Whitening Methods Research Articles

Iterative Data-adaptive Autoregressive (IDAR) whitening procedure for long and short TR fMRI.

Functional magnetic resonance imaging (fMRI) has become a fundamental tool for studying brain function. However, the presence of serial correlations in fMRI data complicates data analysis, violates the statistical assumptions of analyses methods, and can lead to incorrect conclusions in fMRI studies. In this paper, we show that conventional whitening procedures designed for data with longer repetition times (TRs) (>2 s) are inadequate for the increasing use of short-TR fMRI data. Furthermore, we comprehensively investigate the shortcomings of existing whitening methods and introduce an iterative whitening approach named "IDAR" (Iterative Data-adaptive Autoregressive model) to address these shortcomings. IDAR employs high-order autoregressive (AR) models with flexible and data-driven orders, offering the capability to model complex serial correlation structures in both short-TR and long-TR fMRI datasets. Conventional whitening methods, such as AR(1), ARMA(1,1), and higher-order AR, were effective in reducing serial correlation in long-TR data but were largely ineffective in even reducing serial correlation in short-TR data. In contrast, IDAR significantly outperformed conventional methods in addressing serial correlation, power, and Type-I error for both long-TR and especially short-TR data. However, IDAR could not simultaneously address residual correlations and inflated Type-I error effectively. This study highlights the urgent need to address the problem of serial correlation in short-TR (< 1 s) fMRI data, which are increasingly used in the field. Although IDAR can address this issue for a wide range of applications and datasets, the complexity of short-TR data necessitates continued exploration and innovative approaches. These efforts are essential to simultaneously reduce serial correlations and control Type-I error rates without compromising analytical power.

Fast sparse Bayesian learning-based seismic resolution enhancement

Seismic high resolution processing plays a crucial role in seismic interpretation and reservoir characterization. However, the low and high frequency of seismic signal are lost owing to the effects of earth filtering and diffraction. The missing of low-frequency increases the energy of wavelet side lobe, which not only enhances the interference with adjacent events, but also lead to side lobe artifacts. High frequency attenuation is more serious, which significantly reduces the seismic resolution. In addition, the current resolution enhancement methods are difficult to achieve desirable result in noise contaminated environment. A novel resolution enhancement method that extends high and low frequencies simultaneously and improves the signal-to-noise ratio (SNR) under the framework of sparse decomposition theory is proposed. Firstly, an over-complete dictionary is constructed using non-zero phase Ricker wavelet and then the effective seismic signal is extracted by sparse decomposition using the fast sparse Bayesian learning (FSBL) algorithm. Secondly, the effective frequency range of the seismic signal is determined through a series of atoms obtained by sparse decomposition. Then, a desired broadband spectrum can be identified depending on this range. By approximating the broadband spectrum of seismic data, the weak high-frequency information can be extended. Furthermore, a correction term is introduced in frequency domain to suppress the side lobes of atoms. The side lobes are well suppressed without distorting the main lobe, meanwhile, both the low and high frequencies are extended. Finally, the validity of this method is verified by synthetic and field data. The results show that this method has better performance than the ordinary deconvolution and spectral whitening methods in processing high resolution data.

ЭКО ОТБЕЛИВАНИЕ, ПЕРСПЕКТИВЫ БУДУЩЕГО

Beautiful, healthy teeth shining with healthy whiteness are an aspect of external attractiveness, success in other areas of life. Teeth whitening is a conservative method of aesthetic dentistry. A snow-white smile has taken a strong position in the beauty industry. However, the most common side effect of whitening is tooth hyperesthesia. Of the 150 patients surveyed, 132 people (88%) resorted to teeth whitening in their lives and only 18 people are categorically against teeth whitening. 59 people (45%) out of 132 teeth whitening patients regularly visit a dentist for professional whitening and selection of home whitening methods, the Phillips Zoom home whitening system. However, there is a category of patients - 73 people (55%) do not go to dental clinics, but use certain methods of home whitening on their own. Most often, they buy Crest whitening strips at the pharmacy, use apple cider vinegar, citric acid, or brush their teeth using ground birch (activated) charcoal. Of these 73 people, fifteen had tooth enamel hyperesthesia after brushing their teeth with birch (activated) charcoal. Therefore, despite the wide range of bleaching agents in the arsenal of a dentist, it seems necessary to develop, test and implement tools and methods for a quick, gentle and financially inexpensive way to whiten teeth. We have proposed an Eco-whitening complex of teeth, consisting of: Molasses, Silicon Dioxide, Sorbitol and White Wax / Gelatin. Eco-whitening complex is presented in the form of a sticker or chewing gum. Preliminary results of using the developed Eco-whitening complex of teeth showed that it does not harm health and the environment (does not require disposal). The teeth of 70% of the subjects, with the time of using this composition, whitened by two tones, the sensitivity did not increase, the tooth enamel was without mechanical damage. The use of the complex does not require adherence to the "white diet". The effectiveness of the developed Eco-whitening complex of teeth has been confirmed. It is easy to use, but not without drawbacks, requires storage in the refrigerator and the shelf life does not exceed 7 days. It is necessary to continue work on the improvement of the Eco-whitening complex of teeth to eliminate the identified shortcomings.

Whitening method for passive water pipeline assessment using ambient noise

Previous studies have verified the feasibility of using ambient noise in water pipeline networks as natural signals to assess pipeline condition passively. This passive technology uses correlation peaks of the ambient noise as characteristics to identify pipe faults and deterioration, and it requires the noise power spectrum density (PSD) to be adequately whitened. However, conventional noise whitening methods cannot provide sufficient whitening for the ambient noise in water pipelines due to the significant noise PSD variations that are unevenly distributed across the wide relative bandwidth of the noise signals. This paper proposes a tailored whitening process for water pipeline ambient noise by applying logarithmic transforms on both the magnitude and frequency axes to compresses the large dynamic range of the PSD magnitude and bandwidth. Numerical simulations and field experiment results have verified that the proposed method can effectively whiten the noise signals in water pipelines, and accurately restore the amplitude of correlation peaks to be consistent with the theoretical derivation using white noise assumptions. The theoretical derivation also reveals the relation between the amplitudes of correlation peaks and the noise spatial distribution, fault distance and its reflection/transmission coefficients. The feasibility of estimating the reflection coefficient of pipe faults from the correlation results with appropriately whitened noise is also investigated in this paper.

Simultaneous denoising and resolution enhancement of seismic data based on elastic convolution dictionary learning

Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancement methods are difficult to yield satisfactory processing outcomes for reservoir characterization. To solve this problem, we develop a new approach for simultaneous denoising and resolution enhancement of seismic data based on convolution dictionary learning. First, an elastic convolution dictionary learning algorithm is presented to efficiently learn a convolution dictionary with stronger representation capability from the noisy data to be processed. Specifically, the algorithm introduces the elastic L1/2 norm as a sparsity constraint and employs a steepest gradient descent strategy to efficiently solve the frequency-domain linear system with substantial computational cost in a half-quadratic splitting framework. Then, based on the learned convolution dictionary, a weighted convolutional sparse representation paradigm is designed to encode the noisy data to acquire an optimal sparse approximation of the effective signal. Subsequently, a high-resolution dictionary with a broadband spectrum is constructed by the proposed parameter scaling strategy and matched filtering technique on the basis of atomic spectrum modeling. Finally, the optimal sparse approximation of the effective signal and the constructed high-resolution dictionary are used for data reconstruction to obtain the seismic signal with high resolution and high signal-to-noise ratio. Synthetic and field dataset examples are executed to check the effectiveness and reliability of the developed method. The results indicate that this method has a more competitive performance in seismic applications compared with the conventional deconvolution and spectral whitening methods.

ДОМАШНЕЕ ОТБЕЛИВАНИЕ, СРАВНИТЕЛЬНАЯ ХАРАКТЕРИСТИКА ВИДОВ (in vitro)

Subject. Mechanical and chemical properties of home whitening products most commonly used by patients.&#x0D; Objectives. Conduct a comparative analysis of the impact of different types of home whitening on tooth enamel (in vitro).&#x0D; Methodology. The study was conducted at the Department of Dentistry, at the Department of Morphology and Pathology (M&amp;P) of the Medical University "Reaviz". The survey of 50 patients aged 18 to 55 years was conducted regarding the use of home whitening types.&#x0D; The results of the impact of home whitening products, listed by patients, on tooth enamel (in vitro) were analyzed: Phillips Zoom, Crest strips, and birch (activated) charcoal (recommended by some patients).&#x0D; Results. The survey of patients showed that out of 50 patients, 44 people resorted to teeth whitening in their lives, this amounted to 88% of the patients surveyed. Of the 44 patients who resorted to teeth whitening, only 20 people (45%) regularly visit a dentist for professional whitening and selection of home whitening methods. As a rule, this is the Phillips Zoom home whitening system. The remaining 24 patients (55%) use home whitening methods on their own: Crest whitening strips, or brush their teeth using ground birch (activated) charcoal.&#x0D; The impact of home whitening products on tooth enamel (in vitro): Phillips Zoom – tooth enamel became lighter by 3 tones and without spots, Crest strips – enamel lightening by only one tone, heterogeneous; birch (activated) charcoal – the enamel became lighter by 1 tone and covered with small scratches.&#x0D; Conclusions. The most effective whitening method for teeth is using Phillips Zoom home whitening methods. The enamel brightened by 3 tones according to the VITA classical shade scale (p &lt; 0.05) and without visible damage.

Various Aspects Involved in the Study of Tooth Bleaching Procedure: A Questionnaire-Based Study.

A beautiful smile is an important feature when it comes to a pleasant appearance of the face, and one of the most common situations that drive patients to book a dental appointment is tooth discoloration. Tooth bleaching is the treatment of choice for extrinsic tooth discoloration, as it is a cheap, fast, and minimally invasive procedure. This study aimed to provide comparative information on the perceptions of both patients and dentists regarding different whitening methods and on the factors involved in people’s willingness to recommend and use a bleaching procedure. In addition to this, this study evaluated the degree of satisfaction in relation to the bleaching methods and materials used; it also evaluated the following: negative side effects, economic characteristics and the patients’ perceptions of the aesthetic appearance of their dental arches, especially tooth color. The subjects that participated in the present study were selected based on their background and were then divided into two categories. The first group consisted of 120 patients who had received tooth-bleaching treatments in dental clinics during the study and the second group consisted of 127 dentists. A conventional sampling method was used. The study aimed to define a relationship between multiple aspects of the tooth-bleaching procedure, including the patients’ desires and their general knowledge of this procedure. Tooth color and the way it changes is a very important factor that motivates patients to come to the dentist for whitening procedures. Patients showed the highest levels of satisfaction with the results of in-office bleaching procedures. In the group consisting of dentists, satisfaction levels were higher for the procedure of home bleaching supervised by a dentist. Factors influencing the choice of bleaching materials are appreciated differently by dentists and patients. Furthermore, the rate of patients using OTC (over the counter) products was found to be high. Further research is needed to find more effective and safer alternatives to home tooth-bleaching procedures.

Preparation and In Vitro Characterization of Gels Based on Bromelain, Whey and Quince Extract.

The growing interest in the appearance and color of teeth has led to the emergence of a wide range of teeth whitening methods, both in dental offices and in patients’ homes. Concerns about the possible side effects or toxic effects of peroxide-based whitening gels leads to the identification of alternative whitening methods, based on natural compounds with mild action on tooth enamel and remineralizing effect. In this context, this study describes the preparation and in vitro analysis of whitening gels based on natural active agents—bromelain, quince and whey—using organic (polyacrylate, polyethylene glycol) and/or inorganic (silicate) excipients. Five natural products gels were prepared, containing bromelain extract, quince extract and whey, in various proportions. Two supplementary gels, one containing Lubrizol and another containing SiO2, were prepared. All gels were submitted for multiple in vitro analysis such as: SDS-PAGE analysis, UV-vis and FTIR spectroscopy, SEM microscopy, antibacterial activity on Streptococcus mutans ATCC 25175, Porphyromonas gingivalis ATCC 33277, Enterococcus faecalis ATCC 29212, Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 25923. The quince extract sample was the only one which completely discolored the blue dye on SDS-PAGE analysis. On the UV-vis spectra, the 303 nm band is assigned to an in situ modified form of bromelain. SEM images of gels containing SiO2 particles show evident marks of these particles, while the rest of the gels containing Lubrizol or whey are more uniform. Regarding antibacterial tests, the SiO2 gel samples did not show inhibition in any strains, but the other tested samples varied in the size of the inhibition diameter depending on the amicrobial strain tested; the protease activity of bromelain modulates the composition of the added whey proteins. Bromelain added as a nanoencapsulated assembly better preserves its integrity. The prepared gels showed antibacterial properties.

Evaluation of Coconut Oil Pulling vs. Whitening Mouthwash as Home Teeth Whitening Methods

Purpose: This study was aimed to evaluate whitening efficacy, tooth sensitivity, and soft tissue irritation of coconut oil pulling as a home whitening method compared to an over-the-counter whitening mouthwash. Material and Methods: A randomized controlled clinical study was done on 60 females at Umm Al-Qura University, Faculty of Dentistry. The participants were divided into two main groups (n=30), to test two whitening agents; Study Group “Coconut Oil Swish” and Control Group “Crest 3D White”. Color measurement was done using the VITA Easyshade® Advance device at three times; the baseline, after one week and after two weeks of whitening. Pain assessment “ tooth sensitivity & soft tissue irritation” was done by utilizing the Pain Rating Scale “Wong-Baker FACES”. Results: The results in this study revealed no significant difference between lightness of the both group but the color differences (ΔE1 & ΔE2) in the Crest 3D White (control group) were scientifically higher than in the Coconut Oil Swish (study group). Regarding the pain assessment, a significant difference in pain scores was found between the two groups as Coconut Oil Swich (study group) recorded lower pain score than Crest 3D White (control group). Conclusion: Although the Coconut oil pulling revealed a whitening efficacy after two weeks of use; the whitening mouthwash that contains 1.5% hydrogen peroxide recorded higher color change at one- or two-weeks use. Coconut oil pulling causes less tooth sensitivity and/or soft tissue irritation during regular use when compared to the whitening mouthwash that contains 1.5% hydrogen peroxide.

Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMGσ).

Previous works have shown that whitening improves the processed electromyogram (EMG) signal for use in end applications such as EMG to torque modelling. Traditional whitening methods fit each subject from calibration contractions, which is a hindrance to their widespread use. To eliminate this cumbersome calibration, a universal whitening filter was developed using the whitening filters from a pre-existing data set (64 subjects, 8 electrodes/subject). Since the shape of each subject-specific whitening filter was observed to be relatively consistent across subjects, the universal whitening filter was formed as their ensemble average. The processed EMG was then used to model surface EMG to torque about the elbow. Traditional and universal whitening provided the same EMG-torque benefit, each improving statistically over unwhitened processing by ~14% during dynamic contractions. We further studied the use of root difference of squares (RDS) post-processing to attenuate additive measurement noise in EMG channels. With and without whitening, RDS processing (vs. no RDS processing) better attenuated additive noise, reducing it from 2-4% (on average) of the processed EMG from a 50% contraction down to < 1%. The combined use of universal whitening filters and RDS processing should be a particular benefit in real-time applications such as prosthesis control.

A Critical Review of Modern Concepts for Teeth Whitening.

Besides prevention of caries and periodontitis, an increasing number of oral care products focus on teeth whitening. The aim of this review is to summarize and discuss frequently used whitening agents and their efficacy from a chemical viewpoint. Therefore, a comprehensive literature survey on teeth whitening agents and products was conducted. The current whitening methods are analyzed and discussed from a chemist’s viewpoint. Frequently used whitening agents are abrasives (mechanical removal of stains), antiredeposition agents (prevention of deposition of chromophores), colorants (intended to lead to a white color), proteases (degradation of proteins), peroxides (oxidation of organic chromophores), and surfactants (removal of hydrophobic compounds from tooth surface). In-office bleaching using peroxides is effective, but side effects like tooth sensitivity or a damage of the natural organic matrix of enamel and dentin may occur. The applicability of abrasives in teeth whitening is limited due to potential tooth wear, especially when toothpastes with high RDA values are used. The effect of other whitening agents in vivo is often unclear because of a shortage of placebo-controlled clinical trials.

Effect of home care whitening methods on surface roughness of low shrinkage composite (in vitro study)

Effect of home care whitening methods on surface roughness of low shrinkage composite (in vitro study)

Estimation and application of EMG amplitude during dynamic contractions.

The sections above have described an EMG amplitude estimator and an initial application of this estimator to the EMG-torque problem. The amplitude estimator consists of six stages. In the first stage, motion artifact and power-line interference are attenuated. Motion artifact is typically removed with a highpass filter. Elimination of power-line noise is more difficult. Commercial systems tend to use notch filters, accepting the concomitant loss of "true" signal power in exchange for simplicity and robustness. Adaptive methods may be preferable, however, to preserve more "true" signal power. In stage two, the signal is whitened. One fixed whitening technique and two adaptive whitening methods were described. For low-amplitude levels, the adaptive whitening technique that includes adaptive noise cancellation may be necessary. In stage three, multiple EMG channels (all overlying the same muscle) are combined. For most applications, simple gain normalization is all that is required. Stage four rectifies the signal and then applies the power law required to demodulate the signal. In stage six, the inverse of the power law is applied to relinearize the signal. Direct comparison of MAV (first power) to RMS (second power) processing demonstrates little difference between the two. Therefore, unless there is reason to believe that the EMG density departs strongly from that found in the existing studies, RMS and MAV processing are essentially identical. In stage five, the demodulated samples are averaged across all channels and then smoothed (time averaged) to reduce the variance of the amplitude estimate, but at the expense of increasing the bias. For best performance, the window length that best trades off variance and bias error is selected. The advanced EMG processing was next applied to dynamic EMG-torque estimation about the elbow joint. Results showed that improved EMG amplitude estimates led to improved EMG-torque estimates. An initial comparison of different system-identification techniques and model orders was reported. It is expected that these advanced processing and identification algorithms will also improve performance in other EMG applications, including myoelectrically controlled prostheses, biofeedback, and ergonomic assessment.

Spatial evolutionary spectrum for DOA estimation and blind signal separation

We combine the concepts of evolutionary spectrum and array processing. We present a cross-power stationary periodogram for both direction-of-arrival (DOA) estimation and blind separation of nonstationary signals. We model the nonstationary signals received by each array sensor as a sum of complex sinusoids with time-varying amplitudes. These magnitudes carry information about the DOA that may also be time-varying. We first estimate the time-varying amplitudes using estimators obtained by minimizing the mean-squared error. Then using the estimated time-varying amplitudes, we estimate the evolutionary cross-power distributions of the sensor. Next, using cross-power estimates at time-frequency points interest, we estimate the DOAs using one of the existing methods. If the directions are time varying, we choose time-frequency points around the time of interest to estimate spontaneous source locations. If the sources are stationary, time-frequency points of interest can be combined for the estimation of fixed directions. Whitening and subspace methods used to find the mixing matrix and separate nonstationary signals received by the array. We present examples illustrating the performance of the proposed algorithms.

A noninvasive shallow seismic source comparison on the Oak Ridge Reservation, Tennessee

Nine seismic sources were compared in preparation for production seismic reflection profiling to about 500 m depth at a hazardous waste site on the Oak Ridge Reservation, Tennessee. Test data provided a 125-shotpoint common midpoint profile and a walkaway vertical seismic profile for each source. Sources tested included five swept sources and four impulsive sources. Eight of the sources were “noninvasive,” in that they would not penetrate the ground surface. When spectral whitening methods were applied to the data, the IVI Minivib provided the best image of the subsurface on the basis of continuity and clarity of reflections. Without prewhitening, the performance of the IVI Minivib and the Bison elastic wave generator were similar.

Cancellation of polarized impulsive noise using an azimuth-dependent conditional mean estimator

The separation of signals from noisy vector measurements is obtained by taking advantage of the Middleton Class A model of noise amplitude and the correlation of the components of the noise process due to their polarization. The signal is assumed to be white Gaussian. Noise is a superposition of M non-Gaussian processes, each with a fixed azimuth of polarization. Neither the number of processes (M) nor their azimuths are known. The separation of signal from noise is based on the conditional mean estimators. In addition to the optimum estimator, which can be derived from a knowledge of the bivariate density functions, two suboptimum solutions for polarized noise are discussed: the circularly symmetric estimator and the azimuth-dependent one. Circular symmetry is suitable for the nonpolarized noise vector, whereas the azimuth-dependent estimator is tailored to polarized noise. The azimuth-dependent approach consists of two steps: first, the data vector process is discretized into azimuth sectors, and then, in those classified as noisy, the signal is separated from the noise. Statistical model parameters of random processes are estimated by using the optimum classification, based on the likelihood ratio test (decision-directed method). Iterative whitening methods are also discussed for correlated vector signals. Numerical examples show the effectiveness of the above technique in canceling polarized noise.