Miracle-dz/UniFAR-FTUs huggingface dataset:
Working Memory Network Changes in ALS: An fMRI Study

We used amyotrophic lateral sclerosis (ALS) as a model of prefrontal dysfunction in order to re-assess the potential neuronal substrates of two sub processes of working memory, namely information storage and filtering. To date it is unclear which exact neuronal networks sustain these two processes and the prefrontal cortex was suggested to play a crucial role both for filtering out of irrelevant information and for the storage of relevant information in memory. Other research has attributed information storage to more posterior brain regions, including the parietal cortex and stressed the role of subcortical areas in information filtering. We studied 14 patients suffering from ALS and the same number of healthy controls in an fMRI-task that allowed calculating separate storage and filtering scores. A brain volume analysis confirmed prefrontal atrophy in the patient group. Regarding their performance in the working memory task, we observed a trend toward slightly impaired storage capabilities whereas filtering appeared completely intact. Despite the rather subtle behavioral deficits we observed marked changes in neuronal activity associated with ALS: Compared to healthy controls patients showed significantly reduced hemodynamic responses in the left occipital cortex and right prefrontal cortex in the storage contrast. The filter contrast on the other hand revealed a relative hyperactivation in the superior frontal gyrus of the ALS patients. This hyperactivation might reflect a possible compensational mechanism for the prefrontal degeneration found in ALS. The reduced hemodynamic responses in the storage contrast might reflect a disruption of prefrontal top-down control of posterior brain regions, a process which was especially relevant in the most difficult high load memory task. Taken together, the present study demonstrates marked neurophysiological changes in ALS patients compared to healthy controls during the filtering and storage of information in spite of largely intact behavior. With respect to the neuronal substrates of the two working memory processes under investigation here, the results suggest that it is rather the degree to which top-down control is required for task completion that determines prefrontal cortex involvement than the specific nature of the process, i.e., storage vs. filtering.
Quantitative evaluation of hand functions using a wearable hand exoskeleton system

To investigate, improve, and observe the effect of rehabilitation therapy, many studies have been conducted on evaluating the motor function quantitatively by developing various types of robotic systems. Even though the robotic systems have been developed, functional evaluation of the hand has been rarely investigated, because it is difficult to install a number of actuators or sensors to the hand due to limited space around the fingers. Therefore, in this study, a hand exoskeleton was developed to satisfy the required specifications for evaluating the hand functions including spasticity of finger flexors, finger independence, and multi-digit synergy and algorithms to evaluate such functions were proposed. The hand exoskeleton was composed with the four 4-bar linkages, two motors, and three loadcells for each finger, and it was able to flex/extend the metacarpal (MCP) and proximal interphalangeal(PIP) joints independently while measuring the pulling force at each phalanx. Using the hand exoskeleton, the hand functions of the three healthy subject were evaluated and the experimental results were analyzed.
Refractive Index Patterns in Silicon Inverted Colloidal Photonic Crystals

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A critical-conduction-mode bridgeless interleaved boost power factor correction: Its control scheme based on commonly available controller

This paper describes about how to utilize the industry standard critical conduction mode (CRM) boost interleaved power factor correction (PFC) control IC in a bridgeless environment. The proposed control technique is based on control signal diversion. It makes the bridgeless CRM boost interleaved PFC control signal looks like a conventional bridged-CRM boost interleaved PFC to the control IC. The presented solution has proven for its simplicity and its feasibility. In this paper, the control theory, considerations, and experiment data will be thoroughly presented.
What does the eye tell the brain?: Development of a system for the large scale recording of retinal output activity

A multielectrode array system has been developed to study how the retina processes and encodes visual images. This system can simultaneously record the extracellular electrical activity from hundreds of retinal output neurons as a dynamic visual image is focused on the input neurons. The retinal output signals detected can be correlated with the visual input to study the neural code used by the eye to send information about the visual world to the brain. The system consists of the following components: (1) a 32 /spl times/ 16 rectangular array of 512 planar microelectrodes with a sensitive area of 1.7 square mm. The electrode spacing is 60 microns and the electrode diameter is 5 microns. (Hexagonal arrays with 519 electrodes are under development); (2) eight 64-channel custom-designed integrated circuits to platinize the electrodes and AC couple the signals; (3) eight 64-channel integrated circuits to amplify, band-pass filter and analog multiplex the signals; (4) a data acquisition system; and (5) data processing software. This paper will describe the design of the system, the experimental and data analysis techniques, and some first results with live retina. The system is based on techniques and expertise acquired in the development of silicon microstrip detectors for high energy physics experiments.
View-Based Collective I/O for MPI-IO

This paper presents the design and implementation of a new file system independent collective I/O optimization based on file views: view-based collective I/O. View-based collective I/O has been implemented and evaluated inside ROMIO implementation of MPI-IO standard. The evaluation section shows that view-based I/O outperforms the original two-phase collective I/O from ROMIO in most of the cases for three well-known parallel I/O benchmarks. This is especially due to a smaller cost of scatter/gather operations, a reduction of the metadata overhead, and a smaller number of collective communication and synchronization primitives used in the implementation.
Properties of advanced semiconductor materials : GaN, AlN, InN, BN, SiC, SiGe

Contributors. Preface. Gallium Nitride (GaN) (V. Bougrov, et al.). Aluminum Nitride (AIN) (Y. Goldberg). Indium Nitride (InN) (A. Zubrilov). Boron Nitride (BN) (S. Rumyantsev, et al.). Silicon Carbide (SiC) (Y. Goldberg, et al.). Silicon-Germanium (Si-1-xGe-x) (F. Schaffler). Appendix 1: Basic Physical Constants. Appendix 2: Periodic Table of the Elements. Appendix 3: Rectangular Coordinates for Hexagonal Crystal. Appendix 4: The First Brillouin Zone for Wurtzite Crystal. Appendix 5: Zinc Blende Structure. Appendix 6: The First Brillouin Zone for Zinc Blende Crystal. Additional References.
Mining Hierarchies of Correlation Clusters

The detection of correlations between different features in high dimensional data sets is a very important data mining task. These correlations can be arbitrarily complex: one or more features might be correlated with several other features, and both noise features as well as the actual dependencies may be different for different clusters. Therefore, each cluster contains points that are located on a common hyperplane of arbitrary dimensionality in the data space and thus generates a separate, arbitrarily oriented subspace of the original data space. The few recently proposed algorithms designed to uncover these correlation clusters have several disadvantages. In particular, these methods cannot detect correlation clusters of different dimensionality which are nested into each other. The complete hierarchical structure of correlation clusters of varying dimensionality can only be detected by a hierarchical clustering approach. Therefore, we propose the algorithm HiCO (hierarchical correlation ordering), the first hierarchical approach to correlation clustering. The algorithm determines the cluster hierarchy, and visualizes it using correlation diagrams. Several comparative experiments using synthetic and real data sets show the performance and the effectivity of HiCO
Velocity-based variable thresholds for improving collision detection in manipulators

In absence of tactile and visual sensors, manipulators rely on dynamic modeling and force/torque sensors to detect collisions. Predicated upon the understanding that collision detection will be improved by removing the effects of torque sensor error and friction compensation error, we propose an approach to measure these undesired effects in external torque residual signals without resorting to remodeling of the robot. Compensation of these effects leads to the proposed velocity-based variable thresholds which are shown to detect collisions with better efficacy than uncompensated methods. Implementation of the proposed velocity-based variable thresholds on a torque sensor equipped robot validates our methodology.
User tools and languages for graph‐based Grid workflows

This article presents a graph‐based Grid workflow language that is based on the formalism of Petri nets and the corresponding workflow enactment machine, developed by the author within the Fraunhofer Resource Grid in Germany. The workflow enactment machine supports dynamic refinement of workflows during runtime and automatic mapping of abstract jobs onto concrete Grid resources, which are accessed by means of the Globus Toolkit. Copyright © 2005 John Wiley & Sons, Ltd.
A fast thermal aware placement with accurate thermal analysis based on Green function

In this paper, we propose a fast and accurate thermal aware analytical placer. Thermal model is constructed based on Green function with enhanced DCT to generate full chip temperature profile. Unlike other previous thermal aware placers, our thermal model is tightly integrated with a flat force directed placement. A thermal spreading force based on 2D Gaussian model is proposed to reduce maximum on-chip temperature with dynamic hot region size control, optimizing between total half-perimeter wirelength (HPWL) and on-chip temperature distribution. Our thermal model is evaluated by the most recent commercial tool and has an average deviation of 6.5% with 242× speed up. Our placer can reach the same quality compared to Capo and APlace2 with 2-3× speed up. Experiments are tested using ISPD 2005 benchmark with up to 2 million gate design. The results are further evaluated using GSRC Bookshelf Evaluator for total HPWL, and using ICEPAK for temperature distribution. To the best of our knowledge, this is the first thermal-aware placer using analytical thermal model and experimented on large scale design. It takes 6.5 hours to complete entire 2005 ISPD benchmark using our thermal aware placer.
Generative Adversarial Networks for Multimodal Representation Learning in Video Hyperlinking

Continuous multimodal representations suitable for multimodal information retrieval are usually obtained with methods that heavily rely on multimodal autoencoders. In video hyperlinking, a task that aims at retrieving video segments, the state of the art is a variation of two interlocked networks working in opposing directions. These systems provide good multimodal embeddings and are also capable of translating from one representation space to the other. Operating on representation spaces, these networks lack the ability to operate in the original spaces (text or image), which makes it difficult to visualize the crossmodal function, and do not generalize well to unseen data. Recently, generative adversarial networks have gained popularity and have been used for generating realistic synthetic data and for obtaining high-level, single-modal latent representation spaces. In this work, we evaluate the feasibility of using GANs to obtain multimodal representations. We show that GANs can be used for multimodal representation learning and that they provide multimodal representations that are superior to representations obtained with multimodal autoencoders. Additionally, we illustrate the ability of visualizing crossmodal translations that can provide human-interpretable insights on learned GAN-based video hyperlinking models.
STABILITY ANALYSIS OF SOLUTIONS TO AN OPTIMAL CONTROL PROBLEM ASSOCIATED WITH A GOURSAT-DARBOUX PROBLEM †

The question of the continuous dependence of solutions to an optimal control problem on data (the so-called stability analysis of solutions or well-posedness) is very important from the point of view of practical applications of theory. Indeed, if the problem is related to a physical phenomenon, its data can be considered only an arbitrarily close approximation to exact values. Consequently, if the solution does not depend continuously on the data, it is not actually determined.
Enabling Effective Personalized Learning: Determinants for Knowledge based Web Information Retrieval Systems

In the digitized World, information is entangled in a mesh of unstructured web. Finding and retrieving relevant web resources to suit the user’s information requirement is a challenge. Moreover, understanding and adapting to cater to different user information requirements is also an uphill task. To achieve the desired outcome, it is needed to have user accepted technology. Therefore, web information retrieval systems, especially search engines, should be user centered. Technology Acceptance Model (TAM) provides a basis with which one traces how external variables influence belief, attitude, and intention to use. Two cognitive beliefs are posited by TAM; perceived usefulness and perceived ease of use. This empirical study explores the influence of Users and Environment characteristics on a modern web information retrieval system. This paper analyzes the variables to determine perceptions of usefulness, attitude and preferences leading towards frequent factors to influence typical TAM results.
Development of Novel Bioactive PMMA-Based Bone Cement and its In Vitro and In Vivo Evaluation

In order to overcome the disadvantage of commercialized PMMA bone cement, we have developed novel PMMA-based bone cement(7P3S) reinforced by 30 wt. % of bioactive CaO-SiO2 gel powders to induce the bioactivity as well as to increase mechanical property for the PMMA bone cement. The novel 7P3S bone cement hardened after mixing for about 7 minutes. For in vitro evaluation, apatite forming ability of it was investigated using SBF. When the novel 7P3S bone cement was soaked into SBF, it formed apatite on its surfaces within 1 week Furthermore; there is no decrease in its compressive strength within 9 weeks soaking in SBF. It is though that hardly decrease in compressive strength of 7P3S bone cement in SBF is due to the relative small amount of gel powder or its spherical shape and monosize. In vivo evaluation of the novel 7P3S bone cement was carried out using rabbit. After implantion into rabbit tibia for several periods, the interface between novel bone cement and natural bone was evaluated by CT images. According to the results, the novel bone cement directly contact to the natural bone without fibrous tissue after implantation for 4 weeks. This results indicates that the newly developed 7P3S bone cement can bond to the living bone and also be effectively used as bioactive bone cement without decrease in mechanical property.
Use of the optical disector in canine mammary simple and complex carcinomas

Grading of canine mammary carcinomas (CMC) is associated to subjective assessments made by the pathologists. Due to its unbiased nature, stereology can be used to objectively quantify morphological parameters associated with grading and malignancy. However, the use of stereology in CMC has not been fully disclosed. The nuclear numerical density [NV (nuclei, tumor)] is a cellularity‐associated parameter that can be estimated by the optical disector. Herein, it was estimated in 44 CMC and its association with clinicopathologic factors – such as tumor size, histological subtype and grade, vascular/lymph node invasion, nuclear pleomorphism, and survival – was evaluated. Considering all the cases, the mean NV (nuclei, tumor) was 1.6 × 106 ± 0.5 × 106 nuclei/mm3. Lower values were attained in complex carcinomas, comparing to simple carcinomas, in tumors smaller than 5 cm, with low mitotic activity and in those with high nuclear pleomorphism. No statistically significant association with grade or vascular/lymph node invasion was observed, but tumors with disease progression had lower nuclear densities. The NV (nuclei, tumor) and the correlated parameters mirror to some extension those in human breast cancer, suggesting an interesting interspecies agreement. This first estimation of the nuclear numerical density in CMC highlights the feasibility of the optical disector and their utility for objective morphological assessments in CMC. The association between nuclear numerical density and disease progression warrants future studies.
A Benchmark Evaluation of Fault Tolerant Wind Turbine Control Concepts

As the world's power supply to a larger and larger degree depends on wind turbines, it is consequently and increasingly important that these are as reliable and available as possible. Modern fault tolerant control (FTC) could play a substantial part in increasing reliability of modern wind turbines. A benchmark model for wind turbine fault detection and isolation, and FTC has previously been proposed. Based on this benchmark, an international competition on wind turbine FTC was announced. In this brief, the top three solutions from that competition are presented and evaluated. The analysis shows that all three methods and, in particular, the winner of the competition shows potential for wind turbine FTC. In addition to showing good performance, the approach is based on a method, which is relevant for industrial usage. It is based on a virtual sensor and actuator strategy, in which the fault accommodation is handled in software sensor and actuator blocks. This means that the wind turbine controller can continue operation as in the fault free case. The other two evaluated solutions show some potential but probably need improvements before industrial applications.
Semi-supervised Domain Adaptation with Instance Constraints

Most successful object classification and detection methods rely on classifiers trained on large labeled datasets. However, for domains where labels are limited, simply borrowing labeled data from existing datasets can hurt performance, a phenomenon known as "dataset bias. " We propose a general framework for adapting classifiers from "borrowed" data to the target domain using a combination of available labeled and unlabeled examples. Specifically, we show that imposing smoothness constraints on the classifier scores over the unlabeled data can lead to improved adaptation results. Such constraints are often available in the form of instance correspondences, e.g. when the same object or individual is observed simultaneously from multiple views, or tracked between video frames. In these cases, the object labels are unknown but can be constrained to be the same or similar. We propose techniques that build on existing domain adaptation methods by explicitly modeling these relationships, and demonstrate empirically that they improve recognition accuracy in two scenarios, multicategory image classification and object detection in video.
Multiple wave scattering and calculated effective stiffness and wave properties in unidirectional fiber- reinforced composites

Analytic methods of elastic wave scattering in fiber-reinforced composite materials are investigated in this study to calculate the effective static stiffness (axial shear modulus, µ) and wave properties (axially shear wave speed, B and attenuation, Ψ) in composites. For simplicity only out-of-plane shear waves are modeled propagating in a plane transverse to the fiber axis. Statistical averaging of a spatially random distribution of fibers is performed and a simultaneous system of linear equations are obtained from which the effective global wave numbers are numerically calculated. The wave numbers, K=Re(K)+iIm(K), are complex numbers where the real parts are used to compute the effective axial shear static stiffness and wave speed; the imaginary parts are used to compute the effective axial shear wave attenuation in composites. Three major parts of this study are presented. The first part is the discussion of multiple scattering phenomena in a successive-events scattering approach. The successive-events scattering approach is proven to be mathematically exact by comparing the results obtained by the many-bodies-single-event approach. Scattering cross-section is computed and comparison of the first five scattering orders is made. Furthermore, the ubiquitous quasi-crystalline approximation theorem is given a justifiable foundation in the fiber-matrix composite context. The second part is to calculate µ, Β and Ψ for fiber-reinforced composites with interfacial layers between fibers and matrix. The material properties of the layers are assumed to be either linearly or exponentially distributed between the fibers and matrix. A concise formula is obtained where parameters can be computed using a computationally easy-to-program determinant of a square matrix. The numerical computations show, among other things, that the smoother (more divisional layers), or thinner, the interfacial region the less damped are the composite materials. Additionally composites with exponential order distribution of the interfacial region are more damped than the linear distribution ones. The third part is to calculate µ, Β and Ψ for fiber-reinforced composites with interfacial cracks. The procedures and computational techniques are similar to those in the second part except that the singularity near the crack tip needs the Chebychev function as a series expansion to be adopted in the computation. Both the interfacial layers and interfacial crack cases are analyzed in the low frequency range. The analytic results show that waves in both cases are attenuated and non-dispersive in the low frequency range. The composites with interfacial layers are transversely isotropic, while composites with interfacial cracks are generally transversely anisotropic.