfully achieved.
DEFICIENCIA ANDROGÉNICA Y SÍNDROMES DE OJO SECO ANDROGEN DEFICIENCY & DRY EYE SYNDROMES

Acknowledgments: Research cited in this editorial was supported in part by grants from United States National Eye Institute [NIH grants EY05612 & 12 23], Allergan [USA & Japan], the German Research Society DFG, the Sjogren’s Syndrome Foundation, the Massachusetts Lion’s Research Fund, the Joint Clinical Research Center of the Schepens Eye Research Institute and the Massachusetts Eye & Ear Infirmary, and the General Clinica l Research Center at the University of Chicago Medical Center Foundation). EDITORIAL
The universal cover of 3-manifolds built from injective handlebodies is $\mathbb R^3$

This paper gives a proof that the universal cover of a closed 3-manifold built from three $\pi_1$-injective handlebodies is homeomorphic to $\mathbb R^3$. This construction is an extension to handlebodies of the conditions for gluing of three solid tori to produce non-Haken Seifert fibered manifolds with infinite fundamental group. This class of manifolds has been shown to contain non-Haken non-Seifert fibered manifolds.
FAUT-IL ENCORE FAIRE DES PHARYNGOTOMIES DANS LE SYNDROME D'APNEES DU SOMMEIL ?

e syndrome d’apnées au cours du sommeil est une entité pathologique bien connue, dont le traitement fait l’objet de nombreuses discussions. L’uvulo-palato-pharyngoplastie (UPP) est l’un des traitements du syndrome d’apnées au cours du sommeil (SAS). Depuis les travaux de Fujita et coll. , en 1981 (1), elle a été largement utilisée, avec des échecs et des succès. Il paraît intéressant, avec quelques années de recul, de préciser la place de l’UPP, ou pharyngotomie, dans le traitement du syndrome d’apnées au cours du sommeil. Le SAS est évoqué chez un patient dont l’interrogatoire bien conduit trouve un ronflement avec un mauvais sommeil, des pauses respiratoires décrites par l’épouse, mais surtout des symptômes diurnes qui invalident la vie du patient, avec une somnolence diurne (qui peut être quantifiée par l’échelle d’Epworth), une asthénie matinale et des céphalées. Bien d’autres éléments sont à rechercher, à savoir l’endormissement devant la télévision, l’impossibilité d’effectuer de longs trajets en automobile, ces différents paramètres recoupant les critères des échelles objectives. La certitude diagnostique est obtenue uniquement par l’enregistrement polysomnographique du sommeil. On peut ainsi décrire l’existence d’un SAS après avoir constaté un index d’apnées/hypopnées (IAH) horaire supérieur à 10. Cet enregistrement permettra aussi de rechercher l’existence d’une désaturation en oxygène nocturne, et analysera la structure du sommeil. Depuis les travaux de He et coll. , il est établi que la morbidité et la mortalité liées au syndrome d’apnées du sommeil (problèmes cardiovasculaires, neurologiques, troubles de la vigilance) s’observent lorsque l’IAH est supérieur à 20 (2).
PREFRONTAL CORTEX AND ACTION SEQUENCES: A REVIEW ON NEURAL COMPUTATIONAL MODELS

The prefrontal cortex (PFC) can be considered the central executive of cognitive control, responsible for the flexibility of human behavior. By a switchingmechanism PFC can update rules and goals representations stored in working memory, so as to performance novel task and accomplish complex routines. PFC functional organization and relation with specific subcortical areas give an account of representations active mantainance that allows to achieve a goal through a series of sub-goals. On the basis of the most recent studies, we present a rieview of the theories concerning PFC role and neural computational models. The paper incudes a focus section on models developed to study the role of PFC in action-sequences learning and performing.
Le rôle modérateur de la complexité du traitement des messages sur les effets de la répétition publicitaire

Cette étude suggère que l'effet, sur l'évaluation de la marque, de l'exposition répétée à la publicité est modéré par la complexité du traitement de l'information véhiculée par le message publicitaire. Elle montre que l'exposition croissante à la publicité favorise l'efficacité du message quand celui-ci est complexe, augmente puis réduit cette efficacité quand le message est modérément complexe, et réduit puis augmente cette efficacité quand le message est simple. Ces résultats tendent à prouver que l'efficacité des messages publicitaires est affectée par le temps de traitement de l'information et le temps consacré à cette tâche.
Emotional Focus and Source Monitoring

Misattributions about the origin of mental experience underlie most memory distortions and the role that emotion plays in such source monitoring errors is a critical theoretical and practical issue. Three experiments explored the impact of the direction and target of listeners’ emotional focus on their subsequent ability to identify the origin of memories for statements they had heard. Participants heard an audio tape (Experiment 1) or watched a video (Experiments 2 and 3) of two people making various statements (e.g.,Halloween is becoming a dangerous holiday). Participants were given tasks that focused them either on how they felt about what was being said or on how they thought the speakers felt. Self-focus resulted in equal or better recognition for the content of the statements than did Other-focus, but poorer identification of the source of the statements (Experiments 1–3). However, the deficit of Self-focus relative to Other-focus was eliminated when participants focused on how they felt about the speakers rather than on how they felt about what was being said (Experiment 3). We suggest that whether emotional focus is likely to produce confusions among external sources of memories depends on whether it reduces the processing that binds content with the kinds of perceptual, contextual, and semantic features of external events that are important cues for source.
A Low-Cost Antenna-in-Package Solution for 77GHz Automotive Radar Applications

This work proposes a low-cost Antenna in package (AiP) solution implemented on Advanced single sided substrates (aS3 package) for 77-GHz automotive radar applications. The impact of fabrication tolerances is also studied in this work. This work demonstrates firstly the 77-GHz losses of the transition from chip to package among flip-chip ball grid array (FCBGA) package, flip chip chip scale (FCCSP) package, Fan out wafer level chip scale package (Fan-out WLP), and aS3 package. Although Fan-out WLP can minimizes 77-GHz losses of transition from chip to package plus package to PCB, low-cost AiP solutions are very important for 77-GHz automotive radar applications. The proposed AiP solution on aS3 package has low losses of transition from chip to package, and the performance of designed antenna on aS3 package meets the requirements of 77-GHz automotive radar systems. Finally, this work also demonstrates the impact of fabrication inaccuracies on the bandwidth and radiation pattern of AiP on aS3 package. This work provides a cost-effective AiP approach for 77-GHz automotive radar systems.
An Energy-Efficient and Deadline-Aware Task Offloading Strategy Based on Channel Constraint for Mobile Cloud Workflows

Energy efficiency is a fundamental problem due to the fact that numerous tasks are running on mobile devices with limited resources. Mobile cloud computing (MCC) technology can offload computation-intensive tasks from mobile devices onto powerful cloud servers, which can significantly reduce the energy consumption of mobile devices and thus enhance their capabilities. In MCC, mobile devices transmit data through the wireless channel. However, since the state of the channel is dynamic, offloading at a low transmission rate will result in the serious waste of time and energy, which further degrades the quality of service (QoS). To address this problem, this paper proposes an energy-efficient and deadline-aware task offloading strategy based on the channel constraint, with the goal of minimizing the energy consumption of mobile devices while satisfying the deadlines constraints of mobile cloud workflows. Specifically, we first formulate a task offloading decision model that combines the channel state with task attributes such as the workload and the size of the data transmission to determine whether the task needs to be offloaded or not. Afterward, we apply it to a new adaptive inertia weight-based particle swarm optimization (NAIWPSO) algorithm to create our channel constraint-based strategy (CC-NAIWPSO), which can obtain a near-optimal offloading plan that can consume less energy while meeting the deadlines. The experimental results show that our proposed task offloading strategy can outperform other strategies with respect to the energy consumption of mobile devices, the execution time of mobile cloud workflows, and the running time of algorithms.
[Evaluation of mental status of children with malabsorption syndrome after long-term treatment with gluten-free diet (preliminary report)].

The author examined 41 children, suffering from celiac disease with psychiatric methods and EEG. The children, aged 7-17 y. , were many years on gluten-free diets. Various psychiatric symptoms were found in 48.8%, and EEG abnormalities in 70.7%. Only 9 children (21.9%) were free from any psychiatric disorders and EEG abnormalities.
Artificial Bandwidth Extension Using H∞ Optimization and Speech Production Model

This work presents a new method for artificial bandwidth extension (ABE) in narrowband telephonic communication. In this regard, we use signal model and H∞ optimization to obtain a synthesis filter for representing the wideband information of a signal. We need to estimate the high-band information in narrowband communication. Hence, we construct a high-band filter which retains the high-band information of the synthesis filter. Signal models may not be the same for different speech signals because of their non-stationary (time-varying) behavior. Hence, a short time processing (framing) is applied to speech signals for converting them into the stationary frames. Signal models of stationary frames may be different. As a result, their high-band filters will vary. So, a Gaussian mixture modelling (GMM) codebook approach is used to store the high-band filters information along with their narrowband information (narrowband feature). This approach is also used to estimate the high-band filter information for a given narrowband feature of the signal. Performance analysis is done for the two types of narrowband information representations.
Oscillation criteria for a certain class of second order Emden-Fowler dynamic equations.

By means of Riccati transformation techniques we establish some oscillation criteria for the second order Emden–Fowler dynamic equation on a time scale. Such equations contain the classical Emden–Fowler equation as well as their discrete counterparts. The classical oscillation results of Atkinson (in the superlinear case) and Belohorec (in the sublinear case) are extended in this paper to Emden–Fowler dynamic equations on any time scale.
Evaluation of a Unique Transient Hardened Transformer Designed to Withstand Primary Switching Transients: Simulation, Lab Tests and Analysis

Many modern electrical distribution systems, such as those used in data centers, demand high power densities, small electrical footprints, high efficiency transformers, redundant systems and frequent testing requiring switching at primary voltages. These various parameters that ensure the highest reliability and availability to mission-critical loads also place the facility in the highest risk category for distribution transformer failures due to primary switching transients. Over the last decade, this phenomenon has been attributed to a significant number of failures of certain types of transformers involving primary circuit breaker switching in data centers and other facilities exhibiting similar characteristics. Although the RC snubber has been proven to safely mitigate the transient overvoltage imposed on the primary winding of the transformer, manufacturers have continued to look for other solutions to the primary switching transients problem resulting in an alternative solution: a unique transient hardened transformer designed to withstand switching transients. The authors conducted an evaluation to prove analytically, through a combination of simulations and field tests, that the transient hardened transformer design will withstand switching transients without the need for transient mitigation using RC snubbers, relying only on conventionally applied surge arresters. This paper focuses specifically on data center transformers, however, the lessons learned here may be applied to numerous applications.
Efficient Iterative Solution of the Three-Dimensional Helmholtz Equation

We examine preconditioners for the discrete indefinite Helmholtz equation on a three-dimensional box-shaped domain with Sommerfeld-like boundary conditions. The preconditioners are of two types. The first is derived by discretization of a related continuous operator that differs from the original only in its boundary conditions. The second is derived by a block Toeplitz approximation to the descretized problem. The resulting preconditioning matrices allow the use of fast transform methods and differ from the discrete Helmholtz operator by an operator of low rank. We present experimental results demonstrating that when these methods are combined with Krylov subspace iteration, convergence rates depend only mildly on both the wave number and discretization mesh size. In addition, the methods display high efficiencies in an implementation on an IBM SP-2 parallel computer.
Poster Abstract: Unsupervised Anomaly Detection via Generative Adversarial Networks

Unsupervised anomaly detection is a fundamental problem in various research areas and application domains, namely the discrimination of abnormal samples from normal samples where training data are only composed of one class (normal) while testing data contains both among which the majority are normal samples. However, previous works can not effectively fit the distribution of high dimensional data and suffers from low AUC scores which measures the classification performance of imbalanced data. To solve these problems, we propose an unsupervised anomaly detection model based on GAN, i.e., UAD-GAN. Specifically, we adopt transfer learning to extract visual features with pre-trained Inception-v3 model and use the discriminator to detect anomalies. UAD-GAN can fit the data distribution and detect anomalies efficiently. Extensive experiments show that UAD-GAN achieves state-of-the-art performance compared to other approaches.
The Fine Plane Range Estimation From Point Cloud

This paper deals with the fine plane estimation. For a plane detection the level connected component labeling algorithm is used. The precise plane position is determined by the plane’s points histogram in the scanning dimension. Up till now, the final plane’s range has been selected manually by a parameter. Plane presence in an input point cloud represents the higher points’ concentration in the scanning dimension, higher than average value. The concentration decreases on both sides from a local maximum value. This paper presents the algorithm of the elbows’ position estimation for the optimal plane’s points range expression. The experimental part shows practical results of several examples and gives recommendations for parameters setting.
Calibration of Vision-Based Measurement of Pain Intensity With Multiple Expert Observers

Facial expression is an important component of the pain measurement process, which can be utilized by clinicians in patients with impaired communicative or cognitive abilities. However, given the complex nature of the pain and the absence of a standard reference, accurate measurement of pain in hospital settings is a difficult practice. In this paper, we present a vision-based measurement system aimed at automatically measuring the pain intensity values through the analysis of the facial expression, based on deep-learning strategies. For the scope of providing a metrological characterization of the system, we designed a benchmark for the estimation of the measurement precision via multiexpert judgments. As a major contribution of this paper, we investigated the interobserver and intraobserver variability as sources of uncertainty at the calibration level in order to provide a robust pain estimation via an automatic framework. Reproducibility and standard reference uncertainty (due to interobserver and intraobserver variability, respectively) have been estimated, modeled, and propagated through the proposed platform using the Guide to the expression of Uncertainty in Measurement (GUM)-compliant procedures. Numerical results, provided in terms of average values and confidence intervals of the accuracy of classification, indicate that such a system can facilitate decision-making in healthcare. Moreover, the proposed benchmark offers new hints to incorporate, rationally, subjective expert judgments within automatic measurement systems.