Miracle-dz/UniFAR-FTUs huggingface dataset:
Accounting for Phase Drifts in SSVEP-Based BCIs by Means of Biphasic Stimulation

This study proposes a novel biphasic stimulation technique to solve the issue of phase drifts in steady-state visual evoked potential (SSVEPs) in phase-tagged systems. Phase calibration was embedded in stimulus sequences using a biphasic flicker, which is driven by a sequence with alternating reference and phase-shift states. Nine subjects were recruited to participate in off-line and online tests. Signals were bandpass filtered and segmented by trigger signals into reference and phase-shift epochs. Frequency components of SSVEP in the reference and phase-shift epochs were extracted using the Fourier method with a 50% overlapped sliding window. The real and imaginary parts of the SSVEP frequency components were organized into complex vectors in each epoch. Hotelling's t-square test was used to determine the significances of nonzero mean vectors. The rejection of noisy data segments and the validation of gaze detections were made based on p values. The phase difference between the valid mean vectors of reference and phase-shift epochs was used to identify user's gazed targets in this system. Data showed an average information transfer rate of 44.55 and 38.21 bits/min in off-line and online tests, respectively.
Membrane Binding of MinE Allows for a Comprehensive Description of Min-Protein Pattern Formation

The rod-shaped bacterium Escherichia coli selects the cell center as site of division with the help of the proteins MinC, MinD, and MinE. This protein system collectively oscillates between the two cell poles by alternately binding to the membrane in one of the two cell halves. This dynamic behavior, which emerges from the interaction of the ATPase MinD and its activator MinE on the cell membrane, has become a paradigm for protein self-organization. Recently, it has been found that not only the binding of MinD to the membrane, but also interactions of MinE with the membrane contribute to Min-protein self-organization. Here, we show that by accounting for this finding in a computational model, we can comprehensively describe all observed Min-protein patterns in vivo and in vitro. Furthermore, by varying the system's geometry, our computations predict patterns that have not yet been reported. We confirm these predictions experimentally.
A decision-process analysis of implicit coscheduling

This paper presents a theoretical framework based on Bayesian decision theory for analyzing recently reported results on implicit coscheduling of parallel applications on clusters of workstations. Using probabilistic modeling, We show that the approach presented can be applied for processes with arbitrary communication mixes. We also note that our approach can be used for deciding the additional spin times in the case of spin-yield. Finally, we present arguments for the use of a different notion of fairness than assumed by prior work.
Respiratory Syncytial Virus NS1 Protein Colocalizes with Mitochondrial Antiviral Signaling Protein MAVS following Infection

Respiratory syncytial virus (RSV) nonstructural protein 1(NS1) attenuates type-I interferon (IFN) production during RSV infection; however the precise role of RSV NS1 protein in orchestrating the early host-virus interaction during infection is poorly understood. Since NS1 constitutes the first RSV gene transcribed and the production of IFN depends upon RLR (RIG-I-like receptor) signaling, we reasoned that NS1 may interfere with this signaling. Herein, we report that NS1 is localized to mitochondria and binds to mitochondrial antiviral signaling protein (MAVS). Live-cell imaging of rgRSV-infected A549 human epithelial cells showed that RSV replication and transcription occurs in proximity to mitochondria. NS1 localization to mitochondria was directly visualized by confocal microscopy using a cell-permeable chemical probe for His6-NS1. Further, NS1 colocalization with MAVS in A549 cells infected with RSV was shown by confocal laser microscopy and immuno-electron microscopy. NS1 protein is present in the mitochondrial fraction and co-immunoprecipitates with MAVS in total cell lysatesof A549 cells transfected with the plasmid pNS1-Flag. By immunoprecipitation with anti-RIG-I antibody, RSV NS1 was shown to associate with MAVS at an early stage of RSV infection, and to disrupt MAVS interaction with RIG-I (retinoic acid inducible gene) and the downstream IFN antiviral and inflammatory response. Together, these results demonstrate that NS1 binds to MAVS and that this binding inhibits the MAVS-RIG-I interaction required for IFN production.
Link adaptation strategy for IEEE 802.11 WLAN via received signal strength measurement

IEEE 802.11 wireless local area network (WLAN) physical layers (PHYs) support multiple transmission rates. The PHY rate to be used for a particular frame transmission is solely determined by the transmitting station. The transmitting rate should be chosen in an adaptive manner since the wireless channel condition varies over time due to such factors as station mobility, time-varying interference, and location-dependent errors. In this paper, we present a novel link adaptation algorithm, which aims to improve the system throughput by adapting the transmission rate to the current link condition. Our algorithm is simply based on the received signal strength measured from the received frames, and hence it does not require any changes in the current IEEE 802.11 WLAN medium access control (MAC) protocol. Based on the simulation and its comparison with a numerical analysis, it is shown that the proposed algorithm closely approximates the ideal case with the perfect knowledge about the channel and receiver conditions.
Semi-Automated Extension of a Specialized Medical Lexicon for French

This paper describes the development of a specialized lexical resource for a specialized domain, namely medicine. First, in order to assess the linguistic phenomena that need to be adressed, we based our observation on a large collection of more than 300'000 terms, organised around conceptual identifiers. Based on these observations, we highlight the specificities that such a lexicon should take into account, namely in terms of inflectional and derivational knowledge. In a first experiment, we show that general resources lack a large part of the words needed to process specialized language. Secondly, we describe an experiment to feed semi-automatically a medical lexicon and populate it with inflectional information. This experiment is based on a semi-automatic methods that tries to acquire inflectional knowledge from frequent endings of words recorded in existing lexicon. Thanks to this, we increased the coverage of the target vocabulary from 14.1% to 25.7%.
Learning a Super Mario controller from examples of human play

Imitating human-like behaviour in action games is a challenging but intriguing task in Artificial Intelligence research, with various strategies being employed to solve the human-like imitation problem. In this research we consider learning human-like behaviour via Markov decision processes without being explicitly given a reward function, and learning to perform the task by observing expert's demonstration. Individual players often have characteristic styles when playing the game, and this method attempts to find the behaviours which make them unique. During play sessions of Super Mario we calculate player's behaviour policies and reward functions by applying inverse reinforcement learning to the player's actions in game. We conduct an online questionnaire which displays two video clips, where one is played by a human expert and the other is played by the designed controller based on the player's policy. We demonstrate that by using apprenticeship learning via Inverse Reinforcement Learning, we are able to get an optimal policy which yields performance close to that of an human expert playing the game, at least under specific conditions.
A fast direct Fourier-based algorithm for subpixel registration of images

This paper presents a new direct Fourier-based algorithm for performing image-to-image registration to subpixel accuracy, where the image differences are restricted to translations and uniform changes of illumination. The algorithm detects the Fourier components that have become unreliable estimators of shift due to aliasing, and removes them from the shift-estimate computation. In the presence of aliasing, the average precision of the registration is a few hundredths of a pixel. Experimental data presented here show that the new algorithm yields superior registration precision in the presence of aliasing when compared to several earlier methods and has comparable precision to the iterative method of P. Thevenaz et al. (1998).
Qualitative descriptors applied to ambient intelligent systems

In this paper, qualitative descriptors of images (QIDL+), 3D scenes (QSn3D) and movements (QMD) are proposed to be applied to ambient intelligent systems for: (i) improving human-computer interaction and (ii) enhancing their reasoning capabilities. These qualitative descriptors align with human perception and are used to produce narratives. Moreover, logic descriptions are obtained in first order logic and Prolog syntax, which enables straightforward reasoning capabilities. Finally, some use case tests carried out at Cartesium – the intelligent building at Spatial Cognition centre, at the University of Bremen – are provided to show the flexibility and applicability of these qualitative descriptors. The results provided are discussed in terms of usability, logic framework used and integration of descriptors.
Association between Toll-Like Receptor 4 Expression and Neural Stem Cell Proliferation in the Hippocampus Following Traumatic Brain Injury in Mice

Whether or how neural stem cells (NSCs) respond to toll-like receptor 4 (TLR4) in an inflammatory environment caused by traumatic brain injury (TBI) has not been understood. In the present study, association between TLR4 expression and NSCs proliferation in the hippocampus was investigated in a mouse model of TBI using controlled cortical impact (CCI). Hippocampal proliferating cells were labeled with the thymidine analog 5-bromo-2-deoxyuridine (BrdU). In order to identify NSCs, the proliferating cells were further co-labeled with BrdU/sex determination region of Y chromosome related high mobility group box gene 2 (SOX2). Morphological observation on the expression of BrdU, SOX2, and TLR4 in the hippocampus was performed by inmmunofluorescence (IF). Relative quantification of TLR4 expression at the protein and mRNA level was performed using Western blotting and real-time polymerase chain reaction (PCR). It was observed that BrdU+/SOX2+ cells accounted for 95.80% ± 7.91% among BrdU+ cells; several BrdU+ cells and SOX2+ cells in the hippocampus were also TLR4-positive post injury, and that BrdU+ cell numbers, together with TLR4 expression at either protein or mRNA level, increased significantly in TBI mice over 1, 3, 7, 14, and 21 days survivals and changed in a similar temporal pattern with a peak at 3 day post-injury. These results indicate that hippocampal proliferating cells (suggestive of NSCs) expressed TLR4, and that there was a potential association between increased expression of TLR4 and the proliferation of NSCs post TBI. It is concluded that hippocampal TLR4 may play a potential role in endogenous neurogenesis after TBI.
MIMODog: How to solve the problem of selfish misbehavior detection mechanism in MANETs using MIMO technology

Mobile Ad-hoc Networks (MANETs) are based on a fundamental aspect, which is the cooperative parameter. This parameter may compromise the networks. The selfish misbehaving nodes can seriously affect the network performance. Moreover, the existing mechanisms based on the monitoring process to detect the misbehaving nodes are not efficient and suffer from an important false alarm rate. These weaknesses are mainly due to the interferences and the costs of the monitoring process. In MANET based on SISO (Single-Input Single-Output) technology, the interferences at the monitor node compromise the observation and the accuracy of the cooperation report. That is why in this paper, we focus on the MIMO (Multi-Input and Multi-Output) technology to overcome these drawbacks and to significantly improve the monitoring process. We propose a new MAC protocol called MIMODog-SPACE-MAC based on the well-known SPACE-MAC protocol. It allows the monitor node to avoid the collision during the monitoring process by adjusting the antennas weights in order to nullify the signal coming from other nodes than the monitored one. Therefore, the proposed solution contributes to significantly enhance the accuracy of the monitoring process. We show that for a MIMO network with randomly located nodes n, each equipped with M antennas, the achievable number of monitor nodes is Θ(M/√(n ln n)). Indeed, theoretical results show that by using MIMODog-SPACE-MAC, the network can have a constant improvement M on an asymptotic number of monitor nodes compared to SISO 802.11 DCF MAC.
Examining Diagnosis Paths: A Process Mining Approach

This paper is motivated by two observations on computer-supported education: First, there has been growing availability, rapid proliferation, and increased diversity of learner-system educational data. Second, advances in learning analytics and data mining have facilitated and spawned a variety of novel investigations using such data. Driven by these complementary trends, the present work is geared towards exploring knowledge-based discovery approaches in understanding learner-system usage data. More specifically, with an eye toward tracing and comprehending learner behaviors in a medical intelligent tutoring system, we explore the utility of Process Mining, in understanding the problem solving trajectories of students in a medical computer-based learning environment.
Human Sensing Using Computer Vision for Personalized Smart Spaces

Smart spaces are everyday environments augmented with computing technologies that enhance human experience and activity performance. Continuous recognition of the presence of people, their identity, location, movement and activity patterns in real-time is a key challenge to address if smart spaces are to be envisioned as personalized and adaptive spaces. This paper introduces the multiple technologies available for human sensing and identification, discussing their advantages and disadvantages. In particular, Kitchen As-A-Pal is described as a smart space with real-time human sensing capabilities using computer vision by fusing fisher face recognition and skeletal tracking approaches. A wall-mounted Kinect is used for both single occupant and multi-occupant settings in kitchen As-A-Pal. The fused approach gives human identity recognition accuracy of 91.75% precision and 66% recall values for single occupant setting with good smart space coverage. Challenges do exist for human identity recognition in multi-occupant settings.
Relation of meat, fat, and fiber intake to the risk of colon cancer in a prospective study among women.

BACKGROUND The rates of colon cancer in various countries are strongly correlated with the per capita consumption of red meat and animal fat and, to a lesser degree, inversely associated with the consumption of fiber. METHODS We conducted a prospective study among 88,751 women 34 to 59 years old and without a history of cancer, inflammatory bowel disease, or familial polyposis who completed a dietary questionnaire in 1980. By 1986, during 512,488 person-years of follow-up, 150 incident cases of colon cancer had been documented. RESULTS After adjustment for total energy intake, animal fat was positively associated with the risk of colon cancer (P for trend = 0.01); the relative risk for the highest as compared with the lowest quintile was 1.89 (95 percent confidence interval, 1.13 to 3.15). No association was found for vegetable fat. The relative risk of colon cancer in women who ate beef, pork, or lamb as a main dish every day was 2.49 (95 percent confidence interval, 1.24 to 5.03), as compared with those reporting consumption less than once a month. Processed meats and liver were also significantly associated with increased risk, whereas fish and chicken without skin were related to decreased risk. The ratio of the intake of red meat to the intake of chicken and fish was particularly strongly associated with an increased incidence of colon cancer (P for trend = 0.0005); the relative risk for women in the highest quintile of this ratio as compared with those in the lowest quintile was 2.49 (95 percent confidence interval, 1.50 to 4.13). A low intake of fiber from fruits appeared to contribute to the risk of colon cancer, but this relation was not statistically independent of meat intake. CONCLUSIONS These prospective data provide evidence for the hypothesis that a high intake of animal fat increases the risk of colon cancer, and they support existing recommendations to substitute fish and chicken for meats high in fat.
Occupancy grid mapping with Markov Chain Monte Carlo Gibbs sampling

Occupancy grids have been widely used for mapping with mobile robots for nearly 30 years. Occupancy grids discretize the analog environment and seek to determine the occupancy probability of each cell. Traditional occupancy grid mapping methods make two assumptions for computational efficiency and it has been shown that the full posterior is computationally intractable without these assumptions. This paper employs a form of Markov Chain Monte Carlo (MCMC) known as Gibbs sampling to sample from the full posterior. By drawing many samples, we are able to capture the full posterior, which more accurately represents the uncertainty in the map due to sensor measurement error. The MCMC method is shown to compute the full posterior in a 1D toy example, and it is shown to be computationally tractable, though not online, for realistic 2D simulations.
Automatic image segmentation with Anisotropic Fast Marching algorithm and geodesic voting

Segmentation methods based on energy minimization techniques like geodesic active contour model generally needs manual intervention to provide initial points to calculate minimal paths. In this paper, we propose complete automation of segmentation. Seeds and Tips are automatically detected, and geodesics are calculated using Anisotropic Fast Marching algorithm. Fast Marching algorithm computes in a single pass, the evolution of the front, at a speed locally given by its position. Anisotropic Fast Marching (AFM) is a variant of Fast Marching, in which the the measure of path length (and the front speed) depends not only on the path position, but also on path direction and orientation. In this work, a gradient based metric has been defined and AFM is evaluated iteratively over a set of points which are automatically detected on the object boundary. Geodesic voting is then applied to get the segmented structure.
Based on RPCL Object Position Clustering under Cellular Network

Aiming to problem how to cluster object position under cellular network situation, using the method of random selection and position, an improved RPCL (Rival Penalized Competitive Learning) algorithm is designed to handle this question, an improved RPCL algorithm is designed to handle this problem. Though theoretical derivation, the correctness of improved RPCL algorithm is proofed. The correctness of improved RPCL algorithm and theoretical derivation is also verified by experiment.
Humour as emotion regulation: The differential consequences of negative versus positive humour

Humour is often seen as an adaptive coping strategy; however, the empirical literature is inconclusive. One possible explanation is that different types of humour have different adaptive consequences. In the present research, we predicted that positive (good-natured) humour would be more effective at regulating negative emotions than negative (mean-spirited) humour. In Study 1, participants were shown negative pictures two times. First, they simply viewed the pictures and rated their levels of positive and negative emotions. Second, they were instructed to: (a) view; (b) use positive humour; or (c) use negative humour, and then rate their reactions. Compared to negative humour, positive humour was more successful at down-regulating negative and up-regulating positive emotion. In Study 2, we replicated these findings and showed that these effects cannot be explained by differences in difficulty between the two humour conditions, participants’ expectations, or social desirability. Taken together, these findings suggest that positive (but not negative) humour may be an effective form of emotion regulation.
Autophagy and microtubules – new story, old players

Summary Both at a basal level and after induction (especially in response to nutrient starvation), the function of autophagy is to allow cells to degrade and recycle damaged organelles, proteins and other biological constituents. Here, we focus on the role microtubules have in autophagosome formation, autophagosome transport across the cytoplasm and in the formation of autolysosomes. Recent insights into the exact relationship between autophagy and microtubules now point to the importance of microtubule dynamics, tubulin post-translational modifications and microtubule motors in the autophagy process. Such factors regulate signaling pathways that converge to stimulate autophagosome formation. They also orchestrate the movements of pre-autophagosomal structures and autophagosomes or more globally organize and localize immature and mature autophagosomes and lysosomes. Most of the factors that now appear to link microtubules to autophagosome formation or to autophagosome dynamics and fate were identified initially without the notion that sequestration, recruitment and/or interaction with microtubules contribute to their function. Spatial and temporal coordination of many stages in the life of autophagosomes thus underlines the integrative role of microtubules and progressively reveals hidden parts of the autophagy machinery.
Pipage Rounding, Pessimistic Estimators and Matrix Concentration

Pipage rounding is a dependent random sampling technique that has several interesting properties and diverse applications. One property that has been useful in applications is negative correlation of the resulting vector. There are some further properties that would be interesting to derive, but do not seem to follow from negative correlation. In particular, recent concentration results for sums of independent random matrices are not known to extend to a negatively dependent setting. We introduce a simple but useful technique called concavity of pessimistic estimators. This technique allows us to show concentration of submodular functions and concentration of matrix sums under pipage rounding. The former result answers a question of Chekuri et al. (2009). To prove the latter result, we derive a new variant of Lieb's celebrated concavity theorem in matrix analysis. We provide numerous applications of these results. One is to spectrally-thin trees, a spectral analog of the thin trees that played a crucial role in the recent breakthrough on the asymmetric traveling salesman problem. We show a polynomial time algorithm that, given a graph where every edge has effective conductance at least κ, returns an O(κ-1 · log n/log log n)-spectrally-thin tree. There are further applications to rounding of semidefinite programs and to a geometric question of extracting a nearly-orthonormal basis from an isotropic distribution.