Miracle-dz/UniFAR-FTUs huggingface dataset:
Two adaptive approaches of nonlinear system control

Generally the artificial neural networks (ANN) are regarded as highly computational demanding method. The usage of ANN in model predictive control as an adaptive predictor is mostly impossible. The aim of this paper is to present and compare one possible way how to reduce computational costs of adaptive predictors based on artificial neural networks. This paper presents real-time system control by two adaptive control methods. The first method is based on the model predictive method with adaptive artificial neural network as a predictor. This artificial neural network offers interesting solution of the computation time problem while using artificial neural network as an adaptive (online) predictor. The second method is established on self-tuning approach. Both these methods are applied to a problem of control liquid level in interconnected tanks. Real-time experiments are performed using Amira DTS200 - three tank system. This system is characterized by non-linear behavior.
Exploring the construct-related validity of the eye and hand coordination subscale of the Griffiths Mental Development Scales-Extended revised (GMDS-ER)

To constantly add to our understanding of child development, a valid, comprehensive, well-researched measure is needed. The recent revision and standardisation of the Griffiths Mental Development Scales Extended Revised (GMDS-ER) has necessitated investigations into its psychometric properties. This measure is used to identify developmental delays in children and critical decisions may be made, hence it is imperative that this measure be deemed both reliable and valid. This study aimed to contribute to the broader restandardisation project and focussed on gathering qualitative and quantitative construct-related validity evidence for one of the six Subscales of the GMDS-ER, namely the Eye and Hand Coordination Subscale (Subscale D). An exploratory descriptive method using a triangulation approach was used to explore the construct-related validity evidence of the Eye and Hand Coordination Subscale. A non-random purposively selected sample of 6 experts, who had worked at least 10 years with children assessing and evaluating the domain of eye-hand coordination, participated in a facet analysis to identify the underlying dimensions tapped by the Eye and Hand Coordination Subscale. The sample for the quantitative aspects of this study, the empirical validation of the construct model, was collected as part of the broader restandardisation and represented a stratified sample of 1026 children between the ages 24 months and 96 months from across the United Kingdom and Eire. Three measures, namely a biographical questionnaire, the GMDS-ER and a construct evaluation form were used to gather the qualitative and quantitative data. The qualitative data was analysed by means of a facet analysis and literature control which included examining other tests or subtests that tapped eye-hand coordination skills. The quantitative data was analysed by means of exploratory common factor analysis using oblique (DQUART)
Elastic Virtual Machine Scheduling for Continuous Air Traffic Optimization

As we are facing ever increasing air traffic demand, it is critical to enhance air traffic capacity and alleviate humancontrollers' workload by viewing air traffic optimization as acontinuous/online streaming problem. Air traffic optimizationis commonly formulated as an integer linear programming(ILP) problem. Since ILP is NP-hard, it is computationallyintractable. Moreover, a fluctuating number of flights changescomputational demand dynamically. In this paper, we presentan elastic middleware framework that is specifically designedto solve ILP problems generated from continuous air trafficstreams. Experiments show that our VM scheduling algorithmwith time-series prediction can achieve similar performanceto a static schedule while using 49% fewer VM hours for arealistic air traffic pattern.
On Anamorphic Adaptations and the Children of Men

In this article, I expand upon Slavoj Zižek’s “anamorphic” reading of Alfonso Cuaron’s Children of Men (2006). In this reading, Zižek distinguishes between the film’s ostensible narrative structure, the “foreground,” as he calls it, and the “background,” wherein the social and spiritual dissolution endemic to Cuaron’s dystopian England draws the viewer into a recognition of the dire conditions plaguing the post-9/11, post-Iraq invasion, neoliberal world. The foreground plots the conventional trajectory of the main character Theo from ordinary, disaffected man to self-sacrificing hero, one whose martyrdom might pave the way for a new era of regeneration. According to Zižek, in this context the foreground merely entertains, while propagating some well-worn cliches about heroic individualism as demonstrated through Hollywood’s generic conventions of an action-adventure/political thriller/science-fiction film. Zižek contends that these conventions are essential to the revelation of the film’s progressive politics, as “the fate of the individual hero is the prism through which … [one] see[s] the background even more sharply. ” Zižek’s framing of Theo merely as a “prism” limits our understanding of the film by not taking into account its status as an adaptation of P.D. James’ The Children of Men (1992). This article offers such an account by interpreting the differences between the film and its literary source as one informed by the transition from Cold War to post-9/11 neoliberal conceptions of identity and politics. To articulate the terms of this argument and its implications, I turn to another narrative depicting the identity and politics at the end of history, Francis Fukuyama’s infamous The End of History and the Last Man (1992), published the same year as James’ novel, both offering meditations on the Cold War and speculations (albeit on different registers) on its aftermath. Incorporating these two texts into Zižek’s anamorphic paradigm contributes to our understanding of the film’s message regarding the “state of things” during the post-9/11 era, as well as the Cold War era that preceded it, as perceived through the eyes of Theo adapted to suit the respective dystopian conditions of the novel and film.
A probabilistic-based approach to process model discovery

Process discovery is crucial for understanding how business operations are performed and how to improve them. The opportunity to discover process models exists given that many systems underlying the execution of process steps log their execution times. However, there are many challenges to discover the actual processes particularly complex ones and without making unrealistic assumptions. In this paper we present a novel probabilistic-based approach to discover high quality process models of any complexity. The approach has a series of steps to discover links between nodes corresponding to execution dependencies between tasks and at the end it ranks these links according to their probabilities of actually existing and classifies them according to their type. In this paper we formulate the process discovery problem, describe the challenges and describe our solution.
Evaluation of TerraSAR-X Observations for Wetland InSAR Application

This paper assesses the potential of using spaceborne X-band synthetic aperture radar (SAR) data for monitoring water-level changes over wetlands. Our analysis is based on three sets of TerraSAR-X (TSX) observations acquired over South Florida's Everglades wetlands during an eight-month period in 2008. The first set was acquired in single HH polarization stripmap mode over our northern study area, consisting of managed wetlands and urban environments. The second set was acquired in dual-polarization stripmap mode over the western half of the same area, consisting mostly of managed wetlands. The third set was also acquired with dual-polarization stripmap mode over our southern study area, consisting of natural flow freshand salt-water wetlands in the southern Everglades. The first data set was used for a proof-of-concept study to verify that X-band data can generate coherent interferograms in wetland areas. Interferometric processing of this data set shows a high level of coherence (> 0.35) over both wetland and urban regions, maintaining interferometric phase in all three interferograms spanning 11 days. Surprisingly, phase is maintained over some of the wetlands even for interferograms spanning 33 days. The other two data sets were used to evaluate interferometric coherence of all four polarization modes and to determine dominant scattering mechanism in each wetland environment. Our results show high coherence values (> 0.4) in all polarization modes, with highest values in HH, then VV, and lowest in HV or VH. Interferograms calculated from multipolarization data show very similar fringe patterns regardless of the polarization type, suggesting that the phase information in all polarization data reflects water-level changes in wetlands and that volume scattering may be less important than commonly believed. We also used the two multipolarization data sets to conduct the Pauli decomposition, finding a strong dependence of scattering mechanism on vegetation type. The high interferometric coherence level of all polarization data suggests that a significant part of the X-band scattered signal interacts with lower sections of the vegetation (trunks and branches), because scattering from wind-affected canopies cannot support such a high coherence level. The high spatial resolution of TSX, combined with its 11-day repeat orbit, makes this X-band sensor surprisingly suitable for wetland interferometric SAR applications.
ANIQUE: An Auditory Model for Single-Ended Speech Quality Estimation

In predicting subjective quality of speech signal degraded by telecommunication networks, conventional objective models require a reference source speech signal, which is applied as an input to the network, as well as the degraded speech. Non-intrusive estimation of speech quality is a challenging problem in that only the degraded speech signal is available. Non-intrusive estimation can be used in many real applications when source speech signal is not available. In this paper, we propose a new approach for non-intrusive speech quality estimation utilizing the temporal envelope representation of speech. The proposed auditory non-intrusive quality estimation (ANIQUE) model is based on the functional roles of human auditory systems and the characteristics of human articulation systems. Experimental evaluations on 35 different tests demonstrated the effectiveness of the proposed model.
Highly Strained Mid-Infrared Type-I Diode Lasers on GaSb

We describe how growth at low temperatures can enable increased active layer strain in GaSb-based type-I quantum-well diode lasers, with emphasis on extending the emission wavelength. Critical thickness and roughening limitations typically restrict the number of quantum wells that can be grown at a given wavelength, limiting device performance through gain saturation and related parasitic processes. Using growth at a reduced substrate temperature of 350 °C, compressive strains of up to 2.8% have been incorporated into GaInAsSb quantum wells with GaSb barriers; these structures exhibited peak room-temperature photoluminescence out to 3.96 μm. Using this growth method, low-threshold ridge waveguide lasers operating at 20°C and emitting at 3.4 μm in pulsed mode were demonstrated using 2.45% compressively strained GaInAsSb/GaSb quantum wells. These devices exhibited a characteristic temperature of threshold current of 50 K, one of the highest values reported for type-I quantum-well laser diodes operating in this wavelength range. This temperature stability is attributable to the increased valence band offset afforded by the high strain values, due to the simultaneously high quantum well indium and antimony mole fractions. Exploratory experiments using bismuth both as a surfactant during quantum well growth, as well as in dilute amounts incorporated into the crystal were also studied. Both methods appear to be promising avenues to surmount current strain-related limitations to laser performance and emission wavelength.
Inhibition of HIV-1 Env-Mediated Cell-Cell Fusion by Lectins, Peptide T-20, and Neutralizing Antibodies

Background: Broadly cross-reactive, neutralizing human monoclonal antibodies, including 2F5, 2G12, 4E10 and IgG1 b12, can inhibit HIV-1 infection in vitro at very low concentrations. We examined the ability of these antibodies to inhibit cell-cell fusion between Clone69TRevEnv cells induced to express the viral envelope proteins, gp120/gp41 (Env), and highly CD4-positive SupT1 cells. The cells were loaded with green and red-orange cytoplasmic fluorophores, and fusion was monitored by fluorescence microscopy. Results: Cell-cell fusion was inhibited completely by the carbohydrate binding proteins (CBPs), Hippeastrum hybrid (Amaryllis) agglutinin (HHA), and Galanthus nivalis (Snowdrop) agglutinin (GNA), and by the peptide, T-20, at relatively low concentrations. Anti-gp120 and anti-gp41 antibodies, at concentrations much higher than those required for neutralization, were not particularly effective in inhibiting fusion. Monoclonal antibodies b12, m14 IgG and 2G12 had moderate inhibitory activity; the IC50 of 2G12 was about 80 µg/ml. Antibodies 4E10 and 2F5 had no inhibitory activity at the concentrations tested. Conclusions: These observations raise concerns about the ability of neutralizing antibodies to inhibit the spread of viral genetic material from infected cells to uninfected cells via cell-cell fusion. The interaction of gp120/gp41 with cell membrane CD4 may be different in cell-cell and virus-cell membrane fusion reactions, and may explain the differential effects of antibodies in these two systems. The fluorescence assay described here may be useful in high throughput screening of potential HIV fusion inhibitors.
The performance evaluation of k-means by two MapReduce frameworks, Hadoop vs. Twister

In data mining, k-means is a method of cluster analysis using the nearest mean. It has been successfully used in various topics, ranging from market segmentation, computer vision, geostatistics, and astronomy to agriculture. But k-means like clustering is not easy to apply MapReduce model due to the iterative manner that can happen the stagger map tasks with high likelihood. This paper presents the result of performance evaluation of K-means application running on Twister and Hadoop framework. We report how to design a MapReduce application to organize the objects of dataset into k partitions. This approach provides the way to cluster a dataset by Hadoop, the MapReduce frameworks in a parallel manner.
De-noising the Image Corrupted by Mixed Noise by WESNR Model

De-noising the image comprising mixed noises all together is a challenging task as the distribution of noise is unsystematic across the image and does not have a parametric model. A system that preserves the original image matters that are not damaged and bring back the damaged or noisy part is an significant requirement wherever the noise distribution is indefinite. Additive white Gaussian noise (AWGN) combined with impulse noise (IN) is a kind of distinctive noise. In the removal of these noises lots of researches have been published, but many of them are detection based techniques. That is first impulse noise pixels locations is spotted and then mixed noise is removed. When mixed noise is robust, such schemes may yield artifacts. In this paper a modest and effective, different image denoising strategy based on weighted encoding with sparse nonlocal regularization model is suggested. This method is used to detect both noises instantaneously, where the regulation function consists of the sparsity and nonlocal self-similarity and then weighted encoding technique is engaged. It is perceived from experimental outcomes that projected method accomplishes leading performance in denoising image also pictorial quality of restored image is enhanced and the quality measuring factors shows the greater parallel with the original image.
The M r 193 , 000 Vault Protein Is Up-Regulated in Multidrug-resistant Cancer Cell Lines 1

Vaults are 13 megadalton ribonucleoprotein particles composed largely of the major vault protein (MVP) and two high molecular weight proteins, p240 and p193, and a small vault RNA (vRNA). Increased levels of MVP expression, vault-associated vRNA, and vaults have been linked directly to multidrug resistance (MDR). To further define the putative role of vaults in MDR, we produced monoclonal antibodies against theMr 193,000 vault protein and studied its expression levels in various multidrug-resistant cell lines. We find that, like MVP, p193 mRNA and protein levels are increased in various multidrug-resistant cell lines. Subcellular fractionation of vault particles revealed that vault-associated p193 levels are increased in multidrug-resistant cells as compared with the parental, drug-sensitive cells. Furthermore, protein analysis of postnuclear supernatants and coimmunoprecipitation studies show that drug-sensitive MVP-transfected tumor cells lack this up-regulation in vault-associated p193. Our observations indicate that vault formation is limited not only by the expression of the MVP but also by the expression or assembly of at least one of the other vault proteins.
An ATPG Flow to Generate Crosstalk-Aware Path Delay Pattern

With technology scaling, the growing impact of signal integrity issues imposes significant challenges in integrated circuit testing. They cause delay in the supply and ground networks, cross talk noise between multiple interconnects, variations in substrate and thermal noise parameters of the circuit, etc. Therefore, the consideration of signal integrity issues during pattern generation ensures a better path delay fault coverage. In this paper, we propose a constrained Automatic Test Pattern Generation(ATPG) flow to test path delay fault by simultaneously coupling multiple aggressors surrounding a delay sensitive victim path. This flow uses the most effective aggressors for pattern generation based on cross talk information predetermined from the layout of the circuit. We developed the constrained ATPG flow by customizing the existing scan-based techniques to generate functionally testable path delay faults. The proposed ATPG flow is applied to ITC'99 benchmark circuits. The comparison results with SPICE-based simulations shows the effectiveness of our pattern in determining worst-case path delay and also in terms of computation time.
Evaluation of Spectrum Occupancy in Indoor and Outdoor Scenario in the Context of Cognitive Radio

Dynamic spectrum access is an integral part of the Cognitive Radio paradigm. However, efficient spectrum sensing techniques are crucial on the way towards systems, which use idle spectrum bands opportunistically and increase the overall spectral efficiency. Current spectrum occupancy was evaluated in few measurement campaigns at different locations mostly located in the USA. In this paper we report about an extensive measurement campaign conducted in Aachen, Germany, comparing indoor-and outdoor measurement results. The highly sensitive measurement system enabled us to measure also man-made or ambient noise. Since an energy detector cannot differentiate such noise from other primary user signals we determine a very high spectrum occupancy in the outdoor scenario in the band from 20 MHz up to 3 GHz. Considerably less occupation was measured in the indoor scenario also because of less ambient noise. Our measurements confirm that the spectrum band 3-6 GHz is rarely occupied. We further provide a case study how the amplitude probability distribution can be used together with detailed regulatory information to infer additional information about the spectral usage. Such information is beneficial in order to optimize the spectrum sensing process and identify candidate bands for further investigation and possible secondary usage.
A voxel-based morphometry study of gray matter in parents of children with autism

Previous structural imaging studies of autistic individuals have identified gray matter abnormalities. It remains unclear, however, which abnormalities contribute to the etiology of autism and, among these abnormalities, which reflect genetic factors. Using voxel-based morphometry, we compared regional gray matter volume in 23 parents of autistic children to an age and sex-matched control sample. We identified relative local gray matter volume increases and decreases in the parent group that are consistent with previous research with autistic individuals. Further, differences were identified in regions that are functionally associated with social-cognitive and motor processes that are impaired in autism. This investigation constitutes the first whole-brain study of regional brain volume in the parents of autistic children, and suggests that a number of structural changes observed in autism may be familial.
Temperature and leaf nitrogen affect performance of plant species at range overlap

Plant growth and survival near range limits are likely sensitive to small changes in environmental conditions. Warming temperatures are causing range shifts and thus changes in species composition within range-edge ecotones; however, it is often not clear how temperature alters performance. Through an observational field study, we assessed temperature and nitrogen effects on survival and growth of co-occurring temperate (Acer saccharum) and boreal (Abies balsamea) saplings across their overlapping range limits in the Great Lakes region, USA. Across sampled ranges of soil texture, soil pH, and precipitation, it appears that temperature affects leaf nitrogen for A. saccharum near its northern range limit (R2 = 0.64), whereas there was no significant leaf N ~ temperature relationship for A. balsamea. Higher A. saccharum leaf N at warm sites was associated with increased survival and growth. Abies balsamea survival and growth were best modeled with summer temperature (negative relationship); performance at warm sites depended upon light availability, suggesting the shade-tolerance of this species near its southern range limits may be mediated by temperature. The ranges of these two tree species overlap across millions of hectares, and temperature and temperature-mediated nitrogen likely play important roles in their relative performance.
Finger Motion Classification by Forearm Skin Surface Vibration Signals

The development of prosthetic hand systems with both decoration and motion functionality for hand amputees has attracted wide research interests. Motion-related myoelectric potentials measured from the surface of upper part of forearms were mostly employed to construct the interface between amputees and prosthesis. However, finger motions, which play a major role in dexterous hand activities, could not be recognized from surface EMG (Electromyogram) signals. The basic idea of this study is to use motion-related surface vibration, to detect independent finger motions without using EMG signals. In this research, accelerometers were used in a finger tapping experiment to collect the finger motion related mechanical vibration patterns. Since the basic properties of the signals are unknown, a norm based, a correlation coefficient based, and a power spectrum based method were applied to the signals for feature extraction. The extracted features were then fed to back-propagation neural networks to classify for different finger motions. The results showed that, the finger motion identification is possible by using the neural networks to recognize vibration patterns.