Miracle-dz/UniFAR-FTUs huggingface dataset:
The rehabilitation of face recognition impairments: a critical review and future directions

While much research has investigated the neural and cognitive characteristics of face recognition impairments (prosopagnosia), much less work has examined their rehabilitation. In this paper, we present a critical analysis of the studies that have attempted to improve face-processing skills in acquired and developmental prosopagnosia, and place them in the context of the wider neurorehabilitation literature. First, we examine whether neuroplasticity within the typical face-processing system varies across the lifespan, in order to examine whether timing of intervention may be crucial. Second, we examine reports of interventions in acquired prosopagnosia, where training in compensatory strategies has had some success. Third, we examine reports of interventions in developmental prosopagnosia, where compensatory training in children and remedial training in adults have both been successful. However, the gains are somewhat limited—compensatory strategies have resulted in labored recognition techniques and limited generalization to untrained faces, and remedial techniques require longer periods of training and result in limited maintenance of gains. Critically, intervention suitability and outcome in both forms of the condition likely depends on a complex interaction of factors, including prosopagnosia severity, the precise functional locus of the impairment, and individual differences such as age. Finally, we discuss future directions in the rehabilitation of prosopagnosia, and the possibility of boosting the effects of cognitive training programmes by simultaneous administration of oxytocin or non-invasive brain stimulation. We conclude that future work using more systematic methods and larger participant groups is clearly required, and in the case of developmental prosopagnosia, there is an urgent need to develop early detection and remediation tools for children, in order to optimize intervention outcome.
Research of universal characteristic curve using MATLAB

This paper proposes two surface fitting methods, one is direct surface fitting method and the other is a method, which mixes polynomial and interpolation to get fitting curve and then generate the fitting surface. The engine universal characteristic curve can be drawn using iso-line method from the given surface. The two methods cannot only be effective, but also can deduce more accurate curve functions and intuitive fitting curves. Both of the methods are simple and have intuitive physical meaning.
Repeatability Using Automatic Tracing with Canon OCT- HS100 and Zeiss Cirrus HD-OCT 5000

Background Optical coherence tomography (OCT), can be used in clinical practice to provide high resolution cross-sectional images of the retina, optic disc and macula structure. These measurements can be useful for early detection, diagnosis, monitoring and treatment guidance for retinal diseases. Therefore, repeatability of measurements in OCT is of great importance. Methods Macula and optic disc parameters from the right eye of 30 healthy subjects were obtained twice with the Canon OCT-HS100 and Zeiss Cirrus HD-OCT 5000. Repeatability was evaluated by use of the coefficient of repeatability (CR) and the coefficient of repeatability as a percentage of the mean (CR%), and the obtained measurements were compared between the instruments. Results CR% of optic disc parameters ranged between 0.90 and 22.22% and 0.00 and 16.00% with the Canon and Zeiss OCT respectively. For macular parameters CR% ranged between 0.62 and 2.81% and 0.99 and 1.81% with the Canon and Zeiss OCT respectively. No statistical difference could be found when comparing the CR of all macular and disc measurements between the instruments. Compared to our previously published data repeatability has significantly improved with the inclusion of automatic tracking systems with both the Canon and Zeiss OCT. Conclusion Automatic tracking function improves repeatability in both Canon OCT-HS100 and Zeiss Cirrus HD-OCT 5000. However, measurements generated by the two instruments are still not interchangeable.
All‐uses testing of shared memory parallel programs

Parallelism has become a way of life for many scientific programmers. A significant challenge in bringing the power of parallel machines to these programmers is providing them with a suite of software tools similar to the tools that sequential programmers currently utilize. Unfortunately, writing correct parallel programs remains a challenging task.In particular, automatic or semi‐automatic testing tools for parallel programs are lacking. This paper takes a first step in developing an approach to providing all‐uses coverage for parallel programs. A testing framework and theoretical foundations for structural testing are presented, including test data adequacy criteria and hierarchy, formulation and illustration of all‐uses testing problems, classification of all‐uses test cases for parallel programs, and both theoretical and empirical results with regard to what can be achieved with all‐uses coverage for parallel programs. Copyright © 2003 John Wiley & Sons, Ltd.
CONSTRUCTING EQUIVARIANT MAPS FOR REPRESENTATIONS

We show that if i is a discrete subgroup of the group of the isometries of H k , and if ½ is a representation of i into the group of the isometries of H n , then any ½-equivariant map F : H k → H n extends to the boundary in a weak sense in the setting of Borel measures. As a consequence of this fact, we obtain an extension of a result of Besson, Courtois and Gallot about the existence of volume non-increasing, equivariant maps. Then, we show that the weak extension we obtain is actually a measurable ½-equivariant map in the classical sense. We use this fact to obtain measurable versions of Cannon-Thurston-type results for equivari- ant Peano curves. For example, we prove that if i is of divergence type and ½ is non-elementary, then there exists a measurable map D : @H k → @H n conjugating the actions of i and ½(i). Related applications are discussed.
Electromagnetic Model for SAR Imaging of Natural Surfaces

In this paper an innovative, completely fractal-based model describing the SAR imaging process of natural scenes is presented. In the hypothesis that a small slope regime can be assumed for the surface, we evaluate here, in closed form, the Power Spectral Densities of the SAR image. The proposed model effectively accounts for the effect of finite sensor resolutions and for the peculiarity of SAR acquisition geometry. Moreover, it is shown how the inversion of this direct model allows us to retrieve the fractal dimension of the observed surface. Significant experimental results, validating the theoretical conclusions, are also shown.
POWER BUDGET ANALYSIS OF REFLECTED GPS L1 AND L5 FREQUENCY SIGNALS FOR PASSIVE MICROWAVE IMAGING

The GPS signals are commonly used for navigation purposes. Another utilization of reflected GPS signals is for remote sensing. This paper focuses on the power budget analysis of bi-static radar using GPS satellite as a "transmitter of opportunity". In this application the direct and reflected GPS signals are acquired using customized hardware, where the receiver can be mounted on an airborne platform or remain static. GPS satellites currently transmit L1 frequency signals with C/A codes used as a ranging signal, but plans for transmitting additional L5 frequency signals as part of GPS modernization efforts are underway. Here we present the simulated results for power budget analysis of both GPS L1 and L5 frequency signals. The Signal to Noise Ratio (SNR) for different ranges is calculated and results have been plotted. It can be deduced that SNR of GPS L5 reflected signal is higher as compared to GPS L1 signal for similar target ranges and therefore, these signals are more suitable for remote sensing applications as compared to GPS L1 signals. Simulation is carried out in MATLAB®.
Personalized Views for Immersive Analytics

In this paper we present work-in-progress toward a vision of personalized views of visual analytics interfaces in the context of collaborative analytics in immersive spaces. In particular, we are interested in the sense of immersion, responsiveness, and personalization afforded by gaze-based input. Through combining large screen visual analytics tools with eye-tracking, a collaborative visual analytics system can become egocentric while not disrupting the collaborative nature of the experience. We present a prototype system and several ideas for real-time personalization of views in visual analytics.
Constrained Viterbi Algorithm and its Application in Error Resilient Transmission of SPIHT Coded Images

The Viterbi algorithm (VA) is well-known to be an optimum decoding method for channels with random error patterns. But the decoding complexity grows greatly while the memory size increases and it doesn't work while burst errors occurs. Constrained Viterbi algorithm (C-VA) was proposed in a novel product code scheme (Lei Cao and Chang Wen Chen, 2003) to overcome those drawbacks. The main idea of C-VA is to make full use of those bits known to be decoded correctly first. It has been proved in Lei Cao and Chang Wen Chen (2003) that once reliable constraint conditions can be given, the C-VA works well in normal image transmission. In this paper, a new scheme is proposed for error resilient transmission of set partitioning in hierarchical trees (SPIHT) coded images by adding constraint condition directly and simply. Experiments show that the C-VA is very useful under the extremely inferior channel conditions if the best quality of reconstructed images can be sacrificed.
Revealing What to Extract from Where, for Object-Centric Content Based Image Retrieval (CBIR)

Content Based Image Retrieval (CBIR) techniques retrieve similar digital images from a large database. As the user often does not provide any clue (indication) of the region of interest in a query image, most methods of CBIR rely on a representation of the global content of the image. The desired content in an image is often localized (e.g. car appearing salient in a street) instead of being holistic, demanding the need for an object-centric CBIR. We propose a biologically inspired framework WOW ("What" Object is "Where") for this purpose. Design of WOW framework is motivated by the cognitive model of human visual perception and feature integration theory (FIT). The key contributions in the proposed approach are: (i) Feedback mechanism between Recognition ("What") and Localization ("Where") modules (both supervised), for a cohesive decision based on mutual consensus; (ii) Hierarchy of visual features (based on FIT) for an efficient recognition task. Integration of information from the two channels ("What" and "Where") in an iterative feedback mechanism, helps to filter erroneous contents in the outputs of individual modules. Finally, using a similarity criteria based on HOG features (spatially localized by WOW) for matching, our system effectively retrieves a set of rank-ordered samples from the gallery. Experimentation done on various real-life datasets (including PASCAL) exhibits the superior performance of the proposed method.
Audio data classification by means of new algorithms

This paper describes classification of sound recordings based on their audio features. This is useful for querying large datasets, searching for recordings with some desired content. We use musical recordings as well as birdsongs recordings, which usually have rich structure and contain a lot of patterns suitable for classification. We present two different classification methods, one for musical recordings and one for birdsongs. These methods are compared and their differences are discussed. We use feature vectors that capture the audio content of recording as a whole piece and then classify these feature vectors using combination of the Self-organizing map and the Learning Vector Quantization, which represent a powerful algorithm using unlabeled as well as labeled data. In case of birdsongs we use feature vectors representing time frames of a recording.
Bridging the Gap between Real and Simulated Environments: A Hybrid Agent-Based Smart Home Simulator Architecture for Complex Systems

Deployment, maintenance of Smart Homes, Smart Grids in real environments is an expensive, lengthy process. In this paradigm, simulations play an important role by providing means of emulating the behaviour of the aforementioned systems. However, these simulations may suffer from lack of accuracy due to the inability to properly reproduce the operation of complex technologies such as solar panels, Heating, Ventilating, Air Conditioning systems (HVAC), sewerage networks or water provisioning. Within this context, this paper presents a Smart-Home Simulation architecture that is able to carry out more representational simulations by merging agent-based simulation of human behaviour with real-world modelling capabilities such as those provided by the Simulink software. Based on the simulation of human behaviour, water, electricity consumption profiles are generated, sent to Simulink models using the TCP/IP communication protocol. The obtained results show that a synchronized connection of both platforms in feasible, enabling a more accurate representation of the systems involved.
Eye specular highlights telltales for digital forensics: A machine learning approach

Among the possible forms of photographic fabrication and manipulation, there is an increasing number of composite pictures containing people. With such compositions, it is very common to see politicians depicted side-by-side with criminals during election campaigns, or even Hollywood superstars relationships being wrecked by allegedly affairs depicted in gossip magazines. Thinking about this problem, in this paper we analyze telltales obtained from highlights in the eyes of every person standing in a picture in order to decide whether or not those people were really together at the moment of such image acquisition. We validate our approach with a data set containing realistic photographic compositions, as well as authentic unchanged pictures. As a result, our proposed extension improves the classification accuracy of the state-of-art solution in more than 20%.
Optimization of GEO Satellite Links Deployment in the Internet

As the satellite technology will be one of the main components of the Next Generation Internet (NGI), a naturally occurring question concerns the feasibility of providing an optimal satellite-based Internet access. In this paper, we are interested in GEO satellite links deployment in the Internet by addressing the problem of terrestrial-satellite hybrid network optimization for which we propose a general architecture. We devide the general optimization problem into several sub-problems which can be resolved separately. Each sub-problem treats a specific type of traffic and it is defined by a set of inputs, variables, goals, and constraints. The global GEO satellite links deployment optimization heuristic that we propose attempts to determine the optimal hybrid topology which minimizes performance metrics such as delay, throughput, call blocking probabilities, and network cost. Two main steps compose the proposed heuristic: performance evaluation step and satellite uplink position finding step. During the first step we try to determine values of performance metrics of studied traffic and in the second one, we look for the optimal position where to add the current satellite uplink in order to optimize performance criteria. We present in details a case study dealing with multicast traffic optimization during the deployment of GEO satellite links in the Internet. We develop a configuration policy of PIM-SM in hybrid networks concerning the choice of the list of Rendezvous Point (RPs) and the switching from the RP-routed tree to the shortest path tree. This policy provides an optimal use of satellite links for multicast transfer. The obtained results demonstrate the ability of the proposed optimization method to improve multicast performan- ce criteria and to determine effectively satellite uplinks positions using PIM-SM combined with UDLR (UniDirectional Link Routing).
Update on the pathogenesis of Scleroderma: focus on circulating progenitor cells

In systemic sclerosis (SSc), the development of fibrosis seems to be a consequence of the initial ischemic process related to an endothelial injury. The initial trigger event in SSc is still unknown, but circulating progenitor cells (CPCs) might play a key role. Such cells have the ability to traffic into injury sites, exhibiting inflammatory features of macrophages, tissue remodeling properties of fibroblasts, and vasculogenesis functions of endothelial cells. The different subsets of CPCs described thus far in SSc arise from a pool of circulating monocyte precursors (CD14 + cells) and probably correspond to a different degree of differentiation of a single cell of origin. Several subsets of CPCs have been described in patients with SSc, all have a monocytic origin but may or may not express CD14, and all of these cells have the ability to give origin to endothelial cells, or collagen (Col)-producing cells, or both. We were able to identify six subsets of CPCs: pluripotent stem cells (CD14 +, CD45 +, and CD34 +), monocyte-derived multipotential cells (MOMCs) or monocyte-derived mesenchymal progenitors (CD14 +, CD45 +, CD34 +, Col I +, CD11b +, CD68 +, CD105 +, and VEGFR1 +), early endothelial progenitor cells (EPCs) or monocytic pro-angiogenic hematopoietic cells or circulating hematopoietic cells (CD14 +, CD45 +, CD34 low/−, VEGFR2 +/−, CXCR4 +, c-kit +, and DC117 +), late EPCs (CD14 −, CD133 +, VEGFR2 +, CD144 + [VE-cadherin +], and CD146 +), fibroblast-like cells (FLCs)/circulating Col-producing monocytes (CD14 +, CD45 +, CD34 +/−, and Col I +), and fibrocytes (CD14 −, CD45 +, CD34 +, Col I +, and CXCR4 +). It has been demonstrated that circulating CD14 + monocytes with an activated phenotype are increased in patients with SSc when compared with normal subjects. CD14 +, CD34 +, and Col I + spindle-shaped cells have been found in increased numbers in lungs of SSc patients with interstitial lung disease. Elevated blood amounts of early EPCs have been found in patients with SSc by different groups of researchers and such levels correlate directly with the interstitial lung involvement. The prevalence of hematopoietic markers expressed by CPCs that migrate from blood into injury sites in SSc differs and changes according to the degree of differentiation. CXCR4 is the most commonly expressed marker, followed by CD34 and CD45 at an end stage of differentiation. Such difference also indicates a continuous process of cell differentiation that might relate to the SSc clinical phenotype (degree of fibrosis and vascular involvement). A deeper understanding of the role of each subtype of CPCs in the development of the disease will help us to better classify patients in order to offer them targeted approaches in the future.
Complete atrioventricular nodal block after propofol administration in an elderly patient undergoing total knee replacement arthroplasty -A case report-

Complete atrioventricular (AV) block is defined as a dissociation of atrial and ventricular activities. Complete AV block that occurs during the perioperative period is difficult to reverse and usually requires implantation of a pacemaker. Propofol does not affect a normal AV conduction system but may act as a trigger for AV block. It can also potentiate vagal stimulation factors and reduce sympathetic activity. We report a case of complete AV block that may have been related to administration of propofol.
The Network-Firm as a Single Real Entity: Beyond the Aggregate of Distinct Legal Entities

This conceptual paper starts with a question regarding the nature of the firm: is the firm a nexus of contracts or a real entity? To answer this question, the article departs from a critique of firm contract theory that usually focuses on moral personification to propose some theoretical foundations of the firm as a real entity. This provides crucial insights for the analysis of modern complex organizations. Then, this paper applies the real entity paradigm to the case of the network firm: is the network firm merely a collection of distinct legal entities or a single real entity? The integrating and unifying role of intra-network power relationships is emphasized, and some legal and economic aspects of the network firm are discussed to clarify the argument that the network firm is a singular real entity composed from distinct legal entities. Considering the network firm as a single real entity has strong policy implications in terms of employment protection rights and politico-legal responsibilities.
Learning shape metrics based on deformations and transport

Shape evolutions, as well as shape matchings or image segmentation with shape prior, involve the preliminary choice of a suitable metric in the space of shapes. Instead of choosing a particular one, we propose a framework to learn shape metrics from a set of examples of shapes, designed to be able to handle sparse sets of highly varying shapes, since typical shape datasets, like human silhouettes, are intrinsically high-dimensional and non-dense. We formulate the task of finding the optimal metrics on an empirical manifold of shapes as a classical minimization problem ensuring smoothness, and compute its global optimum fast. First, we design a criterion to compute point-to-point matching between shapes which deals with topological changes. Then, given a training set of shapes, we use these matchings to transport deformations observed on any shape to any other one. Finally, we estimate the metric in the tangent space of any shape, based on transported deformations, weighted by their reliability. Experiments on difficult sets are shown, and applications are proposed.
Probability Fluxes and Transition Paths in a Markovian Model Describing Complex Subunit Cooperativity in HCN2 Channels

Hyperpolarization-activated cyclic nucleotide-modulated (HCN) channels are voltage-gated tetrameric cation channels that generate electrical rhythmicity in neurons and cardiomyocytes. Activation can be enhanced by the binding of adenosine-3′,5′-cyclic monophosphate (cAMP) to an intracellular cyclic nucleotide binding domain. Based on previously determined rate constants for a complex Markovian model describing the gating of homotetrameric HCN2 channels, we analyzed probability fluxes within this model, including unidirectional probability fluxes and the probability flux along transition paths. The time-dependent probability fluxes quantify the contributions of all 13 transitions of the model to channel activation. The binding of the first, third and fourth ligand evoked robust channel opening whereas the binding of the second ligand obstructed channel opening similar to the empty channel. Analysis of the net probability fluxes in terms of the transition path theory revealed pronounced hysteresis for channel activation and deactivation. These results provide quantitative insight into the complex interaction of the four structurally equal subunits, leading to non-equality in their function.
Simulink library for simulation of the permanent magnets synchronous machine drive

Reliability of electromechanical actuation systems as those used in aerospace applications may be improved by a proper choice of the motor, of its control strategy and of the architecture of the power electronics feeding the motor. This paper presents a Simulink library for the simulation of the motor and of its control electronics allowing to choose between three types of motor and between two types of vector control. The models allow the simulation of different fault conditions in order to identify the weak and strong points of each architecture. The research reported in this paper was performed within the European Union FP6 project DRESS (distributed and redundant electromechanical nose gear steering system) for more electrical aircraft (http://www.dress-project.eu).