Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordination Demand in Human Control of Heterogeneous Robot

The performance of human-robot teams is complex and multifaceted reflecting the capabilities of the robots, the operator(s), and the quality of their interactions. Recent efforts to define common metrics for human-robot interaction (Steinfeld et al., 2006) have favored sets of metric classes to measure the effectiveness of the system’s constituents and their interactions as well as the system’s overall performance. In this chapter we follow this approach to develop measures characterizing the demand imposed by tasks requiring cooperation among heterogeneous robots. Applications for multirobot systems (MRS) such as interplanetary construction or cooperating uninhabited aerial vehicles will require close coordination and control between human operator(s) and teams of robots in uncertain environments. Human supervision will be needed because humans must supply the perhaps changing goals that direct MRS activity. Robot autonomy will be needed because the aggregate decision making demands of a MRS are likely to exceed the cognitive capabilities of a human operator. Autonomous cooperation among robots, in particular, will likely be needed because it is these activities (Gerkey & Mataric, 2004) that theoretically impose the greatest decision making load. Controlling multiple robots substantially increases the complexity of the operator’s task because attention must constantly be shifted among robots in order to maintain situation awareness (SA) and exert control. In the simplest case an operator controls multiple independent robots interacting with each as needed. A search task in which each robot searches its own region would be of this category although minimal coordination might be required to avoid overlaps and prevent gaps in coverage. Control performance at such tasks can be characterized by the average demand of each robot on human attention (Crandal et al., 2005). Under these conditions increasing robot autonomy should allow robots to be neglected for longer periods of time making it possible for a single operator to control more robots. Because of the need to share attention between robots in MRS, teloperation can only be used for one robot out of a team (Nielsen et al., 2003) or as a selectable mode (Parasuraman et al., 2005). Some variant of waypoint control has been used in most of the MRS studies we have reviewed (Crandal et al., 2005, Nielsen et al., 2003, Parasuraman et al., 2005, Trouvain & Wolf, 2002) with differences arising primarily in behavior upon reaching a waypoint. A more fully autonomous mode has typically been included involving things such as search of
Associations between tactile localization and motor function in children with motor deficits

Children with developmental disorders often have poor motor performance. This study aimed to address the association between tactile localization ability, an indicator of body image, and motor function in children with motor deficits. Eighteen children with motor deficits participated, and their upper and lower limbs were assessed. To assess the level to which the patient’s body image was developed, a tactile localization task (TLT) was used. In the TLT, experimenters touched a child’s fingers, toes, or lower extremities (L/E), and the participants were asked to identify the location of the touch on a body part illustration. We compared TLT ability between high and low motor function groups, and investigated the correlation between TLT and the measures of motor function, age, and non-verbal intelligence. The high motor function group had significantly higher L/E TLT scores than the low motor function group, except in the tests involving the fingers and toes. Furthermore, the L/E TLT correlated only with motor function measures (Gross Motor Function Measure score, measured using one-leg standing time and one-leg hopping ability). The results suggest that children with motor deficits experience developmental delay in terms of their body image.
An Approach for Representing Sensor Data to Validate Alerts in Ambient Assisted Living

The mainstream of research in Ambient Assisted Living (AAL) is devoted to developing intelligent systems for processing the data collected through artificial sensing. Besides, there are other elements that must be considered to foster the adoption of AAL solutions in real environments. In this paper we focus on the problem of designing interfaces among caregivers and AAL systems. We present an alert management tool that supports carers in their task of validating alarms raised by the system. It generates text-based explanations—obtained through an argumentation process—of the causes leading to alarm activation along with graphical sensor information and 3D models, thus offering complementary types of information. Moreover, a guideline to use the tool when validating alerts is also provided. Finally, the functionality of the proposed tool is demonstrated through two real cases of alert.
Effects of Developmental Heuristics for Natural Language Learning

Machine learning in natural language has been a widely pursued area of research. However, few learning techniques model themselves after human learning, despite the nature of the task being closely connected to human cognition. In particular, the idea of learning language in stages is a common approach for human learning, as can be seen in practice in the education system and in research on language acquisition. However, staged learning for natural language is an area largely overlooked by machine learning researchers. This thesis proposes a developmental learning heuristic for natural language models, to evaluate its performance on natural language tasks. The heuristic simulates human learning stages by training on child, teenage and adult text, provided by the British National Corpus. The three staged learning techniques that are proposed take advantage of these stages to create a single developed Hidden Markov Model. This model is then applied to the task of part-of-speech tagging to observe the effects of development on language learning.
Protein Tyrosine Phosphatases PTP-1B, SHP-2, and PTEN Facilitate Rb/E2F-Associated Apoptotic Signaling

To maintain tissue homeostasis, apoptosis is functionally linked to the cell cycle through the retinoblastoma (Rb)/E2F pathway. When the Rb tumor suppressor protein is functionally inactivated, E2F1 elicits an apoptotic response through both intrinsic (caspase-9 mediated) and extrinsic (caspase-8 mediated) apoptotic pathways in order to eliminate hyperproliferative cells. Rb/E2F-associated apoptosis has been demonstrated to be associated with the loss of constitutive transcriptional repression by Rb/E2F complexes and mediated by caspase-8. Protein tyrosine phosphatases (PTPs) PTP-1B and SHP-2 have been previously shown to be directly activated by loss of Rb/E2F repression during Rb/E2F-associated apoptosis. In this current study, we demonstrate that the PTEN tumor suppressor is also directly activated by loss of Rb/E2F repression. We also demonstrate that PTP-1B, SHP-2, and PTEN play a functional role in Rb/E2F-associated apoptosis. Knockdown of PTP1B, SHP2, or PTEN expression with small interfering RNA (siRNA) in apoptotic cells increases cell viability and rescues cells from the Rb/E2F-associated apoptotic response. Furthermore, rescue from apoptosis coincides with inhibition of caspase-8 and caspase-3 cleavage (activation). Our results indicate PTP-1B, SHP-2, and PTEN all play a functional role in Rb/E2F-associated apoptotic signal transduction and provide further evidence that PTP-1B, SHP-2, and PTEN can contribute to tumor suppression through an Rb/E2F-associated mechanism.
The Effects of High Stress on Attention

Attentional narrowing – the involuntary reduction in the range of cues that can be utilized by an individual – represents a major threat in many complex data-rich domains. Still, very little empirical research has been conducted to better understand and overcome the problem, in large part because it is difficult to reliably induce the phenomenon in controlled settings. The present study examined the effectiveness of two factors – high attentional load and ego-threat - for inducing high levels of stress and attentional narrowing in the context of a simplified air traffic control (ATC) task. Five participants were asked to complete two simultaneous noticing tasks - one presented centrally, the other in the periphery of the screen. In the high stress condition, they also had to perform a concurrent paced addition task (high attentional load) and received false feedback on their performance (ego-threat). Performance on the two main ATC tasks and the addition task was measured. Subjective ratings were collected to assess participants’ anxiety levels. High attentional load and ego-threat increased participants’ anxiety level. Overall, performance on the ATC tasks suffered slightly during high stress, suggesting a reduction in the spread of attention. Also, performance on the addition was significantly reduced when performed concurrently with the ATC tasks, as compared to the training phase. The findings from this study represent an important step towards being able to induce and study attentional narrowing systematically and to develop countermeasures to this significant safety threat.
Primate frontal eye fields. III. Maintenance of a spatially accurate saccade signal.

1. We studied the activity of single neurons in the monkey frontal eye fields during oculomotor tasks designed to assess the activity of these neurons when there was a dissonance between the spatial location of a target and its position on the retina. 2. Neurons with presaccadic activity were first studied to determine their receptive or movement fields and to classify them as visual, visuomovement, or movement cells with the use of the criteria described previously (Bruce and Goldberg 1985). The neurons were then studied by the use of double-step tasks that dissociated the retinal coordinates of visual targets from the dimensions of saccadic eye movements necessary to acquire those targets. These tasks required that the monkeys make two successive saccades to follow two sequentially flashed targets. Because the second target disappeared before the first saccade occurred, the dimensions of the second saccade could not be based solely on the retinal coordinates of the target but also depended on the dimensions of the first saccade. We used two versions of the double-step task. In one version neither target appeared in the cell's receptive or movement field, but the second eye movement was the optimum amplitude and direction for the cell (right-EM/wrong-RF task). In the other the second stimulus appeared in the cell's receptive field, but neither eye movement was appropriate for the cell (wrong-EM/right-RF task). 3. Most frontal-eye-field cells discharged in the right-EM/wrong-RF version of the double-step task. Their discharge began after the first saccade and continued until the second saccade was made. They usually discharged even on occasional trials in which the monkey failed to make the second saccade. They discharged much less, or not at all, in the wrong-EM/right-RF version of the double-step paradigm. Thus most presaccadic cells in the frontal eye fields were tuned to the dimensions of saccadic eye movements rather than to the coordinates of retinal stimulation. 4. Eleven movement cells (including 1 which also had independent postsaccadic activity for saccades opposite its presaccadic movement field) were studied, and all had significant activity in the right-EM/wrong-RF task. 5. Almost all (28/32) visuomovement cells, including 12 with independent postsaccadic activity, discharged in the right-EM/wrong-RF task. None of the four that failed had independent postsaccadic activity. 6. The majority (26/40) of visual cells were responsive in the right-EM/wrong-RF task. (ABSTRACT TRUNCATED AT 400 WORDS)
Multimodal sensing of affect intensity

Most research on affect intensity has relied on the Affect Intensity Measure (AIM) of self-report that asks respondents to rate how often they react to situations with strong emotions. The AIM gives an indication of how strongly or weakly individuals tend to experience emotions in their everyday life. In this PhD project, I plan to quantify the affect intensity on a continuous scale using multiple modalities of video and audio on real-world, clinically validated depression datasets. Most of the work in this area treats the problem as a binary classification problem, mainly due to the lack of dimensional data. As the depression severity of a subject increases, as seen in the case of melancholia, the facial movements become very subtle. In order to quantify depression in general, and subtypes such as melancholia in particular, we need to reveal these subtle changes. To do this, I propose to use video magnification approaches. Inspired by the success of deep learning in video classification, I plan on using deep learning for information fusion over multiple modalities, such as Convolutional Neural Networks and Long Short Term Memory Networks. Using the common approach to video classification, i.e. local feature extraction, fixed size video level description and training a classifier on the resulting bag of words representation, I present preliminary results on the classification of melancholic and non-melancholic depressed subjects and healthy controls, which will serve as a baseline for future development in depression classification and analysis. I have also compared the sensitivity and specificity of classification in depression sub-types.
Codebook constrained Wiener filtering for speech enhancement

Speech enhancement using iterative Wiener filtering has been shown to require interframe and intraframe constraints in all-pole parameter estimation. We show that a clean speech VQ codebook is more effective in providing intraframe constraints and, hence, better convergence of the iterative filtering scheme. Satisfactory speech enhancement results are obtained with a small codebook of 128, and the algorithm is effective for both white noise and pink noise up to 0 dB SNR.
Cerebrally Lateralized Mental Representations of Hand Shape and Movement

Previous psychophysical and neuroimaging studies suggest that perceiving the handedness of a visually presented hand depends on sensorimotor processes that are specific to the limb of the stimulus and that may be controlled by the cerebral hemisphere contralateral to the limb. Therefore, it was hypothesized that disconnection between cerebral hemispheres would disrupt mental simulation of a hand presented to the ipsilateral, but not the contralateral, hemisphere. This hypothesis was examined by the present study in which two callosotomy patients and eight healthy controls judged the handedness of drawings of left and right hands in various positions, without moving or inspecting their own hands. Stimuli were presented for 150 msec in the right or left visual hemifield. As predicted, for each hemisphere, patients’ accuracy was high when the hand was contralateral to the perceiving hemisphere, but it was not above chance when it was ipsilateral to the perceiving hemisphere. Controls’ accuracy was high in both conditions. Response time analyses indicate patients, like controls, mentally simulated reaching into stimulus postures. When the stimulus laterality was ipsilateral to the perceiving hemisphere, patients imagined the hand contralateral to the perceiving hemisphere reaching into the stimulus posture but did not detect the mismatch, guessing with a response bias or responding on the basis of shape similarity. We conclude that each hemisphere could represent the shape and movement of the contralateral hand but could not for the ipsilateral hand. Mentally simulating one’s action and discriminating body part handedness both depend on lateralized sensorimotor and somatosensory representations.
Efficient Fast Independent Component Analysis Algorithm with Fifth-Order Convergence

⎯Independent component analysis (ICA) is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton's iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.
On the Power of Randomized Ordered Branching Programs

We deene the notion of a randomized branching program in the natural way similar to the deenition of a randomized circuit. We exhibit an explicit boolean function f n : f0;1g n ! f0;1g for which we prove that: 1) f n can be computed by polynomial size randomized read-once ordered branching program with a small one-sided error; 2) f n cannot be computed in polynomial size by nondeterministic ordered read A-k-times branching program for k = o(n= log n) (any non-deterministic ordered read A-k-times branching program that computes function f n has the size no less than 2 (n? 1)=(2k? 1)). By read A-k-times branching program we deene branching program with the property: no input variable appears more than k times on any consistent accepting computation path in the program. 1 Preliminaries and deenitions Diierent models of branching program introduced in 18, 19], has been studied extensively in the last decade (see 25]). A survey of known lower bounds for diierent models of branching programs can be found in 22]. Developments in the eld of digital design and veriication have led to the introduction of restricted forms of branching programs. In circuit veriication ordered binary decision diagrams (OBDD) or ordered read-once branching program are used 9], 26]. But many important functions cannot be computed by read-once branching programs of polynomial size. For more information see the survey 9] and papers 23], 20]. Implementation of randomization in computation can reduce complexity sometimes. Diierent such examples are known 16]. These examples lead to
Bacterial Diversity in Meconium of Preterm Neonates and Evolution of Their Fecal Microbiota during the First Month of Life

The establishment and succession of bacterial communities in infants may have a profound impact in their health, but information about the composition of meconium microbiota and its evolution in hospitalized preterm infants is scarce. In this context, the objective of this work was to characterize the microbiota of meconium and fecal samples obtained during the first 3 weeks of life from 14 donors using culture and molecular techniques, including DGGE and the Human Intestinal Tract Chip (HITChip) analysis of 16S rRNA amplicons. Culture techniques offer a quantification of cultivable bacteria and allow further study of the isolate, while molecular techniques provide deeper information on bacterial diversity. Culture and HITChip results were very similar but the former showed lower sensitivity. Inter-individual differences were detected in the microbiota profiles although the meconium microbiota was peculiar and distinct from that of fecal samples. Bacilli and other Firmicutes were the main bacteria groups detected in meconium while Proteobacteria dominated in the fecal samples. Culture technique showed that Staphylococcus predominated in meconium and that Enterococcus, together with Gram-negative bacteria such as Escherichia coli, Escherichia fergusonii, Klebsiella pneumoniae and Serratia marcescens, was more abundant in fecal samples. In addition, HITChip results showed the prevalence of bacteria related to Lactobacillus plantarum and Streptococcus mitis in meconium samples whereas those related to Enterococcus, Escherichia coli, Klebsiella pneumoniae and Yersinia predominated in the 3rd week feces. This study highlights that spontaneously-released meconium of preterm neonates contains a specific microbiota that differs from that of feces obtained after the first week of life. Our findings indicate that the presence of Serratia was strongly associated with a higher degree of immaturity and other hospital-related parameters, including antibiotherapy and mechanical ventilation.
Security or insecurity? Representations of the UK border in public and policy discourses

Abstract This article analyses representations of the UK border (in relation to migration) in UK public and policy discourses. It uses methods from corpus linguistics and critical discourse analysis to compare the two discursive domains. A 26 million-word corpus of policy documentation and British newspaper articles published between 2007 and 2014 is examined using the analysis tool Sketch Engine and applying qualitative concordance analysis. The analysis reveals a key difference between the two domains: while the UK border is represented as a security concept in the policy corpus, the corpus of the public newspaper domain frequently and saliently represents the UK border as a concept dominated by insecurity. The article argues that the discursive label of European Union has played a role in contributing to this difference.
Exploring the potential of facial skin regions for the provision of identity information

This work presents a novel framework to investigate the possibility of using textural information from facial skin regions for biometric identification of individuals. Such information is of practical use when the entire facial image is not available for identifying individuals, such as in forensic investigations. Here, four facial regions were investigated (forehead, right cheek, left cheek, and chin), since they are likely to be visible even in partially occluded facial images and they are relatively easy to distinguish. Facial landmarks are automatically detected to facilitate the extraction of these facial regions of interest. A skin detection technique is applied to identify regions with significant skin content. Each skin region is then processed independently using features based on Local Binary Patterns and Gabor wavelet filters. Feature fusion of sub-regions is used prior to classification of the images. Experiments were carried out, using the publicly available Skin Segmentation database and the XM2VTS databases, to evaluate the performance of skin detection technique and biometric recognition respectively. The results show that the skin detection algorithm provided comparable results to other state-of-the-art techniques. Of the regions investigated, the forehead and chin regions were found to provide a rich source of biometric information.
A Probabilistic Model for Cell Cycle Distributions in Synchrony Experiments

Synchronized populations of cells are often used to study dynamic processes during the cell division cycle. However, the analysis of time series measurements made on synchronized populations are confounded by the fact that populations lose synchrony over time. Time series measurements are thus averages over a population distribution that is broadening over time. Moreover, direct comparison of measurements taken from multiple synchrony experiments is difficult, as the kinetics of progression during the time series are rarely comparable. Here, we present a flexible mathematical model that describes the dynamics of population distributions resulting from synchrony loss over time. The model was developed using S. cerevisiae, but we show that it can be easily adapted to predict distributions in other organisms. We demonstrate that the model reliably fits data collected from populations synchronized by multiple techniques, and can accurately predict cell cycle distributions as measured by other experimental assays. To indicate its broad applicability, we show that the model can be used to compare global periodic transcription data sets from different organisms: S. cerevisiae and S. pombe.