Miracle-dz/UniFAR-FTUs huggingface dataset:
Moderating Factors in Return to Work and Job Stability After Traumatic Brain Injury

Objective:To examine job stability moderating variables and develop a postinjury work stability prediction model. Design:Multicenter analysis of individuals with traumatic brain injury (TBI) who returned for follow-up at 1, 2, and 3, or 4 years postinjury, were of working age (between 18 and 62 years of age at injury), and were working preinjury. Setting:Six National Institute on Disability and Rehabilitation Research TBI Model System centers for coordinated acute and rehabilitation care. Participants:A total of 186 adults with TBI were included in the study. Main outcome measures:Job stability was categorized as stably employed (employed at all 3 follow-up intervals); unstably employed (employed at one or two of all three follow-up intervals); and unemployed (unemployed at all three follow-up intervals). Results:After injury, 34% were stably employed, 27% were unstably employed, and 39% were unemployed at all three follow-up intervals. Minority group members, people who did not complete high school, and unmarried people were more likely to be unemployed. Driving independence was highly influential and significantly related to employment stability. A discriminant function analysis, which included age, length of unconsciousness and Disability Rating Scale scores at 1 year postinjury, accurately predicted job stability groupings. ConclusionData analysis provided evidence that employment stability is predictable with a combination of functional, demographic, and injury severity variables. Identification of people at risk for poor employment outcomes early on can facilitate rehabilitation planning and intervention.
Heterogeneity in Kv2 Channel Expression Shapes Action Potential Characteristics and Firing Patterns in CA1 versus CA2 Hippocampal Pyramidal Neurons

Abstract The CA1 region of the hippocampus plays a critical role in spatial and contextual memory, and has well-established circuitry, function and plasticity. In contrast, the properties of the flanking CA2 pyramidal neurons (PNs), important for social memory, and lacking CA1-like plasticity, remain relatively understudied. In particular, little is known regarding the expression of voltage-gated K+ (Kv) channels and the contribution of these channels to the distinct properties of intrinsic excitability, action potential (AP) waveform, firing patterns and neurotransmission between CA1 and CA2 PNs. In the present study, we used multiplex fluorescence immunolabeling of mouse brain sections, and whole-cell recordings in acute mouse brain slices, to define the role of heterogeneous expression of Kv2 family Kv channels in CA1 versus CA2 pyramidal cell excitability. Our results show that the somatodendritic delayed rectifier Kv channel subunits Kv2.1, Kv2.2, and their auxiliary subunit AMIGO-1 have region-specific differences in expression in PNs, with the highest expression levels in CA1, a sharp decrease at the CA1-CA2 boundary, and significantly reduced levels in CA2 neurons. PNs in CA1 exhibit a robust contribution of Guangxitoxin-1E-sensitive Kv2-based delayed rectifier current to AP shape and after-hyperpolarization potential (AHP) relative to that seen in CA2 PNs. Our results indicate that robust Kv2 channel expression confers a distinct pattern of intrinsic excitability to CA1 PNs, potentially contributing to their different roles in hippocampal network function.
Inhibition of Natural Killer Cells through Engagement of CD81 by the Major Hepatitis C Virus Envelope Protein

The immune response against hepatitis C virus (HCV) is rarely effective at clearing the virus, resulting in ∼170 million chronic HCV infections worldwide. Here we report that ligation of an HCV receptor (CD81) inhibits natural killer (NK) cells. Cross-linking of CD81 by the major envelope protein of HCV (HCV-E2) or anti-CD81 antibodies blocks NK cell activation, cytokine production, cytotoxic granule release, and proliferation. This inhibitory effect was observed using both activated and resting NK cells. Conversely, on NK-like T cell clones, including those expressing NK cell inhibitory receptors, CD81 ligation delivered a costimulatory signal. Engagement of CD81 on NK cells blocks tyrosine phosphorylation through a mechanism which is distinct from the negative signaling pathways associated with NK cell inhibitory receptors for major histocompatibility complex class I. These results implicate HCV-E2–mediated inhibition of NK cells as an efficient HCV evasion strategy targeting the early antiviral activities of NK cells and allowing the virus to establish itself as a chronic infection.
REVEL

REVEL is an augmented reality (AR) tactile technology that allows for change to the tactile feeling of real objects by augmenting them with virtual tactile textures using a device worn by the user. Unlike previous attempts to enhance AR environments with haptics, we neither physically actuate objects or use any force- or tactile-feedback devices, nor require users to wear tactile gloves or other apparatus on their hands. Instead, we employ the principle of reverse electrovibration where we inject a weak electrical signal anywhere on the user body creating an oscillating electrical field around the user's fingers. When sliding his or her fingers on a surface of the object, the user perceives highly distinctive tactile textures augmenting the physical object. By tracking the objects and location of the touch, we associate dynamic tactile sensations to the interaction context. REVEL is built upon our previous work on designing electrovibration-based tactile feedback for touch surfaces [Bau, et al. 2010]. In this paper we expand tactile interfaces based on electrovibration beyond touch surfaces and bring them into the real world. We demonstrate a broad range of application scenarios where our technology can be used to enhance AR interaction with dynamic and unobtrusive tactile feedback.
Downlink Small-Cell Base Station Cooperation Strategy in Fractal Small-Cell Networks

Coordinated multipoint (CoMP) communications are considered for the fifth-generation (5G) small-cell networks as a tool to improve the high data rates and the cell-edge throughput. The average achievable rates of the small-cell base stations (SBS) cooperation strategies with distance and received signal power constraints are respectively derived for the fractal small-cell networks based on the anisotropic path loss model. Simulation results are presented to show that the average achievable rate with the received signal power constraint is larger than the rate with a distance constraint considering the same number of cooperative SBSs. The average achievable rate with distance constraint decreases with the increase of the intensity of SBSs when the anisotropic path loss model is considered. What's more, the network energy efficiency of fractal small-cell networks adopting the SBS cooperation strategy with the received signal power constraint is analyzed. The network energy efficiency decreases with the increase of the intensity of SBSs which indicates a challenge on the deployment design for fractal small-cell networks.
Texture coordinate generation of colonic surface meshes for surgical simulation

Simulation of surgical procedures requires visualisation of realistic geometric models of organs generated from 3D patient images. Significant improvements in visual realism can be obtained through appropriate surface texturing and shading. In this paper we present a novel technique for continuous surface parameterisation of colonic geometric models utilising surface voxel to centreline correspondences derived from Laplace's equation. Our technique creates continuous texture coordinates which exhibit minimal distortion and which enable us to use advanced texturing and shading techniques. Experimental results from phantom volumes and real cases are detailed.
Designing locative media for creative misuse: learning from urban intervention

This paper examines the possibilities of designing locative media for creative misuse by learning from non-conventional and interventive urban practices. Instead of taking technologies as a starting point, we focused on the location and media related practices of two distinct communities who by virtue of the practices they are engaged with, have a particular relationship to places and spaces. By collaboratively mapping their practices we aimed to ground the further development of locative media application concepts and formulate design considerations for creative misuse in this context.
Hand gesture recognition using neural network based techniques

In this paper, two neural network based methods were implemented for recognition of images showing 10 hand gestures. Images were available from 24 subjects and captured on two different backgrounds and with several space orientations. Firstly, Histogram of Oriented Gradients method was applied for feature extraction and training was performed with multilayer feed forward neural network with back propagation algorithm. Within the second method, Sparse autoencoder with 5 hidden layers and decreasing number of neurons was implemented. For both methods it was examined how number of descriptors influences the accuracy of classification and found relationship was used to determine best performing case. Both classification methods achieved accuracy of about 92.5%, by using the similar number of estimated parameters.
Determination of protein–DNA binding constants and specificities from statistical analyses of single molecules: MutS–DNA interactions

Atomic force microscopy (AFM) is a powerful technique for examining the conformations of protein-DNA complexes and determining the stoichiometries and affinities of protein-protein complexes. We extend the capabilities of AFM to the determination of protein-DNA binding constants and specificities. The distribution of positions of the protein on the DNA fragments provides a direct measure of specificity and requires no knowledge of the absolute binding constants. The fractional occupancies of the protein at a given position in conjunction with the protein and DNA concentrations permit the determination of the absolute binding constants. We present the theoretical basis for this analysis and demonstrate its utility by characterizing the interaction of MutS with DNA fragments containing either no mismatch or a single mismatch. We show that MutS has significantly higher specificities for mismatches than was previously suggested from bulk studies and that the apparent low specificities are the result of high affinity binding to DNA ends. These results resolve the puzzle of the apparent low binding specificity of MutS with the expected high repair specificities. In conclusion, from a single set of AFM experiments, it is possible to determine the binding affinity, specificity and stoichiometry, as well as the conformational properties of the protein-DNA complexes.
Regulation of Glutathione Synthesis via Interaction between Glutamate Transport-Associated Protein 3-18 (GTRAP3-18) and Excitatory Amino Acid Carrier-1 (EAAC1) at Plasma Membrane

Regulation of the cysteine transporter known as excitatory amino acid carrier-1 (EAAC1) for intracellular glutathione (GSH) content was investigated using human embryonic kidney (HEK) 293 cells as a model system. GSH content was significantly reduced by l-aspartate-β-hydroxamate (50–250 μM), an inhibitor of both EAAC1 and GLT1, both of which are transporters to take up cysteine, whereas dihydrokainate (1–100 μM), a specific inhibitor of GLT1, failed to do so. This indicates that EAAC1 is involved in GSH content in HEK293 cells. We examined the effect of glutamate transport-associated protein 3-18 (GTRAP3-18), which is capable of interacting with EAAC1. The GSH content decreased when the GTRAP3-18 protein level at the plasma membrane was increased by methyl-β-cyclodextrin (250 μM), rendering the cells more vulnerable to oxidative stress. Intracellular GSH increased when the GTRAP3-18 protein level at the plasma membrane was decreased by antisense oligonucleotides, rendering the cells more resistant to oxidative stress. Furthermore, we found that the increase in GSH content produced by stimulating protein kinase C, a translocator and activator of EAAC1, was inhibited by an increase in cell surface GTRAP3-18 protein. These results show GTRAP3-18 to negatively and dominantly regulate cellular GSH content via interaction with EAAC1 at the plasma membrane.
Effect of Wenxin Granules on Gap Junction and MiR-1 in Rats with Myocardial Infarction

Myocardial infarction (MI) patients are at high risk of potential lethal arrhythmia. Gap junction and microRNA-1 (miR-1) are both arrhythmia generating conditions. The present study investigated whether Wenxin Granules (Wenxin-Keli, WXKL) could prevent potential lethal arrhythmia by improving gap junctions and miR-1 following MI. Male Sprague-Dawley rats were divided randomly into control, model, metoprolol, low dose WXKL, and high dose WXKL groups. The MI rat model was created by coronary artery ligation. Treatments were administrated intragastrically to the rats for 4 weeks. Conventional transmission electron microscopy was performed to observe the ultrastructure of gap junctions. Quantitative real-time PCR and western blotting were used to detect the expression of miR-1, protein kinase C (PKC), and related proteins. Additionally, a programmatic electrophysiological stimulation test was performed to detect the ventricular fibrillation threshold (VFT). WXKL protected the ultrastructure of the gap junctions and their constituent Cx43 by regulating miR-1 and PKC mediated signal transduction and increased the VFT significantly in the rat MI model. The results suggested that WXKL is an effective alternative medicine to prevent potentially lethal arrhythmia following MI.
Structure of solutions of the Skyrme model on a three-sphere: numerical results

The hedgehog Skyrme model on a three-sphere admits a very rich spectrum of solitonic solutions which can be encompassed by a strikingly simple scheme. The main result of this paper is the statement of the tripartite structure of solutions of the model and the discovery of which configurations contain these solutions. The model contains features of more complicated models in general relativity and as such can give insight into them.
Efficient partial enhanced scan for high coverage delay testing

The architectural limitations of traditional scan restrict the two pattern delay tests that can be applied to a design, resulting in degraded delay test coverage. The use of enhanced scan flip-flops can alleviate this problem by supporting arbitrary delay test vector pairs, but at very high area overhead. Earlier work[13], using a Monte-Carlo simulation based flip-flop selection procedure on the smaller benchmark circuits has shown that most of the TDF coverage benefits of full enhanced scan can be achieved by using only 20–30% enhanced scan flip-flops. However, Monte-Carlo simulation to obtain signal probabilities to identify flip-flops that have poor controllability is not practical for large circuits. We present a new, computationally efficient method for selecting the enhanced scan flip-flops that leverages commercial testability tools by using easy to compute SCOAP [6] testability measures. Furthermore, our method substantially improves on the earlier partial enhanced scan results by developing a methodology for eliminating some of the poor controllability flip-flops as candidates for enhanced scan through analysis of signal constraints due to the circuit structure. We also discover additional flip-flops that display strong dependencies between the V1 and V2 vectors during LOC tests that were missed in [13]. The result is a computationally efficient selection method that identifies only those flip-flops where the dependency between the V1 and V2 vectors in LOC tests limits TDF coverage. Our results show that only 10–20% enhanced scan flip-flops can support high quality delay tests.
Study of Globally Exponential Synchronization for the Family of RÖssler Systems

This paper considers the globally exponential synchronization (GES) of the family of Rossler chaotic systems. One pair of the six transmitter-receiver systems is specifically studied, and algebraic criterion for the GES is obtained via proper nonlinear feedback controls. Based on the study of the systems' structures, appropriate Lyapunov functions are constructed for error systems. The method presented in this paper provides a convenient tool in the practical use of chaos control and synchronization. Numerical simulations are provided to demonstrate the theoretical results.
Persistent Phytoplankton Bloom in Lake St. Lucia (iSimangaliso Wetland Park, South Africa) Caused by a Cyanobacterium Closely Associated with the Genus Cyanothece (Synechococcaceae, Chroococcales)

ABSTRACT Lake St. Lucia, iSimangaliso Wetland Park, South Africa, is the largest estuarine lake in Africa. Extensive use and manipulation of the rivers flowing into it have reduced freshwater inflow, and the lake has also been subject to a drought of 10 years. For much of this time, the estuary has been closed to the Indian Ocean, and salinities have progressively risen throughout the system, impacting the biotic components of the ecosystem, reducing zooplankton and macrobenthic biomass and diversity in particular. In June 2009, a bloom of a red/orange planktonic microorganism was noted throughout the upper reaches of Lake St. Lucia. The bloom persisted for at least 18 months, making it the longest such bloom on record. The causative organism was characterized by light and electron microscopy and by 16S rRNA sequencing and was shown to be a large, unicellular cyanobacterium most strongly associated with the genus Cyanothece. The extent and persistence of the bloom appears to be unique to Lake St. Lucia, and it is suggested that the organism's resistance to high temperatures, to intense insolation, and to hypersalinity as well as the absence of grazing pressure by salinity-sensitive zooplankton all contributed to its persistence as a bloom organism until a freshwater influx, due to exceptionally heavy summer rains in 2011, reduced the salinity for a sufficient length of time to produce a crash in the cyanobacterium population as a complex, low-salinity biota redeveloped.
Online Detection of Network Traffic Anomalies Using Degree Distributions

Diagnosing traffic anomalies rapidly and accurately is critical to the efficient operation of large computer networks. However, it is still a challenge for network administrators. One problem is that the amount of traffic data does not allow real-time analysis of details. Another problem is that some generic detection metrics possess lower capabilities on diagnosing anomalies. To overcome these problems, we propose a system model with an explicit algorithm to perform on-line traffic analysis. In this scheme, we first make use of degree distributions to effectively profile traffic features, and then use the entropy to determine and report changes of degree distributions, which changes of entropy values can accurately differentiate a massive network event, normal or anomalous by adaptive threshold. Evaluations of this scheme demonstrate that it is feasible and efficient for on-line anomaly detection in practice via simulations, using traffic trace collected at high-speed link.
Identification of RF Harmonic Distortion on Si Substrates and its Reduction Using a Trap-Rich Layer

Harmonic distortion (HD) is measured arising from coplanar waveguide structures on various substrates at 900 MHz, and significant distortion for silicon substrates is demonstrated for the first time. For an input power of +35 dBm, 2nd harmonic power of -47 dBm and 3rd of -57 dBm are measured for a thru calibration structure on oxidized high-resistivity silicon (HRS) substrates, and 2nd harmonic of -23 and 3rd of -20 dBm for a longer line on a thinner oxide. These levels are high compared to a full cellular transmit switch product specification of -45 and -40 dBm for 2nd and 3rd harmonics, respectively, at similar power levels. The contribution of the silicon substrate to high harmonic levels is investigated experimentally, and an efficient technological solution based on the introduction of a trap-rich layer is demonstrated.
Bootstrap Confidence Interval for the Median Failure Time of Three-Parameter Weibull Distribution

In many applications of failure time data analysis, it is important to perform inferences about the median of the distribution function in situations of failure time data modeling with skewed distribution. For failure time distributions where the median of the distribution function can be analytically calculated, its maximum likelihood estimator is easily obtained from the invariance properties of the maximum likelihood estimators. From the asymptotical normality of the maximum likelihood estimators, confidence intervals can be obtained. However, these results might not be very accurate for small sample sizes and/or with large proportion of censored obser- vations. Considering the three-parameter Weibull distribution for the failure time data, we present and compare the accuracy of asymptotical confidence intervals with confidence intervals based on bootstrap simulation. The alternative methodology of confidence intervals for the median of the three-parameter Weibull distribution function is illustrated by using real data from engineering field. The nonparametric bootstrap procedure was implemented in the SAS® system which incorporated proc nlp, proc surveyselect and proc iml in the SAS® macro environment.
One Shot Photometric Stereo from Reflectance Classification

3D reconstruction of object shape is one of the most important problem in the field of computer vision. Especially, estimation of normal orientation of object surface is useful for photo-realistic image rendering. For this estimation, the photometric stereo is often used. However, it requires multiple images taken under different lighting conditions in the same pose, and thus, we cannot apply it to moving objects in general. In this paper, we propose a one-shot photometric stereo for estimating surface normal of moving objects with arbitrary textures. In our method, we estimate surface orientation and reflectance property simultaneously. For this objective, reflectance data set is used for decreasing DoF (Degree of Freedom) of estimation. In addition, we classify reflectance property of an input image into limited number of classes. By using the prior knowledge, our method can estimate surface orientation and reflectance property, even if input information is not sufficient for the estimation.