Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrative Neuroscience Review Article Visualizing the Blind Brain: Brain Imaging of Visual Field Defects from Early Recovery to Rehabilitation Techniques

Visual field defects (VFDs) are one of the most common consequences observed after brain injury, especially after a stroke in the posterior cerebral artery territory. Less frequently, tumors, traumatic brain injury, brain surgery or demyelination can also determine various visual disabilities, from a decrease in visual acuity to cerebral blindness. Visual field defects is a factor of bad functional prognosis as it compromises many daily life activities (e.g., obstacle avoidance, driving, and reading) and therefore the patient's quality of life. Spontaneous recovery seems to be limited and restricted to the first 6 months, with the best chance of improvement at 1 month. The possible mechanisms at work could be partly due to cortical reorganization in the visual areas (plasticity) and/or partly to the use of intact alternative visual routes, first identified in animal studies and possibly underlying the phenomenon of blindsight. Despite processes of early recovery, which is rarely complete, and learning of compensatory strategies, the patient's autonomy may still be compromised at more chronic stages. Therefore, various rehabilitation therapies based on neuroanatomical knowledge have been developed to improve VFDs. These use eye-movement training techniques (e.g. to show brain activations in the course of spontaneous recovery or after specific rehabilitation techniques.
A pr 2 00 8 Sparse Approximate Solution of Partial Differential Equations ∗

A new concept is introduced for the adaptive finite element discretization of partial differential equations that have a sparsely representable solution. Motivated by recent work on compressed sensing, a recursive mesh refinement procedure is presented that uses linear programming to find a good approximation to the sparse solution on a given refinement level. Then only those parts of the mesh are refined that belong to nonzero expansion coefficients. Error estimates for this procedure are refined and the behavior of the procedure is demonstrated via some simple elliptic model problems.
New method for solving partial and ordinary differential equations using finite-element technique

In this paper I introduce a new method for solving partial and ordinary differential equations with large first, second, and third derivatives of the solution in some part of the domain using the finite-element technique (here called the Galerkin-Gokhman method) The method is based on the application of the Galerkin method to a modified differential equation. The exact solution of the modified equation is the Galerkin approximation for the unknown function with exact values of the unknown at the nodal points. An application of the Galerkin-Gokhman method to a general second-order nonlinear ordinary differential equation and to Navier-Stokes equations in the case of developing flow in a pipe is formulated. I also include the results of an application of the Galerkin-Gokhman method to two specific ordinary differential equations. One is y — dy/dx = 0, the other one is a second-order nonlinear equation describing fully developed turbulent flow in a pipe.
Greedy dirty models: A new algorithm for multiple sparse regression

This paper considers the recovery of multiple sparse vectors, with partially shared supports, from a small number of noisy linear measurements of each. It has recently been shown that it is possible to lower the sample complexity of recovery, for all levels of support sharing, by using a “dirty model”: a super-position of sparse and group-sparse modeling approaches; this is based on convex optimization. In this paper, we provide a new forward-backward greedy procedure for the dirty model approach. Each forward step involves the addition of either a shared feature common to all vectors, or a unique feature to one of the vectors, chosen in a natural greedy fashion. Each backward step involves greedy removal, again of at most one feature of either type. Analytical and empirical evidence shows that this outperforms all convex approaches, in terms of both sample and computational complexity.
On Recommending Newly Published Academic Papers

To recommend newly-published papers that did not receive any citations yet, this paper proposes a novel method by using the authors' interest on the papers cited in the newly-published paper. Compared to citation-network based methods, the empirical validation shows a significant improvement with our method in accuracy of 11%-41% in precision and 8%-34% in recall.
ProcDef: Local‐to‐global Deformation for Skeleton‐free Character Animation

Animations of characters with flexible bodies such as jellyfish, snails, and, hearts are difficult to design using traditional skeleton‐based approaches. A standard approach is keyframing, but adjusting the shape of the flexible body for each key frame is tedious. In addition, the character cannot dynamically adjust its motion to respond to the environment or user input. This paper introduces a new procedural deformation framework (ProcDef) for designing and driving animations of such flexible objects. Our approach is to synthesize global motions procedurally by integrating local deformations. ProcDef provides an efficient design scheme for local deformation patterns; the user can control the orientation and magnitude of local deformations as well as the propagation of deformation signals by specifying line charts and volumetric fields. We also present a fast and robust deformation algorithm based on shape‐matching dynamics and show some example animations to illustrate the feasibility of our framework.
New rehabilitation models for neurologic inpatients in Brazil

Abstract Purpose: To describe the effects of a rehabilitation program in a neurological inpatient unit in terms of independence for activities of daily living and return to work. Method: Retrospective study with 148 adults with stroke, traumatic brain injury (TBI), spinal cord injury, and Guillain–Barré syndrome admitted as rehabilitation inpatients within a 1-year period for hospitalization at the Instituto de Reabilitação Lucy Montoro, Brazil. According to their diagnostic groups, subjects undergone semi-standardized models of intensive multidisciplinary rehabilitation for 4–6 weeks. Primary outcome measures: Functional Independence Measure (FIM™), Modified Rankin scale (Rankin), and Glasgow Outcome Scale (GOS Subjects were evaluated at admission, discharge, and 6 months after discharge. Results: Improvement in motor FIM™, Rankin and GOS was observed in all groups. Cognitive FIM™ increase was less evident in TBI patients. After 6 months, 37.6% of patients were unemployed, 34% underwent outpatient rehabilitation, and 65.2% maintained gains. Conclusions: This is the first report on the effects from an inpatients rehabilitation model in Brazil. After a short intensive rehabilitation, there were motor and cognitive gains in all groups. Heterogeneity in functional gains suggests more individualized programs may be indicated. Controlled studies are required with larger samples to compare inpatient and outpatient programs. Implications for Rehabilitation The proposed brief model of rehabilitation for stroke, traumatic brain injury, spinal cord injury, and Guillain–Barre syndrome inpatients shows promising results in terms of functional improvement. Apparent improvements in cognitive and motor levels can be observed after 30 d of the intensive hospital-based program five times a week focusing on caregiver and patients training. After 6 months of discharge, more than one third of patients remained out of work, but appeared to have kept the benefits attained during hospitalization, and performed physical activities in the community as outpatients.
High Performance Multi-Partition Transactions

This PhD project addresses high throughput multi-partition, multi-get/put transactions, a.k. a. read-only/write-only transactions, in distributed storage systems providing strong consistency, specifically serializability, on various workload changes. Current systems either sacrifice performance for concurrency control, or trade consistency for performance. The project takes a new angle on the problem by proposing an epochbased concurrency control mechanism, which separates read operations and write operations into different time slices, referred as epochs, to minimize conflicts among transactions. This mechanism also supports self-adaptation as workload characteristics change using the epoch duration as a tuning parameter. Using this epoch-based concurrency control protocol, our preliminary experiments achieve 1.5 million get/put operations per second per hosts on six server hosts. Our multi-get/put transactions are atomic and serializable.
Barcode detection with uniform partitioning and distance transformation

Barcode detection is required in a wide range of real-life applications. Imaging conditions and techniques vary considerably and each application has its own requirements for detection speed and accuracy. In our earlier works we used uniform partitioning with several approaches for detection of various types of 1D and 2D barcodes and showed their behaviour on a set of test images. In this work, we extend the partitioning idea and replace scan-line based methods with distance transformation to improve accuracy.
Iterative detection/decoding of majority-logic decodable nonbinary LDPC codes over partial response channels

This paper is concerned with the applications of majority-logic decodable nonbinary low-density parity-check (LDPC) codes to partial response (PR) channels. We propose a joint detection/decoding algorithm that works in an iterative manner by exchanging messages between the Viterbi detector and a generalized majority logic decoder (GMLGD). The Viterbi detector is implemented over a sectionalized trellis. The hard-decisions made by the Viterbi detector are then passed to the decoder. The decoder delivers as output estimates of each coded symbols, which will be utilized in next iteration to update the branch metrics of the trellis. Since the proposed algorithm requires only integer operations and finite field operations, it can be implemented with simple combinational logic circuits. Simulation results and complexity analysis show that, when compared with the conventional turbo equalizer implemented with the BCJR algorithm and the Q-ary sum-product algorithm (BCJR-QSPA), the proposed algorithm has a much lower complexity but suffers from a little performance degradation. So the proposed algorithm provides a good candidate for trade-offs between performance and complexity.
Proceedings of The Eleventh Research Symposium on Emerging Electronic Markets (RSEEM 2004) Relationships in Electronic Markets

The paper presents and applies the methodology and techniques of cross case analysis (CCA). The authors identify patterns of success in the field of e-shops and virtual relationships. The findings are based on six selected case studies following the methodology developed by Eisenhardt [1989]. The case study approach was used for two reasons: First, a large number of case studies was collected over the last years containing knowledge that had not yet been analysed and interpreted. Second, the authors assume that the research field of e-business and ICT is particularly suited for cross case analysis because of the dynamic development and the need to learn from best practice [Klein/Myers 1999]. 1 Objectives and Motivation The superior purpose of this paper is to identify a suitable way for cross case analysis. We are following the approach proposed by Eisenhardt [1989]. The case studies were taken from the eXperience case study database [eXperience 2004]. eXperience is a publicly funded project that let to a platform which currently holds about 240 fully qualified case studies about e-business best practice and is intended for research and practitioners alike. In this database, all case studies are classified according to a common categorization scheme. Since some of the case studies are incomplete for the purpose of a thorough analysis and comparison, a framework for a down-toearth approach had to be found. This paper presents the first steps towards this objective. The authors selected six case studies for a first field trial in order to find patterns linked to virtual relationships and multi channel strategies that show significant correlations with the success or failure of e-shops. The motivation for choosing a case study based approach was (1) to test the Eisenhardt methodology and to apply it to the special domain of e-business and (2) to gain general experiences in the field of cross case analysis (CCA). 2 Cross Case Analysis
STaR: a Social Tag Recommender System

The continuous growth of collaborative platforms we are recently witnessing made possible the passage from an 'elitary' Web, written by few and read by many, towards the so-called Web 2.0, a more 'user-centric' vision, where users become active contributors in Web dynamics. In this context, collaborative tagging systems are rapidly emerging: in these platforms users can annotate resources they like with freely chosen keyword (called tags) in order to make retrieval of information and serendipitous browsing more and more easier. However, as tags are handled in a simply syntactical way, collaborative tagging systems suffer of typical Information Retrieval (IR) problems like polysemy and synonymy: so, in order to reduce the impact of these drawbacks and to aid at the same time the so-called tag convergence, systems that assist the user in the task of tagging are required. The goal of these systems (called tag recommenders) is to suggest a set of relevant keywords for the resources to be annotated by exploiting different approaches. In this paper we present a tag recommender developed for the ECML-PKDD 2009 Discovery Challenge. Our approach is based on two assumptions: firstly, if two or more resources share some common patterns (e.g. the same features in the textual description), we can exploit this information supposing that they could be annotated with similar tags. Furthermore, since each user has a typical manner to label resources, a tag recommender might exploit this information to weigh more the tags she already used to annotate similar resources.
Autoreactivity and Exceptional CDR Plasticity (but Not Unusual Polyspecificity) Hinder Elicitation of the Anti-HIV Antibody 4E10

The broadly-neutralizing anti-HIV antibody 4E10 recognizes an epitope in the membrane-proximal external region of the HIV envelope protein gp41. Previous attempts to elicit 4E10 by vaccination with envelope-derived or reverse-engineered immunogens have failed. It was presumed that the ontogeny of 4E10-equivalent responses was blocked by inherent autoreactivity and exceptional polyreactivity. We generated 4E10 heavy-chain knock-in mice, which displayed significant B cell dysregulation, consistent with recognition of autoantigen/s by 4E10 and the presumption that tolerance mechanisms may hinder the elicitation of 4E10 or 4E10-equivalent responses. Previously proposed candidate 4E10 autoantigens include the mitochondrial lipid cardiolipin and a nuclear splicing factor, 3B3. However, using carefully-controlled assays, 4E10 bound only weakly to cardiolipin-containing liposomes, but also bound negatively-charged, non-cardiolipin-containing liposomes comparably poorly. 4E10/liposome binding was predominantly mediated by electrostatic interactions rather than presumed hydrophobic interactions. The crystal structure of 4E10 free of bound ligands showed a dramatic restructuring of the combining site, occluding the HIV epitope binding site and revealing profound flexibility, but creating an electropositive pocket consistent with non-specific binding of phospholipid headgroups. These results strongly suggested that antigens other than cardiolipin mediate 4E10 autoreactivity. Using a synthetic peptide library spanning the human proteome, we determined that 4E10 displays limited and focused, but unexceptional, polyspecificity. We also identified a novel autoepitope shared by three ER-resident inositol trisphosphate receptors, validated through binding studies and immunohistochemistry. Tissue staining with 4E10 demonstrated reactivity consistent with the type 1 inositol trisphosphate receptor as the most likely candidate autoantigen, but is inconsistent with splicing factor 3B3. These results demonstrate that 4E10 recognition of liposomes competes with MPER recognition and that HIV antigen and autoepitope recognition may be distinct enough to permit eliciting 4E10-like antibodies, evading autoimmunity through directed engineering. However, 4E10 combining site flexibility, exceptional for a highly-matured antibody, may preclude eliciting 4E10 by conventional immunization strategies.
Empirical evaluation of image reconstruction techniques

Image reconstruction is the process of manipulating an image to increase the amount of information perceived by a human eye. In this paper most popular filtering techniques have taken for comparison, that are Non Local Mean method, Particle filtering and Markov random fields. The Original NL Mean method replaces a noisy pixel by the weighted average of pixels with related surrounding neighbourhoods. In order to accelerate the algorithm; the filters are used to eliminate unrelated neighborhoods from the weighted average. The particle filtering technique will give statistical behavior of the image. The most appropriate window or neighborhood shape and size to estimate the image intensity in a given position. One attempt is to do perform filtering by selecting the neighboring pixels in a random fashion but without taking image structure into account. MRFs can be used as parametric models for the probability distribution of intensity levels in an image. The resulting framework explores optimally spatial dependencies between image content towards variable bandwidth image reconstruction. The results of techniques Non Local Mean method, Particle Filters and Markov random fields are compared by using two parameters such as PSNR and MSE values for the reconstructed images.Markov Random Fields method provides a better result when compare to Nonlocal mean method and Particle Filter.
A vortex-based subgrid stress model for large-eddy simulation

A class of subgrid stress (SGS) models for large-eddy simulation (LES) is presented based on the idea of structure-based Reynolds-stress closure. The subgrid structure of the turbulence is assumed to consist of stretched vortices whose orientations are determined by the resolved velocity field. An equation which relates the subgrid stress to the structure orientation and the subgrid kinetic energy, together with an assumed Kolmogorov energy spectrum for the subgrid vortices, gives a closed coupling of the SGS model dynamics to the filtered Navier-Stokes equations for the resolved flow quantities. The subgrid energy is calculated directly by use of a local balance between the total dissipation and the sum of the resolved-scale dissipation and production by the resolved scales. Simple one- and two-vortex models are proposed and tested in which the subgrid vortex orientations are either fixed by the local resolved velocity gradients, or rotate in response to the evolution of the gradient field. These models are not of the eddy viscosity type. LES calculations with the present models are described for 32^(3) decaying turbulence and also for forced 32^(3) box turbulence at Taylor Reynolds numbers R-lambda in the range R(lambda)similar or equal to 30 (fully resolved) to R-lambda=infinity. The models give good agreement with experiment for decaying turbulence and produce negligible SGS dissipation for forced turbulence in the limit of fully resolved flow.
Effects of Wrist Posture and Fingertip Force on Median Nerve Blood Flow Velocity

Purpose. The purpose of this study was to assess nerve hypervascularization using high resolution ultrasonography to determine the effects of wrist posture and fingertip force on median nerve blood flow at the wrist in healthy participants and those experiencing carpal tunnel syndrome (CTS) symptoms. Methods. The median nerves of nine healthy participants and nine participants experiencing symptoms of CTS were evaluated using optimized ultrasonography in five wrist postures with and without a middle digit fingertip press (0, 6 N). Results. Both wrist posture and fingertip force had significant main effects on mean peak blood flow velocity. Blood flow velocity with a neutral wrist (2.87 cm/s) was significantly lower than flexed 30° (3.37 cm/s), flexed 15° (3.27 cm/s), and extended 30° (3.29 cm/s). Similarly, median nerve blood flow velocity was lower without force (2.81 cm/s) than with force (3.56 cm/s). A significant difference was not found between groups. Discussion. Vascular changes associated with CTS may be acutely induced by nonneutral wrist postures and fingertip force. This study represents an early evaluation of intraneural blood flow as a measure of nerve hypervascularization in response to occupational risk factors and advances our understanding of the vascular phenomena associated with peripheral nerve compression.
Determinants of Object Persistence: The Role of Cue Type, Cue Duration and Cue Strength

Four experiments investigated object persistence in conscious awareness as a function of the nature of the cues that permit the object to be segregated from the background, and identified. A number of factors were manipulated (cue type, [color, motion, color & motion] cue duration after object identification [1s vs 5s] and cue strength [strong vs weak]). Performance was fractionated into identification, maintenance and persistence components. The results show that (1) stronger cues yielded faster identification, and (2) persistence was independent of identification time, and (3) motion cues were associated with longer persistence than color cues. A distinction between dorsal and ventral visual pathways as used to segregate the object from the background provides one way to organize the data.
Unsupervised statistical sketching for non-photorealistic rendering models

This paper investigates the use of the Bayesian inference for devising an unsupervised sketch rendering procedure. As likelihood model of this inference, we exploit the recent statistical model of the gradient vector field distribution proposed by Destrempes et al. for contour detection. A global prior deformation model for each pencil stroke is also considered. In this Bayesian framework, the placement of each stroke is viewed as the search of the maximum a posteriori estimation of the posterior distribution of its deformations. We use a stochastic optimization algorithm in order to find these optimal deformations. This yields an unsupervised method to create realistic hand-sketched pencil drawings. Combined with an example-based local rendering model, used to transfer the textural tone value of a given depiction style, the proposed scheme allows to simulate automatic synthesis of various artistic illustration styles.