Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of protein phosphatase 2A as an interacting protein of leucine-rich repeat kinase 2

Abstract Mutations in the gene coding for the multi-domain protein leucine-rich repeat kinase 2 (LRRK2) are the leading cause of genetically inherited Parkinson’s disease (PD). Two of the common found mutations are the R1441C and G2019S. In this study we identified protein phosphatase 2A (PP2A) as an interacting partner of LRRK2. We were able to demonstrate that the Ras of complex protein (ROC) domain is sufficient to interact with the three subunits of PP2A in human neuroblastoma SH-SY5Y cells and in HeLa cells. The alpha subunit of PP2A is interacting with LRRK2 in the perinuclear region of HeLa cells. Silencing the catalytic subunit of PP2A by shRNA aggravated cellular degeneration induced by the pathogenic R1441C-LRRK2 mutant expressed in neuroblastoma SH-SY5Y cells. A similar enhancement of apoptotic nuclei was observed by downregulation of the catalytic subunit of PP2A in cultured cortical cells derived from neurons overexpressing the pathogenic mutant G2019S-LRRK2. Conversely, pharmacological activation of PP2A by sodium selenate showed a partial neuroprotection from R1441C-LRRK2-induced cellular degeneration. All these data suggest that PP2A is a new interacting partner of LRRK2 and reveal the importance of PP2A as a potential therapeutic target in PD.
Carbon accumulation in Colorado ponderosa pine stands

Woody encroachment and thickening have occurred throughout the western United States and have been proposed as important processes in the US carbon (C) budget despite large uncertainty in the magnitude of these effects. In this study we investigated ponderosa pine encroachment near Boulder, Colorado. We reconstructed a time series of forest structure to estimate changes in C storage by the trees. Advantages of this technique include the ability to estimate changes in C stocks over time with a single series of measurements (i.e., no historical measurements), and the ability to calculate accumulation rate changes through time. Substantial variation occurred in the C amounts and accumulation rates among the three plots resulting from differences in slope, aspect, and soil conditions. Accumulation rates increased exponentially as trees increased in size and additional trees established within the plots, and were highly variable among plots (0.090.7 Mg C·ha1·year1 during 19802001). These rates were less th.
Coding of sources with unknown statistics-II: Distortion relative to a fidelity criterion

The encoding of sources with unknown statistics is considered. The average distortion that is obtained with universal coding schemes that are independent of the source statistics is shown to be asymptotically identical to the smallest average distortion that can be achieved with the best individual coding scheme (i.e., a code that is based on the specific statistics of the source). This result is shown to hold for any stationary source, as well as for a class of nonstationary sources. The discussion is limited to a certain important class of metric spaces.
What do we value in procedural content generation?

Generative systems embody and promote values through their design. This position paper discusses common values in existing PCG systems and suggests alternate, contrasting values that could lead to new kinds of PCG research and practice. There is a need for criticality and awareness of the values we embed in our work, and for consciously reflecting upon our shared values as a community.
Switching cost, market effects and the pricing model of e-commerce

Our paper develops a Walrasian general equilibrium model based on impersonal networking decisions to investigate the role of switching cost, trading efficiency and fixed leaving cost in a competitive market of e-commerce. Since the general equilibrium in our model is always Pareto optimal as long as nobody can block free entry into any sector and nobody can manipulate relative prices and numbers of specialists, the implications of our model is straightforward that if the e-commerce market is efficient and with lower switching cost, it ensures that network effects of division of labor can be fully exploited and the real income improve, yet the relative price in term of e-commerce service is cheaper. To business practitioners, our model suggests that successful transformation from conventional commerce to e-commerce service is a key for business viability in the future business environment.
An Appearance Model for Textile Fibers

Accurately modeling how light interacts with cloth is challenging, due to the volumetric nature of cloth appearance and its multiscale structure, where microstructures play a major role in the overall appearance at higher scales. Recently, significant effort has been put on developing better microscopic models for cloth structure, which have allowed rendering fabrics with unprecedented fidelity. However, these highly‐detailed representations still make severe simplifications on the scattering by individual fibers forming the cloth, ignoring the impact of fibers' shape, and avoiding to establish connections between the fibers' appearance and their optical and fabrication parameters. In this work we put our focus in the scattering of individual cloth fibers; we introduce a physically‐based scattering model for fibers based on their low‐level optical and geometric properties, relying on the extensive textile literature for accurate data. We demonstrate that scattering from cloth fibers exhibits much more complexity than current fiber models, showing important differences between cloth type, even in averaged conditions due to longer views. Our model can be plugged in any framework for cloth rendering, matches scattering measurements from real yarns, and is based on actual parameters used in the textile industry, allowing predictive bottom‐up definition of cloth appearance.
NEURAL-SLIDING CONTROL WITH CMAC IN VARIABLE STRUCTURE SYSTEMS

This work proposes a new method of dynamical control systems implementation using the Cerebellar Model Articulation Controller (CMAC) neural network as part of a variable structure system. CMAC is a neural network easily implemented in hardware, quite efficient in the reproduction of multivariable functions and extremely fast in its training process. These features yield CMAC applications in robust multivariable on line control in the presence of uncertainties in plant model. Variable Structure Systems (VSS) theory yields the concatenation of at least two, possibly unstable, dynamical structures, in order to realize a low cost controller that guarantees robustness with respect to nonidealities in the control system. This is done by a deliberate introduction of a special behavior named sliding mode where the state of the plant is confined to a subspace determined by the eigenvalues of the desired resultant dynamics until the origin is reached. Further, if the system model equations are written in a particular regular form and complete access to states is guaranteed for any time, the CMAC network in a variable structure system collects information enough about plant dynamics for the closed loop eigenvalues be allocated on line with no previous knowledge of plant model other than its order and structure. Furthermore, if the supposed unknown plant parameters change due to environment interaction, the resultant dynamics is invariant.
A general-purpose optimization approach for designing two-channel FIR filterbanks

An efficient general-purpose optimization approach is proposed for designing two-channel finite impulse response (FIR) filterbanks. This technique can be used for optimizing two-channel FIR filterbanks in all alias-free cases proposed in the literature. The generalized problem is to minimize the maximum of the stopband energies of the two analysis filters subject to the given passband and transition band constraints and the given allowable reconstruction error. Therefore, in addition to the perfect-reconstruction filterbanks, nearly perfect-reconstruction banks can be optimized in a controlled manner. The optimization is carried out in two steps. In the first step, for the selected type of the filterbank, a good starting-point filterbank for further optimization is generated using an existing design scheme. The second step involves optimizing the filterbank with the aid of a modified Dutta-Vidyasagar (1977) algorithm. Several examples are included, illustrating the efficiency and the flexibility of the proposed approach.
Multisensory speech perception in autism spectrum disorder: From phoneme to whole‐word perception

Speech perception in noisy environments is boosted when a listener can see the speaker's mouth and integrate the auditory and visual speech information. Autistic children have a diminished capacity to integrate sensory information across modalities, which contributes to core symptoms of autism, such as impairments in social communication. We investigated the abilities of autistic and typically‐developing (TD) children to integrate auditory and visual speech stimuli in various signal‐to‐noise ratios (SNR). Measurements of both whole‐word and phoneme recognition were recorded. At the level of whole‐word recognition, autistic children exhibited reduced performance in both the auditory and audiovisual modalities. Importantly, autistic children showed reduced behavioral benefit from multisensory integration with whole‐word recognition, specifically at low SNRs. At the level of phoneme recognition, autistic children exhibited reduced performance relative to their TD peers in auditory, visual, and audiovisual modalities. However, and in contrast to their performance at the level of whole‐word recognition, both autistic and TD children showed benefits from multisensory integration for phoneme recognition. In accordance with the principle of inverse effectiveness, both groups exhibited greater benefit at low SNRs relative to high SNRs. Thus, while autistic children showed typical multisensory benefits during phoneme recognition, these benefits did not translate to typical multisensory benefit of whole‐word recognition in noisy environments. We hypothesize that sensory impairments in autistic children raise the SNR threshold needed to extract meaningful information from a given sensory input, resulting in subsequent failure to exhibit behavioral benefits from additional sensory information at the level of whole‐word recognition. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1280–1290. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.
Open-Circuit Fault Diagnosis for Matrix Converter Drives and Remedial Operation Using Carrier-Based Modulation Methods

A novel monitoring system, designed to detect open-circuit (OC) faults that occur in the matrix converter (MC) topology, is proposed in this work. In this monitoring system, a new diagnosis method is implemented which is based on the discrete wavelet transform analysis of the measured output current waveform. In order to ensure the effectiveness of the proposed method and its resistivity to erroneous fault detections, a fuzzy expert system is used in the designed monitoring system. The main advantages of the proposed method are that the implementation cost is minimized because no extra sensors are used and that no information from the control algorithm about the modulation parameters or the applied pulse sequence is required, reducing its implementation complexity and facilitating a more modular design. Additionally, it can be easily adapted to modified matrix topologies. A simple and robust method for the localization of the open-circuited transistor(s) within the identified faulty leg is also proposed. The proposed techniques are validated by simulation and experimental tests. The remedial operation of MC drives after the occurrence of an OC fault by using a redundant leg is also studied. The use of carrier-based modulation methods for this operation is experimentally validated, and related issues are discussed.
Multisensory Motion Perception in 3–4 Month-Old Infants

Human infants begin very early in life to take advantage of multisensory information by extracting the invariant amodal information that is conveyed redundantly by multiple senses. Here we addressed the question as to whether infants can bind multisensory moving stimuli, and whether this occurs even if the motion produced by the stimuli is only illusory. Three- to 4-month-old infants were presented with two bimodal pairings: visuo-tactile and audio-visual. Visuo-tactile pairings consisted of apparently vertically moving bars (the Barber Pole illusion) moving in either the same or opposite direction with a concurrent tactile stimulus consisting of strokes given on the infant’s back. Audio-visual pairings consisted of the Barber Pole illusion in its visual and auditory version, the latter giving the impression of a continuous rising or ascending pitch. We found that infants were able to discriminate congruently (same direction) vs. incongruently moving (opposite direction) pairs irrespective of modality (Experiment 1). Importantly, we also found that congruently moving visuo-tactile and audio-visual stimuli were preferred over incongruently moving bimodal stimuli (Experiment 2). Our findings suggest that very young infants are able to extract motion as amodal component and use it to match stimuli that only apparently move in the same direction.
A Mobile P2P Community System

The distributed architecture of vitual community based on P2P has proved to resolves some problems from central architecture such as single point failure. In this paper, drawing on the idea of SOA, we propose an optimized architecture of distributed mobile P2P community system, in which the virtual communities are divided into separately service components which can be deployed in the overlay networks as resource instead of a central server. And the introduction of the physical network aware technique of P4P can help the client find the most suitable service replica. We also propose a replica consistent control mechanism to facilitate the practice of the system in this paper. At last we develope a prototype system of mobile community.
[Role of Slingshot-1L in peripheral eosinophils of asthmatic patients].

OBJECTIVE To investigate the expression of Slingshot-1L (SSH-1L) in peripheral blood eosinophils of asthmatic patients. METHODS Peripheral vein blood sample of 30 ml was collected from 15 healthy volunteers, 15 asthmatic patients with glucocorticoid treatment and 15 asthmatic patients without the treatment. The eosinophils were isolated, purified and counted for each sample, and SSH-1L/beta-actin gene fragments were amplified simultaneously by RT-PCR for the total RNA. SSH-1L protein was detected by Western blotting from the total protein of the peripheral eosinophils. The expressions of SSH-1L at both mRNA and protein levels are compared between different groups. RESULTS SSH-1L/beta-actin ratio significantly increased in untreated patients with asthma attacks in comparison with healthy volunteers (P<0.05), which did not occur in patients treated with glucocorticoids (P>0.05). The optical density of SSH-1L protein significantly increased in untreated asthmatic patients (P<0.05), but not in patients treated with glucocorticoids (P>0.05), as compared with the healthy volunteers. CONCLUSION Significantly increased SSH-1L expression in peripheral eosinophils may play an important role in the activation and migration of eosinophils.
Population pharmacokinetic‐pharmacodynamic modeling analysis of intrinsic FXa and bleeding from edoxaban treatment

Edoxaban is an oral, once‐daily, direct factor Xa (FXa) inhibitor that has been evaluated for the prevention of stroke in patients with atrial fibrillation (AF) and for the treatment and prevention of venous thromboembolism (VTE) recurrence. Pharmacokinetic (PK) and pharmacodynamic (PD) modeling and logistic regression analyses were used to explore the clinical data from phase 1 and 2 studies to determine the relationship among PK exposure, PD response, and bleeding risk. Population PK/PD modeling was performed using plasma edoxaban concentration data from combined phase 1 and 2 studies and using intrinsic FXa data from a phase 2 AF study. A 2‐compartment PK model adequately described the combined PK data, and a dynamic binding model characterized the dynamics of the intrinsic factor X activity (iFXa) data. Logistic regression analysis then identified the relationship between the iFXa and the observed bleeding risk. The more protracted suppression of FXa over the dosing interval for a 30‐mg twice‐daily dose compared with a 60‐mg once‐daily dose offers an explanation for the significantly higher bleeding rate at the former dose.
Absence of Adenine-Rich Ribonucleic Acid from Purified Infectious Reovirus 3

The basic properties of released and cell-associated reovirus are the same. Both contained as their total nucleic acid complement only double-stranded ribonucleic acid (RNA) with an adenine content of 28%. Preparations of purified cell-associated virus, but not released virus, contained adenine-rich RNA which could be separated from the virus with little or no loss of infectivity. These adenine-rich ribonucleic acids were present in the virus preparations either as free RNA or associated with some structures of molecular weight less than 25 × 106 daltons. In contrast to our previous report, double-stranded reovirus RNA possessed little or no template activity for the Escherichia coli deoxyribonucleic acid and RNA polymerases.
Integrated capacitive power-management circuit for thermal harvesters with output power 10 to 1000µW

Energy harvesters [1] power energy-autonomous wireless sensor systems by converting ambient environmental energy into electrical energy. Thermoelectric generators (TEG's) are a suitable compact power supply for both on-the-body and industrial sensors. Due to changing conditions, the generated power and voltage vary. Therefore a power management circuit (PMC) has to store the generated energy in a rechargeable battery or capacitor. It contains a DC/DC-converter with variable conversion factor and a controller that sets the conversion factor.
A consensus procedure for predicting the location of alpha-helical transmembrane segments in proteins

To aid in the development of three-dimensional models of membrane-bound proteins, a consensus procedure for predicting alpha-helical transmembrane segments from amino acid sequence is presented. The algorithm combines the results of six individual prediction methods and some basic properties of membrane-spanning helices to obtain a final consensus prediction. Comparison with experiment and several other recently developed methods shows that the consensus procedure performs quite well in comparison to other recent methods. A FORTRAN program has been developed which takes an input file containing an amino acid sequence in one-letter code and outputs a list of the alpha-helical transmembrane segments predicted by the consensus algorithm.
Mobile Customer Clustering Based on Call Detail Records for Marketing Campaigns

Competition in the mobile telecommunications industry is becoming more and more fierce. In order to improve mobile operator’s competitiveness and customer value, several data mining technologies can be used. One of most important data mining technologies is customer clustering analysis. This targeting practice has been proven manageable and effective for mobile telecommunications industry. Most telecommunications carriers cluster their mobile customers by billing data. This paper proposes to cluster mobile customers based on their call detail records (CDR). It clusters customers based on real CDR, and analyzes their behaviors. Based on the analyzed results of the clustering model, the paper suggests practical proposals for the mobile operators’ marketing. Furthermore, it compares marketing effectiveness before and after using the clustering, and proves that new promoting strategy has visible effects.
Investigation of steering dynamics ship model identification based on PSO-LSSVR

According to the high-order nonlinearity and parameter uncertainty of the ship steering dynamics, it is difficult to establish the accurate mathematical model by using normal identification methods. To solve this problem, a new kind of least squares support vector regression based on the particle swarm optimization (PSO-LSSVR) is proposed. This method can select the parameters of LSSVR automatically without trial and error, thus ensure the accuracy of parameters optimization. Apply this method to the model identification of the ship steering dynamics, and compare the identification effect with the experimental reference data. The PSO-LSSVR is able to establish the system model effectively, the structure is simple and generalization ability is well.
Trust in Technology as a Safety Aspect in Highly Automated Driving

Abstract Trust in technology is an important factor to be considered for safety-critical systems. Of particular interest today is the transport domain, as more and more complex information and assistance systems find their way into vehicles. Research in driving automation / automated driving systems is in the focus of many research institutes worldwide. On the operational side, active safety systems employed to save lives are frequently used by non-professional drivers that neither know system boundaries nor the underlying functional principle. This is a serious safety issue, as systems are activated under false circumstances and with wrong expectations. At least some of the recent incidents with advanced driving assistance systems (ADAS) or automated driving systems (ADS; SAE J3016) could have been prevented with a full understanding of the driver about system functionality and limitations (instead of overreliance). Drivers have to be trained to accept and use these systems in a way, that subjective trust matches objective trustworthiness (cf. “appropriate trust”) to prevent disuse and / or misuse. In this article, we present an interaction model for trust calibration that issues personalized messages in real time. On the showcase of automated driving we report the results of two user studies related to trust in ADS and driving ethics. In the first experiment (N = 48), mental and emotional states of front-seat passengers were compared to get deeper insight into the dispositional trust of potential users of automated vehicles. Using quantitative and qualitative methods, we found that subjects accept and trust ADSs almost similarly as male / female drivers. In another study (N = 40), moral decisions of drivers were investigated in a systematic way. Our results indicate that the willingness of drivers to risk even severe accidents increases with the number and age of pedestrians that would otherwise be sacrificed. Based on our initial findings, we further discuss related aspects of trust in driving automation. Effective shared vehicle control and expected advantages of fully / highly automated driving (SAE levels 3 or higher) can only be achieved when trust issues are demonstrated and resolved.
Multiple-view face hallucination by a novel regression analysis in tensor space

In this paper, the novel multiple-view face hallucination method was proposed. This method is reconstructed the high-resolution face images in various poses (normal, up, down, left, and right) from a single low-resolution face image within these poses. There are two steps in our proposed method. In the first step, a high-resolution face image in the same view of the observation is reconstructed by the position-patch face hallucination framework with the improved Locally Linear Embedding (LLE), which the number of neighbours is adaptive. In the second step, the reconstructed image is used to generate the highresolution of the other views by the novel tensor regression technique. The experimental results on the well-known dataset show that the proposed method can achieve the better quality image than the baseline methods.