Miracle-dz/UniFAR-FTUs huggingface dataset:
Endothelial cell diversity revealed by global expression profiling

The vascular system is locally specialized to accommodate widely varying blood flow and pressure and the distinct needs of individual tissues. The endothelial cells (ECs) that line the lumens of blood and lymphatic vessels play an integral role in the regional specialization of vascular structure and physiology. However, our understanding of EC diversity is limited. To explore EC specialization on a global scale, we used DNA microarrays to determine the expression profile of 53 cultured ECs. We found that ECs from different blood vessels and microvascular ECs from different tissues have distinct and characteristic gene expression profiles. Pervasive differences in gene expression patterns distinguish the ECs of large vessels from microvascular ECs. We identified groups of genes characteristic of arterial and venous endothelium. Hey2, the human homologue of the zebrafish gene gridlock, was selectively expressed in arterial ECs and induced the expression of several arterial-specific genes. Several genes critical in the establishment of left/right asymmetry were expressed preferentially in venous ECs, suggesting coordination between vascular differentiation and body plan development. Tissue-specific expression patterns in different tissue microvascular ECs suggest they are distinct differentiated cell types that play roles in the local physiology of their respective organs and tissues.
Measurement of Cardiac Output using Bioimpedance Method

Cardiac output (CO), in conjunction with hemoglobin concentration and arterial oxygen saturation are the cornerstones of oxygen transport. Cardiac output is the functional expression of cardiovascular performance and can be used to confirm the need for, or usefulness of treatment. Determination of cardiac output is an important procedure in interventional cardiology and also used in cardiothoracic surgery. Existing invasive cardiac output measurement methods are reasonably accurate, but their use is limited to the intensive care units. The risk of infection, blood loss or other complications associated with arterial catheters is also a matter of concern. Thus, a robust noninvasive alternative is considered to be desirable. Impedance cardiography (ICG) is one such method, which is noninvasive, easy to use, provides continuous CO measurement and has a better accuracy than the existing minimally invasive techniques. Traditionally, ICG involves applying a current field longitudinally across a segment of thorax by means of a constant magnitude, high frequency, and low amplitude alternating current. Most commonly implemented methods utilize the dependency of the peak systolic upslope of ΔZ(t) on the volumetric changes. However,change in the bioimpedance due velocity-induced blood resistivity variations has also been recently explored.This paper presents a detailed study of impedance cardiography as a tool for measuring the cardiac output and the issues related with it.
Effect of INS37217, a P2Y(2) receptor agonist, on experimental retinal detachment and electroretinogram in adult rabbits.

PURPOSE To evaluate the effects of subretinal and intravitreal delivery of INS37217, a P2Y(2) receptor agonist, on subretinal fluid reabsorption in experimentally induced retinal detachments in rabbits, and to characterize the effects of INS37217 on electroretinograms (ERG) in rabbits. METHODS A single retinal detachment was produced in New Zealand White rabbits by injecting approximately 50 micro L of modified phosphate-buffered saline (MPBS) solution into the subretinal space (SRS). In all experiments, one eye served as the INS37217-treated eye and the contralateral eye served as the vehicle control. In the first series of experiments, each rabbit received a SRS injection of MPBS solution, with or without INS37217 (1 mM). In the second series of experiments, each eye received an SRS injection of MPBS solution, followed by an intravitreal injection of MPBS solution, with or without INS37217 (12, 1.4, and 0.15 mM). A masked observer determined the size of blebs by indirect ophthalmoscopy at 30-minute intervals for up to 3 hours after SRS injections. Optical coherence tomography (OCT) was conducted to provide cross-sectional images of the blebs. Cellular expression of P2Y(2) receptor mRNA was localized by nonradioisotopic in situ hybridization in fresh rabbit retina-RPE tissue sections. Bilateral, full-field scotopic and photopic ERGs were made at 1, 7, and 14 days after a single intravitreal injection of 24 mM INS37217. RESULTS SRS administration of 1 mM INS37217 significantly enhanced subretinal fluid reabsorption when compared with vehicle controls (P < 0.05; repeated measures ANOVA). Intravitreal administration of INS37217 at 12 and 1.4 mM, but not at 0.15 mM, also significantly enhanced subretinal fluid reabsorption (P < 0.05). P2Y(2) receptor mRNA was observed throughout the RPE and in discrete layers of the retina. INS37217 had no adverse effects on scotopic and photopic ERG amplitude and latency parameters at any of the postadministration time points evaluated. CONCLUSIONS These results demonstrate that INS37217 enhances subretinal fluid reabsorption in experimental retinal detachment in rabbits and support the development of INS37217 for stimulating subretinal fluid reabsorption in conditions that result in retinal detachment or retinal edema.
FTV standardization in MPEG

FTV (Free-viewpoint TV) enables to view a 3D world by freely changing the viewpoint. MPEG has been developing FTV standards since 2001. MVC (Multiview Video Coding) was the first phase of FTV, which enabled the efficient coding of multiview video. View synthesis is not considered in MVC. 3DV (3D Video) is the second phase of FTV, which enables the efficient coding of multiview video and their depth maps for multiview displays. View synthesis between linearly arranged cameras is considered in 3DV. Based on recent development of 3D technology, MPEG started the third phase of FTV in August 2013, targeting super multiview and free navigation applications. They need more flexible camera arrangement, more efficient video coding and better view synthesis. The vision of this FTV standardization is to establish a new FTV framework that revolutionizes viewing of 3D scenes.
Locomotion Stabilization with Transition between Biped and Quadruped Walk based on Recognition of Slope

The applicative field of activities of robots who have only one locomotion strategy is limited. As means of enhancing the mobile range, it is necessary to have various locomotion modes. Therefore, we focus on dynamic transitions between several kinds of locomotion modes adapting to environmental changes. In this paper, we aim to realize stable locomotion along some unknown test courses consisting of flat and slope with transition between biped and quadruped walks. To achieve this transition, we propose a method to recognize a slope, a design of the transition motion, and a technique for modifying the trajectories of quadruped walk to move between flat and slope. By experiments, we verify that the proposed methods can successfully be applied to both upslope and downslope cases.
Phrasal Substitution of Idiomatic Expressions

Idioms pose a great challenge to natural language understanding. A system that can automatically paraphrase idioms in context has applications in many NLP tasks. This paper proposes a phrasal substitution method to replace idioms with their ﬁgurative meanings in literal English. Our approach identiﬁes relevant replacement phrases from an idiom’s dictionary deﬁnition and performs appropriate grammatical and referential transformations to ensure that the idiom substitution ﬁts seamlessly into the original context. The proposed method has been evaluated both by automatic metrics and human judgments. Results suggest that high quality paraphrases of idiomatic expressions can be achieved.
A group division method based on collaborative learning elements

In order to achieve collaborative learning in network learning system, two primary questions must be solved. First is how to choose and quantify the proper features to build user model. Second is how to divide the users into optimal teams to play the best effectiveness of collaborative learning. Based on the collaborative learning theory, its practical research, and the conditions of network learning system, the paper selects learning interest and knowledge level as user's features, using the methods of educational psychology measurement to quantify these two features so as to establish user model. Considering the elements and some practical teaching cases of collaborative learning, the paper derives the requirements of collaborative learning's basic unit: the collaboration group, and defines three features of collaborative group as: the cohesion within group, the hierarchy within group and the uniformity among groups. Then, the paper builds the group model and put forward the objective function of collaborative learning grouping scheme. Finally, from the perspective of clustering and combinatorial optimization, the paper investigates how to divide the users into collaborative learning's groups. As a result, it comes up the method as follows. Above all, according to the users' learning interest, it uses K-means to cluster the users into different clusters. Then in each cluster, genetic algorithm is adopted for collaborative learning's group division according to the users' knowledge level. Thus, the paper achieves the automatic group division to find the approximate optimal collaboration learning groups. Lastly, through the simulation experiments, the validity of the method is proved.
Memory for Auditory Icons and Earcons with Localization Cues

This study was designed to test whether associations between visual icons on a computer screen and auditory icons (environmental sounds that have a direct association with an object) or earcons (synthetic sounds that have no direct association with an object) are easier to learn. In addition, localization of sound presentation relative to the position of the icons on the screen was tested. Results revealed that participants made faster and more correct matches between visual icons and auditory icons than between visual icons and earcons. The results also suggested that localization may be a useful cue for learning the associations between icons and their auditory counterparts; however, more research is needed to provide conclusive evidence.
Multiscale Entropy-Based Weighted Distortion Measure for ECG Coding

In this letter, a novel objective distortion measure is proposed for compressed electrocardiogram (ECG) signals. The measure is a weighted percentage root-mean-square difference (WPRD) between the subband coefficients of the original and compressed signals with weights equal to the multiscale entropies of the corresponding subbands. The measure appears to be a correct representation of the amount of signal distortion at all the subbands. Experiments show that the measure works better than the other existing measures and correlates well with the subjective assessments.
UHF RFID Localization Based on Evaluation of Backscattered Tag Signals

This paper introduces a 2-D position measurement system for passive ultra-high frequency (UHF) radio frequency identification (RFID) tags based on evaluation of backscattered transponder signals. The main application of the system is the localization of stationary objects tagged with RFID transponders. By combining phase and amplitude evaluation, the accuracy and the robustness of the position estimates are significantly improved compared with either approach alone. A multiple input multiple output system in which, sequentially, each frontend is configured to work as a transmitter while the remaining frontends serve as receivers is used to enable position estimation. For proof of concept, a local position measurement system demonstrator was built comprising conventional passive EPCglobal Class-1 Gen-2 UHF RFID tags, a commercial off-the-shelf RFID reader, eight transceiver frontends, baseband hardware, and signal processing. Measurements were carried out in an indoor office environment where the 3.5 m × 2.5 m measurement zone was surrounded by drywalls and concrete floor and ceiling. The experimental results showed accurate localization with a root-mean-square error of 0.020 m and a median error of 0.011 m. To determine the limits of the system, accuracy simulations were performed, which confirm the experimental results.
Resolution recovery reconstruction for a Compton camera

The spatial resolution from Compton cameras suffers from measurement uncertainties in interaction positions and energies. The degree of degradation in spatial resolution is shift-variant (SV) over the field-of-view (FOV) because the imaging principle is based on the conical surface integration. In our study, the shift-variant point spread function (SV-PSF) is derived from point source measurements at various positions in the FOV and is incorporated into the system matrix of a fully three-dimensional, accelerated reconstruction, i.e. the listmode ordered subset expectation maximization (LMOSEM) algorithm, for resolution recovery. Simulation data from point sources were used to estimate SV and asymmetric parameters for Gaussian, Cauchy, and general parametric PSFs. Although little difference in the fitness accuracy between Gaussian and general parametric PSFs was observed, the general parametric model showed greater flexibility over the FOV in shaping the curve between that for Gaussian and Cauchy functions. The estimated asymmetric SV-PSFs were incorporated into the LMOSEM for resolution recovery. For simulation data from a single point source at the origin, all LMOSEM-SV-PSFs improved the spatial resolution by 2.6 times over the standard LMOSEM. For two point-source simulations, reconstructions also gave a two-fold improvement in spatial resolution and resulted in a greater recovered activity ratio at different positions in the FOV.
RGB-D Indoor Plane-based 3D-Modeling using Autonomous Robot

3D model of indoor environments provide rich information that can facilitate the disambiguation of different places and increases the familiarization process to any indoor environment for the remote users. In this research work, we describe a system for visual odometry and 3D modeling using information from RGB-D sensor (Camera). The visual odometry method estimates the relative pose of the consecutive RGB-D frames through feature extraction and matching techniques. The pose estimated by visual odometry algorithm is then refined with iterative closest point (ICP) method. The switching technique between ICP and visual odometry in case of no visible features suppresses inconsistency in the final developed map. Finally, we add the loop closure to remove the deviation between first and last frames. In order to have a semantic meaning out of 3D models, the planar patches are segmented from RGB-D point clouds data using region growing technique followed by convex hull method to assign boundaries to the extracted patches. In order to build a final semantic 3D model, the segmented patches are merged using relative pose information obtained from the first step.
Biohashing and Fusion of Palmprint and Palm Vein Biometric Data

This paper combines the results of our previous experiments concerning acquisition of the images of the human palm in infrared and visible light, the extraction of features from images as well as our current results on biometric data hashing with the advanced biohashing algorithm. We first describe the properties of the complex 2D matched filtering for feature extraction from images, followed by biometric vector construction techniques and raw biometric data comparison. We address the problem of securing biometric data for multimodal biometric systems, by analyzing the biohashing algorithm and proposing our enhancements. Results of experiments that include raw biometric data comparison, biohashing and advanced biohashing biocode comparisons are presented at the end of the paper.
Stressor-responsive central nesfatin-1 activates corticotropin-releasing hormone, noradrenaline and serotonin neurons and evokes hypothalamic-pituitary-adrenal axis

A recently discovered satiety molecule, nesfatin-1, is localized in neurons of the hypothalamus and brain stem and colocalized with stress-related substances, corticotropin-releasing hormone (CRH), oxytocin, proopiomelanocortin, noradrenaline (NA) and 5-hydroxytryptamine (5-HT). Intracerebroventricular (icv) administration of nesfatin-1 produces fear-related behaviors and potentiates stressor-induced increases in plasma adrenocorticotropic hormone (ACTH) and corticosterone levels in rats. These findings suggest a link between nesfatin-1 and stress. In the present study, we aimed to further clarify the neuronal network by which nesfatin-1 could induce stress responses in rats. Restraint stress induced c-Fos expressions in nesfatin-1-immunoreactive neurons in the paraventricular nucleus (PVN) and supraoptic nucleus (SON) of the hypothalamus, and in the nucleus of solitary tract (NTS), locus coeruleus (LC) and dorsal raphe nucleus (DR) in the brain stem, without altering plasma nesfatin-1 levels. Icv nesfatin-1 induced c-Fos expressions in the PVN, SON, NTS, LC, DR and median raphe nucleus, including PVN-CRH, NTS-NA, LC-NA and DR-5-HT neurons. Nesfatin-1 increased cytosolic Ca2+ concentration in the CRH-immunoreactive neurons isolated from PVN. Icv nesfatin-1 increased plasma ACTH and corticosterone levels. These results indicate that the central nesfatin-1 system is stimulated by stress and activates CRH, NA and 5-HT neurons and hypothalamic-pituitary-adrenal axis, evoking both central and peripheral stress responses.
The MSRA machine translation system for IWSLT 2010

This paper describes the systems of, and the experiments by, Microsoft Research Asia (MSRA), with the support of Microsoft Research (MSR), in the IWSLT 2010 evaluation campaign. We participated in all tracks of the DIALOG task (Chinese/English). While we follow the general training and decoding routine of statistical machine translation (SMT) and that of MT output combination, it is our first time to try our ideas in post-processing output of automatic speech recognition (ASR) before feeding it to SMT decoders. Our findings are: (1) it does not help to use the complete N-best ASR output; rather, the best translation performance is achieved by taking the top one candidate after Minimum Bayes Risk re-ranking of the N-best ASR output; (2) as to punctuation recovery, the best performance is achieved by splitting the problem into two steps, viz. the prediction of punctuation position and the prediction of punctuation given a position.
Application-level Simulation for Network Security

NeSSi (network security simulator) is a novel network simulation tool which incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Its capabilities such as profile-based automated attack generation, traffic analysis and support for detection algorithm plug-ins allow it to be used for security research and evaluation purposes. NeSSi has been successfully used for testing intrusion detection algorithms, conducting network security analysis and developing overlay security frameworks. NeSSi is built upon the agent framework JIAC, resulting in a distributed and extensible architecture. In this paper, we provide an overview of the NeSSi architecture as well as its distinguishing features and briefly demonstrate its application to current security research projects.
Rate of familial amyotrophic lateral sclerosis: a systematic review and meta-analysis

Background The population rate of familial amyotrophic lateral sclerosis (FALS) is frequently reported as 10%. However, a systematic review and meta-analysis of the true population based frequency of FALS has never been performed. Method A Medline literature review identified all original articles reporting a rate of FALS. Studies were grouped according to the type of data presented and examined for sources of case ascertainment. A systematic review and meta-analysis of reported rates of FALS was then conducted to facilitate comparison between studies and calculate a pooled rate of FALS. Results 38 papers reported a rate of FALS. Thirty-three papers were included in analysis and the rate of FALS for all studies was 4.6% (95% CI 3.9% to 5.5%). Restricting the analysis to prospective population based registry data revealed a rate of 5.1% (95% CI 4.1% to 6.1%). The incidence of FALS was lower in southern Europe. There was no correlation between rate of FALS and reported SOD1 mutation rates. Conclusion The rate of FALS among prospective population based registries is 5.1% (CI 4.1 to 6.1%), and not 10% as is often stated. Further detailed prospective population based studies of familial ALS are required to confirm this rate.
Proprioceptive Body Illusions Modulate the Visual Perception of Reaching Distance

The neurobiology of reaching has been extensively studied in human and non-human primates. However, the mechanisms that allow a subject to decide—without engaging in explicit action—whether an object is reachable are not fully understood. Some studies conclude that decisions near the reach limit depend on motor simulations of the reaching movement. Others have shown that the body schema plays a role in explicit and implicit distance estimation, especially after motor practice with a tool. In this study we evaluate the causal role of multisensory body representations in the perception of reachable space. We reasoned that if body schema is used to estimate reach, an illusion of the finger size induced by proprioceptive stimulation should propagate to the perception of reaching distances. To test this hypothesis we induced a proprioceptive illusion of extension or shrinkage of the right index finger while participants judged a series of LEDs as reachable or non-reachable without actual movement. Our results show that reach distance estimation depends on the illusory perceived size of the finger: illusory elongation produced a shift of reaching distance away from the body whereas illusory shrinkage produced the opposite effect. Combining these results with previous findings, we suggest that deciding if a target is reachable requires an integration of body inputs in high order multisensory parietal areas that engage in movement simulations through connections with frontal premotor areas.