Miracle-dz/UniFAR-FTUs huggingface dataset:
Preferential Inspection of Recent Real-World Events Over Future Events: Evidence from Eye Tracking during Spoken Sentence Comprehension

Eye-tracking findings suggest people prefer to ground their spoken language comprehension by focusing on recently seen events more than anticipating future events: When the verb in NP1-VERB-ADV-NP2 sentences was referentially ambiguous between a recently depicted and an equally plausible future clipart action, listeners fixated the target of the recent action more often at the verb than the object that hadn’t yet been acted upon. We examined whether this inspection preference generalizes to real-world events, and whether it is (vs. isn’t) modulated by how often people see recent and future events acted out. In a first eye-tracking study, the experimenter performed an action (e.g., sugaring pancakes), and then a spoken sentence either referred to that action or to an equally plausible future action (e.g., sugaring strawberries). At the verb, people more often inspected the pancakes (the recent target) than the strawberries (the future target), thus replicating the recent-event preference with these real-world actions. Adverb tense, indicating a future versus past event, had no effect on participants’ visual attention. In a second study we increased the frequency of future actions such that participants saw 50/50 future and recent actions. During the verb people mostly inspected the recent action target, but subsequently they began to rely on tense, and anticipated the future target more often for future than past tense adverbs. A corpus study showed that the verbs and adverbs indicating past versus future actions were equally frequent, suggesting long-term frequency biases did not cause the recent-event preference. Thus, (a) recent real-world actions can rapidly influence comprehension (as indexed by eye gaze to objects), and (b) people prefer to first inspect a recent action target (vs. an object that will soon be acted upon), even when past and future actions occur with equal frequency. A simple frequency-of-experience account cannot accommodate these findings.
More theorems about scale-sensitive dimensions and learning

We present a new general-purpose algorithm for learning classes of [0; 1]-valued functions in a generalization of the prediction model, and prove a general upper bound on the expected absolute error of this algorithm in terms of a scale-sensitive generalization of the Vapnik dimension proposed by Alon, Ben-David, Cesa-Bianchi and Haussler. We give lower bounds implying that our upper bounds cannot be improved by more than a constant in general. We apply this result, together with techniques due to Haussler, to obtain new upper bounds on packing numbers in terms of this scale-sensitive notion of dimension. Using a different technique, we obtain new bounds on packing numbers in terms of Kearns and Schapire’s fat-shattering function. We show how to apply both packing bounds to obtain improved general bounds on the sample complexity of agnostic learning. For each > 0, we establish weaker sufficient and stronger necessary conditions for a class of [0; 1]-valued functions to be agnostically learnable to within , to be an uniform Glivenko-Cantelli class, and to be agnostically learnable to within by an algorithm using only hypotheses from the class.
Laser-Capture Microdissection: Refining Estimates of the Quantity and Distribution of Latent Herpes Simplex Virus 1 and Varicella-Zoster Virus DNA in Human Trigeminal Ganglia at the Single-Cell Level

ABSTRACT There remains uncertainty and some controversy about the percentages and types of cells in human sensory nerve ganglia that harbor latent herpes simplex virus 1 (HSV-1) and varicella-zoster virus (VZV) DNA. We developed and validated laser-capture microdissection and real-time PCR (LCM/PCR) assays for the presence and copy numbers of HSV-1 gG and VZV gene 62 sequences in single cells recovered from sections of human trigeminal ganglia (TG) obtained at autopsy. Among 970 individual sensory neurons from five subjects, 2.0 to 10.5% were positive for HSV-1 DNA, with a median of 11.3 copies/positive cell, compared with 0.2 to 1.5% of neurons found to be positive by in situ hybridization (ISH) for HSV-1 latency-associated transcripts (LAT), the classical surrogate marker for HSV latency. This indicates a more pervasive latent HSV-1 infection of human TG neurons than originally thought. Combined ISH/LCM/PCR assays revealed that the majority of the latently infected neurons do not accumulate LAT to detectable levels. We detected VZV DNA in 1.0 to 6.9% of individual neurons from 10 subjects. Of the total 1,722 neurons tested, 4.1% were VZV DNA positive, with a median of 6.9 viral genomes/positive cell. After removal by LCM of all visible neurons on a slide, all surrounding nonneuronal cells were harvested and assayed: 21 copies of HSV-1 DNA were detected in ∼5,200 nonneuronal cells, while nine VZV genomes were detected in ∼14,200 nonneuronal cells. These data indicate that both HSV-1 and VZV DNAs persist in human TG primarily, if not exclusively, in a moderate percentage of neuronal cells.
Multilevel auditory displays for mobile eyes-free location-based interaction

This paper explores the use of multilevel auditory displays to enable eyes-free mobile interaction with location-based information in a conceptual art exhibition space. Multilevel auditory displays enable user interaction with concentrated areas of information. However, it is necessary to consider how to present the auditory streams without overloading the user. We present an initial study in which a top-level exocentric sonification layer was used to advertise information present in a gallery-like space. Then, in a secondary interactive layer, three different conditions were evaluated that varied in the presentation (sequential versus simultaneous) and spatialisation (non-spatialised versus egocentric spatialisation) of multiple auditory sources. Results show that 1) participants spent significantly more time interacting with spatialised displays, 2) there was no evidence that a switch from an exocentric to an egocentric display increased workload or lowered satisfaction, and 3) there was no evidence that simultaneous presentation of spatialised Earcons in the secondary display increased workload.
A Task-Swap Negotiation Protocol Based on the Contract Net Paradigm

In this paper we propose a market-like negotiation protocol which extends the wellknown Contract Net Protocol to cope with domains where task swap is the only possible type of contract. The agents we consider are heterogeneous and self-interested. The absence of an explicit support for utility transfer determines interesting implications on efficiency and stability; in particular, we propose different design alternatives induced by different compositions of the announcement and the bid, and discusses the strategies supported. Task swapping is more feasible than task selling for many realistic applications; symbolic path planning in autonomous robotic agents is the application on which we focus the description of our approach.
Universal organization of resting brain activity at the thermodynamic critical point

Thermodynamic criticality describes emergent phenomena in a wide variety of complex systems. In the mammalian cortex, one type of complex dynamics that spontaneously emerges from neuronal interactions has been characterized as neuronal avalanches. Several aspects of neuronal avalanches such as their size and life time distributions are described by power laws with unique exponents, indicating an underlying critical branching process that governs avalanche formation. Here, we show that neuronal avalanches also reflect an organization of brain dynamics close to a thermodynamic critical point. We recorded spontaneous cortical activity in monkeys and humans at rest using high-density intracranial microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter equivalent to thermodynamic temperature, we observed typical critical behavior in cortical activities near the actual physiological condition, including the phase transition of an order parameter, as well as the divergence of susceptibility and specific heat. Finite-size scaling of these quantities allowed us to derive robust critical exponents highly consistent across monkey and humans that uncover a distinct, yet universal organization of brain dynamics. Our results demonstrate that normal brain dynamics at rest resides near or at criticality, which maximizes several aspects of information processing such as input sensitivity and dynamic range.
Discriminative Optimization of Local Features for Face Recognition

The task of face recognition has been studied in the past few decades, which has led to introducing several methods. However, recently, the use of pictorial structures in object recognition has shown to be powerful. Face, also treated as a structured object, has parts (e.g. eyes, nose, and mouth) which are not dramatically deformed from one instance to another. This enables it to work fairly good on faces as well. Based on this fact, state-of-the -art face recognition methods detect facial features using pictorial structure approach and then apply some local feature descriptors in order to discriminatively train the recognition model. In this work, we propose an approach to optimize the local features at the detected facial points in terms of the patch size, constellation of cells, location, and normalization factors, using SVM Cross Validation Accuracy as the objective function and Gradient Ascent as searching method. We use HoG descriptor but the approach can be used for any other local descriptors. We test our approach on the task of face identification applying on a dataset of celebrity images which we downloaded automatically using Google search engine. We also report results of Face Verification task on the recently released standard dataset called Labelled Faces in the Wild (a.k.a. LFW).
Autophagy is required for G1/G0 quiescence in response to nitrogen starvation in Saccharomyces cerevisiae

In response to starvation, cells undergo increased levels of autophagy and cell cycle arrest but the role of autophagy in starvation-induced cell cycle arrest is not fully understood. Here we show that autophagy genes regulate cell cycle arrest in the budding yeast Saccharomyces cerevisiae during nitrogen starvation. While exponentially growing wild-type yeasts preferentially arrest in G1/G0 in response to starvation, yeasts carrying null mutations in autophagy genes show a significantly higher percentage of cells in G2/M. In these autophagy-deficient yeast strains, starvation elicits physiological properties associated with quiescence, such as Snf1 activation, glycogen and trehalose accumulation as well as heat-shock resistance. However, while nutrient-starved wild-type yeasts finish the G2/M transition and arrest in G1/G0, autophagy-deficient yeasts arrest in telophase. Our results suggest that autophagy is crucial for mitotic exit during starvation and appropriate entry into a G1/G0 quiescent state.
Induced Pluripotent Stem Cell Therapies for Cervical Spinal Cord Injury

Cervical-level injuries account for the majority of presented spinal cord injuries (SCIs) to date. Despite the increase in survival rates due to emergency medicine improvements, overall quality of life remains poor, with patients facing variable deficits in respiratory and motor function. Therapies aiming to ameliorate symptoms and restore function, even partially, are urgently needed. Current therapeutic avenues in SCI seek to increase regenerative capacities through trophic and immunomodulatory factors, provide scaffolding to bridge the lesion site and promote regeneration of native axons, and to replace SCI-lost neurons and glia via intraspinal transplantation. Induced pluripotent stem cells (iPSCs) are a clinically viable means to accomplish this; they have no major ethical barriers, sources can be patient-matched and collected using non-invasive methods. In addition, the patient’s own cells can be used to establish a starter population capable of producing multiple cell types. To date, there is only a limited pool of research examining iPSC-derived transplants in SCI—even less research that is specific to cervical injury. The purpose of the review herein is to explore both preclinical and clinical recent advances in iPSC therapies with a detailed focus on cervical spinal cord injury.
SYSTOLIC AND DIASTOLIC BLOOD PRESSURE ESTIMATION, WITH SPECIAL REFERENCE TO THE AUDITORY METHOD *

IT is being gradually recognized that systolic pressure estimation, tllough valuable, gives very insufficienit infornmation regarding circulatory conditions in hlealtlh and disease, and that a knlowledge of the range of pressure clhange during the whole cardiac cycle woLld be of great inmportance in various ways. The auditory imiethod, eimployed in a certain way, offers distinct advantages in the estimation of systolic pressure, but its greatest importance lies in its relation to the estimation of diastclic pressure.
A Model of Personalized Collaborative Computer Support Ubiquitous Learning Environment

Searching for knowledge is an essential problem that learners face while learning. In a ubiquitous learning environment, it is difficult for a learner to find the right knowledge in time even if the source of this knowledge is very near to his physical location. Therefore, this paper presents a personalized collaborative ubiquitous learning environment in order to support the learner while doing a task. It allows the learners to share knowledge, interact, collaborate, and exchange individual experiences. This environment is called PERKAM. It utilizes the ubiquitous technologies to recommend the educational materials and the peer helpers according to the learnerpsilas current task and location. This paper focuses on the user model and the recommendation methodology.
An application of genetic algorithm for auto-body panel die-design case library based on grid

The use of case library techniques to direct new designs for auto industry is becoming increasing widespread. In this paper, we use a genetic algorithm to realize a quick match with the best case, which can satisfy the intelligence request of the case library. Experiment results show that the proposed algorithm can greatly increase the efficiency of searching for the best case. Additionally, this paper presents a novel framework of auto-body panel die-design case library based on grid. By using grid technology, it has solved the principal problems existing in current case libraries. Consequently, we anticipate that this work will have a broad application in the making of auto-body panel dies.
Clumpy diffuse X-ray emission from the spiral-rich compact galaxy group HCG 16

We carefully reanalyze the ROSAT PSPC X-ray spectro-photometric observations of HCG 16 (Arp 318), and compare them to optical and radio data. Its X-ray morphology resembles its morphology at 20 cm, seen by the NVSS. In par- ticular, we detect diffuse emission in eight regions filling half of the 200 h 1 50 kpc (8: 7) radius circle around the optical cen- ter of the group: one region encompassing galaxie sa&b , two regions surrounding the group galaxie sc&d , aclumpy re- gion roughly 140 h 1 50 kpc from the group galaxies, which may be gas ejected from one of the galaxies, plus regions respec- tively associated with a background radio-source, a probable background radio-source, a foreground star and a background group or cluster. The bolometric X-ray luminosity of the diffuse emission, excluding the regions associated with radio galaxies, is L bol =2 :3 10 41 h 2 50 ergs 1 , i.e., half of the luminosity found by Ponman et al. (1996). The region that is offset from the galaxies contributes half of the diffuse X-ray luminosity of the group. The diffuse emission is cool ( T< 0:55keV with 90% confidence with a best fit T =0 :27keV). At these low tempera- tures, the correction for photoelectric absorption in the estimate of bolometric luminosity is a factor 3.5 and varies rapidly with temperature, hence an uncertain bolometric luminosity. The clumpy distribution of hot diffuse gas in HCG 16 is il- lustrated by the low mean X-ray surface brightness and hot gas density of the regions of undetected emission within 8 0 (at most 1/4 and 1/6 of those of the detected gas, assuming both have same temperature, metallicity and clumpiness). The irregular X-ray morphology of the diffuse emission rules out a (nearly) virialized nature for HCG 16, unless intergalactic gas had suf- ficiently high specific entropy to be unable to collapse with the group. In any event, the clumpy gas distribution, and high lu- minosity given the low temperature suggest that most of the diffuse gas originates from galaxies, either through tidal strip- ping or through galactic winds driven by supernova remnants. Therefore, no spiral-only HCGs are known with regular diffuse emission tracing a gravitational potential. Our results highlight the need for a careful 2D spatial anal- ysis and multi-wavelength study of the diffuse X-ray emission from groups, suggesting that other compact groups could be significantly contaminated by superimposed X-ray sources.
An Efficient Sparse Optimization Algorithm for Weighted $\ell _{0}$ Shearlet-Based Method for Image Deblurring

Sparsity is one of the key concepts that allows the signal recovery at a significantly lower subsample rate than required by the Nyquist-Shannon sampling theorem. By using a multistate transform, such as wavelets and shearlets system, the sparse representation of signals can be obtained. To further exploit the sparsity of the reconstructed signal, a generalized gradient regularizer is introduced to the proposed model. Motivated by the idea of iterative support detection (ISD), an optimization algorithm framework for image deblurring is given. The algorithm aims to solve a reweighted $\ell _{0}$ -minimization problem in split Bregman framework, and the weights used for the next iteration are decided by an ISD process. The advantage of this process is that it forms an iterative-feedback mechanism, which improves the effectiveness for solution searching. A series of experiments are presented to demonstrate the availability of the proposed framework. Experimental results show that this method yields significant improvement in peak signal-to-noise ratio when compared to other counterparts. However, the numerical experiments also show that more computing time is required due to the utilization of the redundant multiscale system.
Hardness Behavior in A17075 Aged Alloys Modified with Ce/La Rare Earths

The plastic injection industry have been supported by the use of steel molds in the manufacturing of a wide range of products; however, lighter materials with excellent mechanical performance, and incomparable heat exchange capabilities, are promising mold materials for increasing the numbers in the manufacturing of products with high quality in a fraction of time [1]. This is the case of high-strength aluminum alloys, originally developed for aircraft applications. The use of the T6 grade Al7075 aluminum for the fabrication of molds, offers a multitude of advantages over those presented by steel. Improved and uniform heat dissipation, good machinability and lightness are attractive characteristics highly valuable in manufacturing processes [2].
RNA Editing and Its Molecular Mechanism in Plant Organelles

RNA editing by cytidine (C) to uridine (U) conversions is widespread in plant mitochondria and chloroplasts. In some plant taxa, “reverse” U-to-C editing also occurs. However, to date, no instance of RNA editing has yet been reported in green algae and the complex thalloid liverworts. RNA editing may have evolved in early land plants 450 million years ago. However, in some plant species, including the liverwort, Marchantia polymorpha, editing may have been lost during evolution. Most RNA editing events can restore the evolutionarily conserved amino acid residues in mRNAs or create translation start and stop codons. Therefore, RNA editing is an essential process to maintain genetic information at the RNA level. Individual RNA editing sites are recognized by plant-specific pentatricopeptide repeat (PPR) proteins that are encoded in the nuclear genome. These PPR proteins are characterized by repeat elements that bind specifically to RNA sequences upstream of target editing sites. In flowering plants, non-PPR proteins also participate in multiple RNA editing events as auxiliary factors. C-to-U editing can be explained by cytidine deamination. The proteins discovered to date are important factors for RNA editing but a bona fide RNA editing enzyme has yet to be identified.
Scaling-Up the Crowd: Micro-Task Pricing Schemes for Worker Retention and Latency Improvement

Retaining workers on micro-task crowdsourcing platforms is essential in order to guarantee the timely completion of batches of Human Intelligence Tasks (HITs). Worker retention is also a necessary condition for the introduction of SLAs on crowdsourcing platforms. In this paper, we introduce novel pricing schemes aimed at improving the retention rate of workers working on long batches of similar tasks. We show how increasing or decreasing the monetary reward over time influences the number of tasks a worker is willing to complete in a batch, as well as how it influences the overall latency. We compare our new pricing schemes against traditional pricing methods (e.g., constant reward for all the HITs in a batch) and empirically show how certain schemes effectively function as an incentive for workers to keep working longer on a given batch of HITs. Our experimental results show that the best pricing scheme in terms of worker retention is based on punctual bonuses paid whenever the workers reach predefined milestones.
Modeling anti-collision protocols for RFID Systems with multiple access interference

Passive tags based on backscattered signals yield low energy consumption and enable a rich set of applications. In this paper, the performance of the dynamic framed ALOHA of the ISO/IEC 18000-6C standard is investigated. A Markov chain model of the protocol is developed by including the effects of the channel under different propagation scenarios. Depending on the air interface parameters and the fading components, it is shown that multiple access interference determines complex and unexpected effects on the system performance. An explicit analysis of the successful interrogation probability is obtained with respect to the number of tags, number of interrogation rounds and fading severity. It is shown that channel statistics may induce significant degradation, although a moderate spread of the fading can be beneficial especially for those contexts that include time-varying conditions.
Byzantine resistant reputation-based trust management

Cloud computing is very useful for improving distributed applications performance. However, it is difficult to manage risks related to trust when collaborating with unknown and potentially malicious peers. Besides, trust evaluation is the target of dishonest behaviors trying to disturb the control process. In this paper, reputation-based trust management models for cloud computing are proposed. These Peer-to-Peer (P2P) reputation models are based on the interaction between peers. Using evaluations and feedbacks, a central entity can estimate the trust of a given peer. Three approaches are proposed to estimate the trust: PerronTrust, CredTrust and CredTrust-trust. They are studied, simulated and compared between them and to two existing methods for trust under several attack scenarios. Our analysis clearly shows that the third approach CredTrust-trust combining the concepts of trust and credibility in an appropriate way is the most efficient to avoid malicious behaviors and to guide and advise future executions in the open cloud in term of selecting the dependable and reliable peers in cloud environment.