Masking Components Research Articles

A New Image Simulation Technique for Deep-Learning-Based Radar Target Recognition

Radar target recognition via deep learning has been an active research area recently. However, this family of methods depends on the quality of radar images and the number of training samples. Given limited training samples of poor quality, these methods will cause severe overfitting. To solve this problem, this paper proposes a new method combining the physical model and deep learning. A new radar measurement simulation technique is presented. The radar measurements are first modeled by the attributed scattering center model. The target is reconstructed by the estimated model parameters. The corresponding residual is formed simultaneously. The reconstructed target and the residual are then frozen. A mask with random shape is imposed on the frequency data. The masked components are reset accordingly. The resulting data are combined and transformed from the frequency domain into the image domain. The new radar measurement can be then generated via the re-imaging process of target. We aim to simulate the unforeseen disturbances during data collection. The simulated radar measurements are used to improve the learning efficiency of deep models under limited sample environments. Multiple comparative studies are performed to demonstrate the advantages of the proposed method.

Degron masking outlines degronons, co-degrading functional modules in the proteome

Effective organization of proteins into functional modules (networks, pathways) requires systems-level coordination between transcription, translation and degradation. Whereas the cooperation between transcription and translation was extensively studied, the cooperative degradation regulation of protein complexes and pathways has not been systematically assessed. Here we comprehensively analyzed degron masking, a major mechanism by which cellular systems coordinate degron recognition and protein degradation. For over 200 substrates with characterized degrons (E3 ligase targeting motifs, ubiquitination sites and disordered proteasomal entry sequences), we demonstrate that degrons extensively overlap with protein-protein interaction sites. Analysis of binding site information and protein abundance comparisons show that regulatory partners effectively outcompete E3 ligases, masking degrons from the ubiquitination machinery. Protein abundance variations between normal and cancer cells highlight the dynamics of degron masking components. Finally, integrative analysis of gene co-expression, half-life correlations and functional relationships between interacting proteins point towards higher-order, co-regulated degradation modules (‘degronons’) in the proteome.

Laboratory changes inherent to acute kidney injury induced by aminoglycosides in wistar rats

Abstract Acute kidney injury (AKI) is defined as an increase greater than 0.3 mg/L of serum creatinine within 48 hours and is a major cause of death in patients in intensive care units. Twenty-four Wistar rats were divided into three groups: Control (0.9% saline), Genta (gentamicin 50 mg.kg-1 BID) and Deh+Genta (gentamicin 50 mg.kg-1 BID + water restriction) and tested in an AKI model by aminoglycoside administration and dehydration implementation. The animals in the Deh+Genta group exhibited the lowest average weight and feed intake after the fifth day of the experiment. In this same period, water consumption by the Genta group was lower than the Control group, but in the following days of the experiment, polydipsia was noted for this group. The Deh+Genta group displayed the highest mean serum urea after the fifth day. The gentamicin-treated groups exhibited higher means than the Control group for serum creatinine, which proved to be a late renal marker for AKI. Serum GGT was higher in the Deh+Genta group, whereas urinary GGT was higher in the groups that received gentamicin, characterizing enzymuria, although severe dehydration can mask the results by indicating false negative values. The urinary GGT enzyme did not act as an early AKI biomarker. Decreased glomerular filtration rates enhanced the concentration of blood components and masked urinary and tissue components.

Стегоанализ цифровых изображений с использованием глубоких нейронных сетей и гетероассоциативных интегральных преобразований

The problem of steganalysis of digital images is considered. The proposed approach is based on the use of deep convolutional neural networks with a relatively simple architecture, distinguished by the use of additional layers of special processing. These networks are trained and used for steganalysis of small fragments of the original large images. For the analysis of full sized images, it is proposed to carry out secondary post-processing, which involves combining the obtained classification results in blocks as a sequence of binary features according to the scheme of a naive Bayesian classifier. We propose to use integral heteroassociative transformations that provide the selection of the estimated and stochastic (masking) components on the processed image fragment based on the forecast model of one part of the fragment in relation to another to identify violations of the structural and statistical image properties after message embedding. Such transformations are included in the architecture of trained neural networks as an additional layer. Alternative versions of deep neural network architectures (with and without an integral layer of heteroassociative transformation) are considered. The PPG-LIRMM-COLOR images base was used to create data sets. Experiments have been carried out for several well-known stego algorithms (including the classic block and block-spectral algorithms of Kutter, Koha - Zhao, modern algorithms EMD, MBEP and algorithms for adaptive spatial steganography WOW and S-UNIWARD) and for the stego algorithms based on the use of heteroassociative compression transformations. It is shown that the accuracy of steganalysis obtained when implementing the proposed information processing schemes for large images with relatively low computational costs is comparable to the results obtained by other authors, and in some cases even exceeds them.

Multi-Area State Estimation: A Distributed Quasi-Static Innovation-Based Model with an Alternative Direction Method of Multipliers

In the modern power system networks, grid observability has greatly increased due to the deployment of various metering technologies. Such technologies enhanced the real-time monitoring of the grid. The collection of observations are processed by the state estimator in which many applications have relied on. Traditionally, state estimation on power grids has been done considering a centralized architecture. With grid deregulation, and awareness of information privacy and security, much attention has been given to multi-area state estimation. Considering such, state-of-the-art solutions consider a weighted norm of residual measurement model, which might hinder masked gross errors contained in the null-space of the Jacobian matrix. Towards the solution of this, a distributed innovation-based model is presented. Measurement innovation is used towards error composition. The measurement error is an independent random variable, where the residual is not. Thus, the masked component is recovered through measurement innovation. Model solution is obtained through an Alternating Direction Method of Multipliers (ADMM), which requires minimal information communication. The presented framework is validated using the IEEE 14 and IEEE 118 bus systems. Easy-to-implement model, build-on the classical weighted norm of the residual solution, and without hard-to-design parameters highlight potential aspects towards real-life implementation.

Selective attention modulates neural envelope tracking of informationally masked speech in healthy older adults.

Speech understanding in noisy situations is compromised in old age. This study investigated the energetic and informational masking components of multi‐talker babble noise and their influence on neural tracking of the speech envelope in a sample of healthy older adults. Twenty‐three older adults (age range 65–80 years) listened to an audiobook embedded in noise while their electroencephalogram (EEG) was recorded. Energetic masking was manipulated by varying the signal‐to‐noise ratio (SNR) between target speech and background talkers and informational masking was manipulated by varying the number of background talkers. Neural envelope tracking was measured by calculating temporal response functions (TRFs) between speech envelope and EEG. Number of background talkers, but not SNR modulated the amplitude of an earlier (around 50 ms time lag) and a later (around 300 ms time lag) peak in the TRFs. Selective attention, but not working memory or peripheral hearing additionally modulated the amplitude of the later TRF peak. Finally, amplitude of the later TRF peak was positively related to accuracy in the comprehension task. The results suggest that stronger envelope tracking is beneficial for speech‐in‐noise understanding and that selective attention is an important ability supporting speech‐in‐noise understanding in multi‐talker scenes.

Community-Based Production of Quality Face Masks for Personal Protection During the COVID-19 Pandemic.

The authors developed a process to produce a reliably fitting face mask from materials that were immediately available to health care workers, to reduce the risk of infection. Multiple materials and designs were developed to produce face masks that focused on ease of production, the ability to generate a reliable facial seal, and the ability to tailor the mask for those who did not fit commercially available N95 masks. Two final designs were selected. Mask components were assembled into kits and distributed to community sewists. Plan-Do-Study-Act cycles were developed for quality improvement. A process was successfully developed to produce 5000 face masks in a period of 3 weeks that fit almost all (95%) health care workers who did not fit in a commercially available mask. The process was able to produce quality face masks with specific attention paid to developing masks that would pass qualitative fit testing.

Adaptive Reverberation Absorption Using Non-Stationary Masking Components Detection for Intelligibility Improvement

This letter proposes a new time domain absorption approach designed to reduce masking components of speech signals under noisy-reverberant conditions. In this method, the non-stationarity of corrupted signal segments is used to detect masking distortions based on a defined threshold. The nonstationarity is objectively measured and is also adopted to determine the absorption procedure. Additionally, no prior knowledge of speech statistics or of the room information is required for this technique. Three intelligibility measures (ESII, ASIIST, SRMRnorm) and a perceptual listening test are used for evaluation. The experiments results show that the proposed scheme leads to a higher intelligibility improvement when compared to competing methods.

Matricryptic peptide-inspired hydrogels for promoting osteogenic differentiation

ABSTRACTIn the natural process of bone repair, matricryptic peptides were activated by up-regulated ECM-degrading enzymes and properly released at bone injury sites, which plays critical roles in bone self-healing. Inspired by this natural process, here, matricryptic peptide-inspired (MPI) hydrogels were designed to promote osteogenic differentiation. MPI hydrogels can be degraded by enzymes and during this time, the masked bioactive components were released to promote osteogenic differentiation. These MPI hydrogels which normally serve as structural support for cell proliferation while promote osteogenic differentiation using embedded osteogenic BFP-1 peptides after degradation may provide a novel design for bone regeneration materials.

Joint High-Order Synchrosqueezing Transform and Multi-Taper Empirical Wavelet Transform for Fault Diagnosis of Wind Turbine Planetary Gearbox under Nonstationary Conditions.

Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.

Recognition of synthesized vowel sequences in steady-state and sinusoidally amplitude-modulated noises.

Modulation masking is known to impact speech intelligibility, but it is not clear whether the mechanism underlying this phenomenon is an invariant, bottom-up process, or if it is subjected to factors such as perceptual segregation and stimulus uncertainty thereby showing a top-down component. In the main experiment of the current study (Exp. II), listeners' ability to recognize sequences of synthesized vowels (i.e., the target) in sinusoidally amplitude-modulated noises (i.e., the masker) was evaluated. The target and masker were designed to be perceptually distinct to limit the top-down component of modulation masking. The duration of each vowel was either 25 or 100 ms, the rate at which the vowels were presented was either 1 or 6 Hz, and the masker modulation rate was varied between 0.5 and 16 Hz. The selective performance degradation when the target and masker modulation spectra overlap, as would be expected from modulation masking, was not observed. In addition, these results were able to be adequately captured using a model of energetic masking without any modulation processing stages and fitted only using the vowel-recognition performance in steady-state maskers, as obtained from Exp. I. Results suggest that speech modulation masking might not be mediated through an early-sensory mechanism.

Additivity of masking at the cocktail party

Multi-talker listening environments, like crowded restaurants, are highly complex. In addition to the target talker, the auditory scene may consist of a combination of one or two interfering talkers close to a listener that would likely be relatively high in level (e.g., from people at the same or a nearby table) and numerous additional masking talkers at greater distances whose outputs reach the listener at lower levels. Our understanding of how these masking components combine is limited by the fact that most studies of multi-talker listening present all interfering talkers at the same level. The current study explored the extent to which error rates in a speech understanding task could be predicted from the error rates for two individual components of the masker, specifically from (a) two higher-level (closer) talkers and (b) four lower-level (more distant) talkers. The variables of angular location and level difference of the “closer” and “farther” talkers were explored. At least for an initial subset...

From macroscopic to microscopic glimpse-based models of intelligibility prediction

Miller and Licklider's explorations of the intelligibility of temporally interrupted speech, and later studies extending their findings to the spectro-temporal plane, have shown how the twin factors of sparseness and redundancy confer a high degree of robustness on speech in noise. The current contribution addresses two questions. First, to what extent can quantitative estimates of supra-threshold unmasked speech account for average (macroscopic) intelligiblity across a range of speech styles and masking conditions? We examine how well glimpse-based objective intelligibility metrics predict listeners' speech recognition scores for natural and synthetic speech in the presence of stationary and fluctuating maskers, and demonstrate reduced correlations for competing sources with an informational masking component. The second question concerns which additional components, beyond speech glimpses, are required to make (microscopic) predictions of actual listener confusions at the level of individual noisy speech tokens. Using corpora of speech-in-noise misperceptions, we show that in many cases the source of listener confusions is the misallocation of information from the masker, suggesting that estimates of supra-threshold unmasked speech alone are insufficient to explain speech intelligibility in noise.

Functional magnetic resonance imaging of pain-related brainstem nuclei in single subjects at 7 Tesla

Background The function or dysfunction of pain-related nuclei in the brainstem has only been scarcely studied in humans due to the lack of non-invasive measurement methods. The performance of functional magnetic resonance imaging (fMRI), a standard non-invasive technique, is hampered by the close vicinity of the brainstem to large arteries and ventricles as well as its propensity to spatial distortions caused by the oral cavity. Furthermore, the small average size of brainstem nuclei necessitates higher spatial resolution and accuracy than in studies of the cortex. Here, we present a new approach based on ultra-high field fMRI acquisition at 7 Tesla and a brainstem-optimized analysis method (mICA), which we apply to study pain-related activity and connectivity of brainstem nuclei in single subjects. Methods Following a multi-modal imaging approach based entirely on echo-planar imaging, we acquired distortion matched functional, T1-weighted structural as well as diffusion-weighted images at a resolution of 1.2 mm isotropic. Five 6 min runs of resting-state fMRI were acquired, during two of which subjects received a continuous pressure pain stimulus applied to their lower leg by an inflatable cuff. Results Pain intensity was percept matched at 50/100 points on a visual analogue scale. Applying our recently developed mICA approach (masked independent component analysis), we were able to detect reproducible resting-state activity for specific brainstem nuclei, like the cuneiform nuclei, periaqueductal grey and as well as brainstem-cortex functional connectivity at the single-subject level. We identified a number of pain-related nuclei that showed distinctive activity changes during pain stimulation. Conclusions Identification of nuclei was greatly aided by fractional anisotropy (FA) maps created from the diffusion data. Finally, assessing activity and functional connectivity of brainstem nuclei on the single-subject level may soon give us a deeper understanding of disease subtypes, individual differences in pain processing, as well as other functions localized in the brainstem.

Animation in Transition: A semiotic reading of Ase Mmanwu Masquerade Costume in Performance.

The study takes a critical look at costume in motion. Motion or movement here imposes on costume the image of a living object and as such a composition drawn on a symbiotic relationship between anarticle of material culture and an animator; usually a human factor. This thus infers that, it is in the conjugal relationship of performer and costume that the performancecostume attains full realization and finally, a scaling up in its utility value. The study addresses critically, the Ase Mmanwu costume in performance. As tool to aid artistic exhibition, the Mmanwu costume in performance comes alive as a rich semiotic field explored for signification in the Ase Mmanwu art. The brand, embodied in spatial movements and convolutions, creates and imposes strictly the image of an animated and highly reflexive object which lingers in the consciousness of its beholder(s) long after its perception. With special interest in the masking components of Ase Mmanwu tradition, this discourse is restricted to the animated and antiquated costume of theMmanwumasquerade of Ase people of Nigeria.

Scene masking is affected by trial blank-screen luminance

The current study investigated the role of the inter-screen luminance contrast (ISLC) of trial blank screens between target and mask screens in visually masking scenes. Participants performed a scene gist recognition task in which we varied mask strength, blank screen luminance, and stimulus onset asynchrony (SOA). Results showed that the more luminant white, and less luminant black, blank screens produced greater masking than intermediate luminance gray blank screens adjusted to the mean luminance of the target screens, specifically for black screens at SOAs<36ms and for white screens at all SOAs. Our findings suggest that researchers interested in controlling for ‘extraneous factors’ should use gray blank screens as they eliminate any contribution of the ISLC component of masking. However, researchers interested in creating and examining differences in processing at early SOAs (<36ms) should use black blank screens as these were shown to increase variation in the SOA function.

Novel masking effects of light are revealed in Drosophila by skeleton photoperiods

Here, we show that in a skeleton photoperiod where all midday light is removed from a standard laboratory 12:12 LD photoperiod, a large diurnal peak of activity is revealed that is continuous with the E peak seen in constant dark (DD). We further show that the circadian clock gene tim regulates light-dependent masking of daytime activity, but the clock gene per does not. Finally, relative to wild-type flies, mutants for both of these clock genes showed increased nighttime activity in the skeleton photoperiod but not in the standard photoperiod. This result suggests that nighttime activity is suppressed by the intact circadian clock, and in its absence, by exposure to a standard photoperiod. These results support and extend the literature addressing the complex interactions between masking and clock-controlled components of overt circadian rhythms.

Exploring facial emotion perception in schizophrenia using transcranial magnetic stimulation and spatial filtering

Schizophrenia patients have difficulty extracting emotional information from facial expressions. Perception of facial emotion can be examined by systematically altering the spatial frequency of stimuli and suppressing visual processing with temporal precision using transcranial magnetic stimulation (TMS). In the present study, we compared 25 schizophrenia patients and 27 healthy controls using a facial emotion identification task. Spatial processing was examined by presenting facial photographs that contained either high (HSF), low (LSF), or broadband/unfiltered (BSF) spatial frequencies. Temporal processing was manipulated using a single-pulse TMS delivered to the visual cortex either before (forward masking) or after (backward masking) photograph presentation. Consistent with previous studies, schizophrenia patients performed significantly below controls across all three spatial frequencies. A spatial frequency by forward/backward masking interaction effect demonstrated reduced performance in the forward masking component in the BSF condition and a reversed performance pattern in the HSF condition, with no significant differences between forward and backward masking in the LSF condition. However, the group by spatial frequency interaction was not significant. These findings indicate that manipulating visual suppression of emotional information at the level of the primary visual cortex results in comparable effects on both groups. This suggests that patients' deficits in facial emotion identification are not explained by low-level processes in the retino-geniculo-striate projection, but may rather depend on deficits of affect perception occurring at later integrative processing stages.

Binocular energy response based quality assessment of stereoscopic images

Perceptual quality assessment in three-dimensional (3D) is challenging. In this research, we propose a binocular energy response based quality assessment metric of stereoscopic images. To be more specific, we first construct binocular energy responses of the original and distorted images, and measure the similarity between them as Image Quality Metric (IQM). Then, the binocular response and the binocular masking components are used to modulate the IQM, respectively. Finally, two evaluation results are nonlinearly integrated into an overall score by considering the importance of each component. Experimental results show that compared with the relevant existing metrics, the proposed metric can achieve higher consistency with the subjective assessment of stereoscopic image.

Lactoferrin directly scavenges hydroxyl radicals and undergoes oxidative self-degradation: a possible role in protection against oxidative DNA damage.

In this study, we examined the protective effect of lactoferrin against DNA damage induced by various hydroxyl radical generation systems. Lactoferrin (LF) was examined with regard to its potential role as a scavenger against radical oxygen species using bovine milk LF. Native LF, iron-saturated LF (holo-LF), and apolactoferrin (apo-LF) effectively suppressed strand breaks in plasmid DNA due to hydroxyl radicals produced by the Fenton reaction. In addition, both native LF and holo-LF clearly protected calf thymus DNA from fragmentation due to ultraviolet irradiation in the presence of H2O2. We also demonstrated a protective effect of all three LF molecules against 8-hydroxydeoxyguanosine (8-OHdG) formation in calf thymus DNA following ultraviolet (UV) irradiation with H2O2. Our results clearly indicate that native LF has reactive oxygen species-scavenging ability, independent of its nature as a masking component for transient metals. We also demonstrated that the protective effect of LF against oxidative DNA damage is due to degradation of LF itself, which is more susceptible to degradation than other bovine milk proteins.