Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural time course of visually enhanced echo suppression.

Auditory spatial perception plays a critical role in day-to-day communication. For instance, listeners utilize acoustic spatial information to segregate individual talkers into distinct auditory "streams" to improve speech intelligibility. However, spatial localization is an exceedingly difficult task in everyday listening environments with numerous distracting echoes from nearby surfaces, such as walls. Listeners' brains overcome this unique challenge by relying on acoustic timing and, quite surprisingly, visual spatial information to suppress short-latency (1-10 ms) echoes through a process known as "the precedence effect" or "echo suppression. " In the present study, we employed electroencephalography (EEG) to investigate the neural time course of echo suppression both with and without the aid of coincident visual stimulation in human listeners. We find that echo suppression is a multistage process initialized during the auditory N1 (70-100 ms) and followed by space-specific suppression mechanisms from 150 to 250 ms. Additionally, we find a robust correlate of listeners' spatial perception (i.e., suppressing or not suppressing the echo) over central electrode sites from 300 to 500 ms. Contrary to our hypothesis, vision's powerful contribution to echo suppression occurs late in processing (250-400 ms), suggesting that vision contributes primarily during late sensory or decision making processes. Together, our findings support growing evidence that echo suppression is a slow, progressive mechanism modifiable by visual influences during late sensory and decision making stages. Furthermore, our findings suggest that audiovisual interactions are not limited to early, sensory-level modulations but extend well into late stages of cortical processing.
Clustering Based on Background Knowledge

Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results.
Radio interface design for ultra-low latency millimeter-wave communications in 5G Era

The projected growth of mobile data traffic requires the 5G wireless systems to support at least 1000 x larger area throughput than the existing 4G solutions. This requires ultra-dense local area networks combined with millimeter-wave communications to provide high spatial multiplexing gain and wide bandwidths for multi-gigabit peak data rates. In this paper, we extend our 5GETLA reference design for 5G small cell network radio interface in 3-10 GHz carrier frequencies towards millimeter-wave communications and discuss separate solutions for both line-of-sight and non-line-of-sight scenarios. The non-line-of-sight frame design achieves frame duration equal to 0.1 ms which is one hundredth of the LTE frame duration. The line-of-sight design is also considered as a good candidate especially for small-distance indoor wireless access or inband backhaul and is particularly optimized in terms of ultra-low latency with frame duration equal to 0.05 ms, achieving the strictest physical layer latency requirements set for 5G communications.
Using the Neandertal and Denisova Genetic Data to Understand the Common MAPT 17q21 Inversion in Modern Humans

Abstract The polymorphic inversion on 17q21, that includes the MAPT gene, represents a unique locus in the human genome characterized by a large region with strong linkage disequilibrium. Two distinct haplotypes, Hl and H2, exist in modern humans, and Hl has been unequivocally related to several neurodegenerative disorders. Recent data indicate that recurrent inversions of this genomic region have occurred through primate evolution, with the H2 haplotype being the ancestral state. Neandertals harbored the H1 haplotype; however, until now, no data were available for the Denisova hominin. Neandertals and Denisovans are sister groups that share a common ancestor with modern humans. We analyzed the MAPT sequence and assessed the differences between modern humans, Neandertals, Denisovans, and great apes. Our analysis indicated that the Denisova hominin carried the H1 haplotype, and the Neandertal and Denisova common ancestor probably shared the same subhaplotype (H1j). We also found 68 intronic variants within the MAPT gene, 23 exclusive to Denisova hominin, 6 limited to Neandertals, and 24 exclusive to present-day humans. Our results reinforce previous data; this suggests that the 17q21 inversion arose within the modern human lineage. The data also indicate that archaic hominins that coexisted in Eurasia probably shared the same MAPT subhaplotype, and this can be found in almost 2% of chromosomes from European ancestry.
Perceiving human motion variety

In order to simulate plausible groups or crowds of virtual characters, it is important to ensure that the individuals in a crowd do not look, move, behave or sound identical to each other. Such obvious 'cloning' can be disconcerting and reduce the engagement of the viewer with an animated movie, virtual environment or game. In this paper, we focus in particular on the problem of motion cloning, i. e. , where the motion from one person is used to animate more than one virtual character model. Using our database of motions captured from 83 actors (45M and 38F), we present an experimental framework for evaluating human motion, which allows both the static (e.g., skeletal structure) and dynamic aspects (e.g., walking style) of an animation to be controlled. This framework enables the creation of crowd scenarios using captured human motions, thereby generating simulations similar to those found in commercial games and movies, while allowing full control over the parameters that affect the perceived variety of the individual motions in a crowd. We use the framework to perform an experiment on the perception of characteristic walking motions in a crowd, and conclude that the minimum number of individual motions needed for a crowd to look varied could be as low as three. While the focus of this paper was on the dynamic aspects of animation, our framework is general enough to be used to explore a much wider range of factors that affect the perception of characteristic human motion.
Computer-aided diagnosis of Alzheimer's disease using support vector machines and classification trees

This paper presents a computer-aided diagnosis technique for improving the accuracy of early diagnosis of Alzheimer-type dementia. The proposed methodology is based on the selection of voxels which present Welch's t-test between both classes, normal and Alzheimer images, greater than a given threshold. The mean and standard deviation of intensity values are calculated for selected voxels. They are chosen as feature vectors for two different classifiers: support vector machines with linear kernel and classification trees. The proposed methodology reaches greater than 95% accuracy in the classification task.
Misconceptions about traumatic brain injury among educators: has anything changed over the last 20 years?

Abstract Purpose: To examine educational professionals’ knowledge and understanding of childhood brain injury. Materials and methods: Educational professionals from all schools in the state of Victoria, Australia, were invited to participate in an online cross-sectional survey consisting of 20 questions assessing knowledge of concussion and 30 questions examining knowledge of traumatic brain injury (n = 364). Results: On average, participants correctly answered 16/20 (80%) questions about concussion and 24.3/30 (81%) about traumatic brain injuries. Participants who had previously taught a child with a brain injury demonstrated greater knowledge of traumatic brain injury, but not concussion, than those who had not. There were no differences in knowledge of concussion or brain injury between participants who had and had not attended a briefing session about concussion. Misconceptions displayed by educators predominantly related to the ongoing effects and impact of both concussion and traumatic brain injury, including effects on emotion, cognition, and social behaviour, as well as the increased risk of multiple injuries following an initial brain injury. When participants’ responses to the brain injury questionnaire were compared with results reported by Farmer and Johnson-Gerard in 1997 using the same questionnaire, many of the same misconceptions were evident in the two samples of educational professionals. Conclusions: Although educators demonstrated reasonable understanding of concussion and brain injury, some gaps in knowledge were apparent. Providing educational professionals with further training and professional development regarding childhood brain injuries would enhance their preparedness to manage students with these injuries in the school environment. Implications for Rehabilitation Mild to moderate brain injuries are relatively common among school-aged children, and educators may be required to manage and support students with these injuries in the school environment. This study shows that educators generally have a good understanding of the symptoms and immediate effects of brain injuries, but have gaps in knowledge regarding the potential socioemotional, behavioural, and cognitive difficulties and vulnerabilities to multiple injuries that may be present during recovery. Pre-service training and professional development may increase educators’ understanding and capacity to accommodate the needs of students with brain injuries.
The development and validation of two prediction models to identify employees at risk of high sickness absence.

BACKGROUND Sickness absence (SA) is a public health risk marker for morbidity and mortality. The aim of this study was to develop and validate prediction models to identify employees at risk of high SA. METHODS Two prediction models were developed using self-rated health (SRH) and prior SA as predictors. SRH was measured by the categories excellent, good, fair and poor in a convenience sample of 535 hospital employees. Prior SA was retrieved from the employer's register. The predictive performance of the models was assessed by logistic regression analysis with high (≥ 90 th percentile) vs. non-high (<90th percentile) SA days and SA episodes as outcome variables and by using bootstrapping techniques to validate the models. RESULTS The overall performance as reflected in the Nagelkerke's pseudo R(2) was 11.7% for the model identifying employees with high SA days and 31.8% for the model identifying employees with high SA episodes. The discriminative ability, represented by the area (AUC) under the receiver operating characteristic (ROC), was 0.729 (95% CI 0.667-0.809) for the model identifying employees with high SA days and 0.831 (95% CI 0.784-0.877) for the model identifying employees with high SA episodes. The Hosmer-Lemeshow test showed acceptable calibration for both models. CONCLUSIONS The prediction models identified employees at risk of high SA, but need further external validation in other settings and working populations before applying them in public and occupational health research and care.
The Role of BEACH Proteins in Dictyostelium

The BEACH family of proteins is a novel group of proteins with diverse roles in eukaryotic cells. The identifying feature of these proteins is the BEACH domain named after the founding members of this family, the mouse beige and the human Chediak–Higashi syndrome proteins. Although all BEACH proteins share a similar structural organization, they appear to have very distinct cellular roles, ranging from lysosomal traffic to apoptosis and cytokinesis. Very little is currently known about the function of most of these proteins, few binding‐partner proteins have been identified, and no molecular mechanism for any of these proteins has been discovered. Thus, it is important to establish good model systems for the study of these novel proteins. Dictyostelium contains six BEACH proteins that can be classified into four subclasses. Two of them, LvsA and LvsB, have clearly distinct roles in the cell. LvsA is localized on the contractile vacuole membrane and is essential for cytokinesis and osmoregulation. LvsB is most similar in sequence to the mammalian beige/Chediak–Higashi syndrome proteins and shares with them a common function in lysosomal trafficking. Structural and functional analysis of these proteins in Dictyostelium will help elucidate the function of this enigmatic novel family of proteins.
The key stability determinants for low-order interval polynomials

This paper aims to derive key stability determinants from Kahritonov polynomials and Routh-Hurwitz criterion. One analyzes Kahritonov's four determinants using only orthogonal aspect of experimental design first. The key stability determinants then are derived for low-order system by both orthogonal property and Routh-Hurwitz criterion. The reasons why there is no available key rules for high order system are analyzed as well. Examples are described in detail to demonstrate key determinants and corresponding inequalities. They are proved to be efficient and useful to save procedure and time of judging system stability for specified characteristic equation with interval polynomials.
An Automatic Corneal Subbasal Nerve Registration System Using FFT and Phase Correlation Techniques for an Accurate DPN Diagnosis

Confocal microscopy is employed as a fast and non-invasive way to capture a sequence of images from different layers and membranes of the cornea. The captured images are used to extract useful and helpful clinical information for early diagnosis of corneal diseases such as, Diabetic Peripheral Neuropathy (DPN). In this paper, an automatic corneal subbasal nerve registration system is proposed. The main aim of the proposed system is to produce a new informative corneal image that contains structural and functional information. In addition a colour coded corneal image map is produced by overlaying a sequence of Cornea Confocal Microscopy (CCM) images that differ in their displacement, illumination, scaling, and rotation to each other. An automatic image registration method is proposed based on combining the advantages of Fast Fourier Transform (FFT) and phase correlation techniques. The proposed registration algorithm searches for the best common features between a number of sequenced CCM images in the frequency domain to produce the formative image map. In this generated image map, each colour represents the severity level of a specific clinical feature that can be used to give ophthalmologists a clear and precise representation of the extracted clinical features from each nerve in the image map. Moreover, successful implementation of the proposed system and the availability of the required datasets opens the door for other interesting ideas, for instance, it can be used to give ophthalmologists a summarized and objective description about a diabetic patient's health status using a sequence of CCM images that have been captured from different imaging devices and/or at different times.
Avec les approches d'eveil au langage, l'interculturel est au centre de l'apprentissage scolaire (With the Language Awareness Approaches, the Intercultural Is at the Center of School Learning).

Language awareness activities seem to give a new breath to intercultural approaches inside the school. They allow all children to be involved by comparing their languages, by sharing their knowledge, by reflecting on language structures and functions. Children develop a research methodology about linguistic properties and understand that their language system is just one from many others. Thus, linguocentrism falls off. Languages are no more confined in closed islands and equally participate in learning. Classroom becomes a real plurilingual community where children speak at the same time about linguistic questions and their own identities. Intercultural issue is thus directly linked to language awareness activities
Superconductivity in the PbO-type structure α-FeSe

The recent discovery of superconductivity with relatively high transition temperature (Tc) in the layered iron-based quaternary oxypnictides La[O1−xFx] FeAs by Kamihara et al. [Kamihara Y, Watanabe T, Hirano M, Hosono H (2008) Iron-based layered superconductor La[O1-xFx] FeAs (x = 0.05–0.12) with Tc = 26 K. J Am Chem Soc 130:3296–3297. ] was a real surprise and has generated tremendous interest. Although superconductivity exists in alloy that contains the element Fe, LaOMPn (with M = Fe, Ni; and Pn = P and As) is the first system where Fe plays the key role to the occurrence of superconductivity. LaOMPn has a layered crystal structure with an Fe-based plane. It is quite natural to search whether there exists other Fe based planar compounds that exhibit superconductivity. Here, we report the observation of superconductivity with zero-resistance transition temperature at 8 K in the PbO-type α-FeSe compound. A key observation is that the clean superconducting phase exists only in those samples prepared with intentional Se deficiency. FeSe, compared with LaOFeAs, is less toxic and much easier to handle. What is truly striking is that this compound has the same, perhaps simpler, planar crystal sublattice as the layered oxypnictides. Therefore, this result provides an opportunity to better understand the underlying mechanism of superconductivity in this class of unconventional superconductors.
Enabling Efficient Dynamic Resizing of Large DRAM Caches via A Hardware Consistent Hashing Mechanism

Die-stacked DRAM has been proposed for use as a large, high-bandwidth, last-level cache with hundreds or thousands of megabytes of capacity. Not all workloads (or phases) can productively utilize this much cache space, however. Unfortunately, the unused (or under-used) cache continues to consume power due to leakage in the peripheral circuitry and periodic DRAM refresh. Dynamically adjusting the available DRAM cache capacity could largely eliminate this energy overhead. However, the current proposed DRAM cache organization introduces new challenges for dynamic cache resizing. The organization diers from a conventional SRAM cache organization because it places entire cache sets and their tags within a single bank to reduce on-chip area and power overhead. Hence, resizing a DRAM cache requires remapping sets from the powered-down banks to active banks. In this paper, we propose CRUNCH (Cache Resizing Using Native Consistent Hashing), a hardware data remapping scheme inspired by consistent hashing, an algorithm originally proposed to uniformly and dynamically distribute Internet trac across a changing population of web servers. CRUNCH provides a load-balanced remapping of data from the powered-down banks alone to the active banks, without requiring sets from all banks to be remapped, unlike naive schemes to achieve load balancing. CRUNCH remaps only sets from the powered-down banks, so it achieves this load balancing with low bank power-up/down transition latencies. CRUNCH’s combination of good load balancing and low transition latencies provides a substrate to enable ecient DRAM cache resizing.
Enabling Efficient Rebroadcast For Reducing Routing Overhead In Manets

Mobile Ad Hoc NETwork is a wireless network formed by wireless nodes without any help of infrastructure. In this network, nodes are mobile and can communicate dynamically in an arbitrary manner. The network is characterized by the absence of central administration devices like base stations and access points. One of the fundamental challenges in Mobile Ad Hoc NETwork is to discover the route with good performance and less overhead. The overhead of a route discovery cannot be neglected. Limiting the number of rebroadcasts can optimize the broadcasting. Enabling efficient rebroadcast for reducing routing overhead in Mobile Ad Hoc NETwork is used to reduce the number of retransmissions and routing overhead. The probabilistic rebroadcast algorithm is used to calculate the Covered Neighbor set and UnCovered Neighbor set for broadcasting. Broadcasting based on probabilistic rebroadcast algorithm can effectively discover the route by using the additional coverage ratio and connectivity factor. Simulation results are demonstrated using NS-2 Simulator. From these results, the proposed system significantly decreases the number of retransmissions, routing overhead and increases the routing performance.
Capital social et performance économique. Un test économétrique sur l'espace rural français

Cet article commence par presenter une grille de lecture des mecanismes par lesquels les caracteristiques sociologiques peuvent influer sur le developpement economique. De cette grille de lecture, on deduit l’importance de distinguer deux formes de capital social : l’une represente la cohesion locale (bonding), et l’autre les liens a l’exterieur des territoires (bridging). Des indicateurs de ces deux formes de capital social sont proposes et des indices synthetiques en sont tires, dans le cas des zones rurales francaises. Enfin, des estimations econometriques testent l’impact du capital social sur le dynamisme economique de l’espace rural francais. Les resultats suggerent un impact positif et robuste du capital social sous ses deux formes.