Fourier-transform Spectra Research Articles

Acoustic characteristics of bamboo-based guitar – A case study

Bamboo is a fast-growing plant easily obtained in Malaysia. It is commonly used for constructing various solid structures including the guitar. Its unique sound quality makes it different from the traditional wooden guitar. The Yamaha guitar sound was used as reference for the generally preferred guitar characteristics. This work focused on the acoustic characteristics easily obtained using the frequency spectrum analysis via a PicoScope oscilloscope and spectrogram using Adobe Audition. A microphone was used for recording the string sound and yielding the frequency response function. The Fast Fourier Transform (FFT) spectra showed that the Yamaha guitar had less partials compared to the bamboo guitar, except string 4. Strings 1, 2, and 3 showed a regular signal from the Yamaha guitar whereas the bamboo guitar showed an irregular pattern with significant overtone. The intensity of the partials in the bamboo guitar displayed a recognizable pattern, i.e., a reduction of partial intensity amplitude proportional to increasing frequency in strings 4, 5, and 6. Some random partials appeared between the harmonics in string 1, 2, and 3 from bamboo guitar whereas the absence of partials in the Yamaha guitar could be due to the higher radiation coefficient of wood, which displays a different timbre.

Development and Testing of a Fast-Acting, 8-Bit, Digital Throttle for Hybrid Rocket Motors

The potential for throttle control of hybrid rocket systems has long been known as a potential advantage for a variety of applications. Because only a single flow path is controlled, theoretically, hybrids should be significantly easier to throttle than bipropellant systems. Unfortunately, the slow response times and nonlinearity of traditional position-control valves have limited practical applications of hybrid throttling. This paper presents an alternative throttling system where the oxidizer flow path is broken into multiple streams, with each flow path controlled by a solenoid-operated on/off valve. The parallel paths allow significantly faster and more precise control than can be achieved using a single position-control valve. The achievable thrust levels are limited only by the size and number of components in the valve cascade. The 8-bit digital throttle system, developed by Utah State University’s Propulsion Research Lab, uses commercial, off-the-shelf components. The throttle system was tested using a 200-N hybrid rocket motor, burning gaseous oxygen, and ABS plastic as propellants. The testing campaign of more than 50 hot fires has demonstrated multiple profiles, including deep throttle ramps, multistep boxcars, and sine waves at frequencies varying from 0.25 to 1-Hz. Comparisons to analytical models are also presented, showing good agreement. Fourier-transform spectra demonstrating the total-system, frequency response are also presented.

Deep CNN for Parkinson’s Disease Classification Using Line Spectral Frequency Images of Sustained Speech Phonation

It is proposed to use Deep Convolution Neural Network (DCNN) which is a good classifier of natural images to learn speech spectrum images of sustained phonation to detect Parkinson’s Disease (PD) as an alternative to the existing feature-based machine learning method. It is shown that the proposed method yields very high accuracy without the need for separate feature computation stage. The speech spectrum representations proposed are Short Time Fourier Transform (STFT) spectrum of size Nx256 and Line Spectral Frequency (LSF) spectrum of size Nx16. LSF reflects the speech production mechanism and it is a novel idea to use LSF spectrum in DCNN to detect PD speech. The spectrum images look like random patterns and the performance is improved when using an additional deeper hidden layer of tampering pattern in the last stage of a fully connected layer. Using a standard PD-sustained phonation dataset the training accuracies achieved are 98.50% and 92.50% for STFT and LSF method, respectively. The validation accuracies achieved are 84.38% for STFT and 100% for LSF. The STFT method results in a sensitivity of 97.05%, a specificity of 88.63%, a precision of 86.84%, an F1-score of 91.66, a false positive rate (FPR) of 11.36%, and a false alarm rate of 12.82%. The LSF method results in a sensitivity 97.05%, a specificity of 95.45%, a precision of 94.28%, an F1-score of 95.65, an FPR of 4.50%, and a false alarm rate of 5.71%. The LSF based method performs better and the performance comparison with the state-of-the-art methods brings out the merits of the LSF spectrum image-based DCNN learning in PD detection using sustained phonation.

First Ab Initio Line Lists for Triatomic Sulfur-Containing Molecules: S2O and S3.

We present in this paper the first room temperature rovibrational line lists for the main isotopologues of disulfur monoxide (S2O) and thiozone (S3) variationally computed from newly developed ab initio potential energy and dipole moment surfaces (PESs and DMSs). S2O and S3 are supposed to be potential candidates for astronomical detection, especially in the Venusian atmosphere where sulfur chemistry plays a major role. Contrary to other stable sulfur-containing species like SO2 or H2S, there is much less experimental data for the short-lived reactive S2O and S3 molecules. Indeed, the infrared spectra of S2O and S3 are quite complicated to analyze without consistent theoretical predictions because they contain both high J (∼100) and a lot of hot band transitions, even at T = 296 K. In this work, we have constructed PESs based on the single-reference coupled cluster approach [CCSD(T)] and including corrections due to the scalar relativistic effects, DBOC, and highly excited Slater determinants. The structure of the excited electronic states of S3 was also discussed. The nuclear-motion Eckart-Watson Hamiltonian expressed in terms of normal-mode irreducible tensor operators was used to compute the energy levels. For line intensity calculation, ab initio DMSs were computed at the CCSD(T)/aug-cc-pV5Z level of the theory. Rotation-vibration patterns in the fundamental bands of S2O and S3 have been simulated taking into account the recent Fourier-transform spectra of S2O recorded at the SOLEIL synchrotron. The present work aims at providing line intensities of S2O and S3 that are missing in the literature as well as new spectroscopic support for atmospheric applications.

Application of Odd-Order Derivatives in Fourier Transform Nuclear Magnetic Resonance Spectroscopy toward Quantitative Deconvolution.

When Fourier transform (FT) spectrum peaks are overlapped, primary maxima of odd-order derivatives can be used to evaluate their independent intensities. We studied the feasibility of higher odd-order derivatives on Lorentzian peak shape and magnitude peak shape. Simulation studies for FT nuclear magnetic resonance (NMR) spectroscopy demonstrated good results toward quantitative deconvolution of overlapping FT spectrum peaks. Although it is not so desirable to deconvolute special line shapes such as Gaussian, Voigt, and Tsallis profiles, the odd-order derivatives exhibit a bright future compared to even-order derivatives. An application example of practical NMR spectroscopy with ethylbenzene isomers is presented. White Gaussian noises were added to the simulated spectra at two different signal-to-noise ratios (20 and 40). Kauppinen's denoising and smoothing algorithms can effectively remove interference of the noise and help to have good deconvoluting results using the odd-order derivatives. We compared features of our approach with popular deconvolution sharpening algorithms and conducted a comparison study with Kauppinen's Fourier self-deconvolution. Our approach has a better dynamic range of peak intensities and is not sensitive to the sampling rates. Other common deconvolution methods are also discussed briefly.

High precision in a Fourier-transform spectrum of protactinium: extensive weighted least-squares fits of peak wavenumbers for analysis of fine and hyperfine structure

A Fourier-transform recording of protactinium in the infrared range is reanalysed with high precision in order to determine the hyperfine interaction constants A and B. Starting with a selection of best lines and least-squares fits of hyperfine structure intervals, large systems of linear equations compare experimental hyperfine peak wavenumbers with a theoretical representation. The theoretical representation is based on Ritz’s combination principle and Casimir’s formula according to the existing classification. Weighted least-squares fits allow a discrimination between unperturbed and perturbed data such as blended hyperfine structure components. For the first time, the wavenumbers of the hyperfine components of more than 600 lines are fitted using the characteristics of about 250 levels as parameters. 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Standard errors around 0.1 ×10-3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes 10^{-3}$$\\end{document} cm-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document} for the A constants and 10-3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-3}$$\\end{document} cm-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{-1}$$\\end{document} for the B constants and the fine structure energies are achieved. Representative examples illustrate extensive results obtained for atomic protactinium. This high precision facilitates further search for new energy levels, and 20 new levels were presented. Foreword The data presented here are the results of a study carried out at the Laboratoire Aimé Cotton (LAC) at Paris-Orsay in the years 2003 and 2004, when I was there for a research stay. At this time, I worked together with Jean-François Wyart and Annie Ginibre on the re-examination of protactinium spectra that have been measured about 30 years earlier and that were available in the form of a printed list of peak wavenumbers and a printed paper chart of the intensity profile. The spectra had already been analysed, but there was still a lot of additional information that could be extracted from the spectra with time and effort. The review of the data, the selection of the data and the step-by-step optimization of the data set took a lot of time. When I returned to Berlin in 2004, we had made good progress, but in principle, it is like a bottomless pit. We continued together to optimize the data and tried to the finishing touches to it. At some point, we decided that we had reached a ‘level of maturity’ where the data could be published. We have discussed a lot about how detailed the text should be. This discussion has dragged on over the years and this project has repeatedly been lost in the stream of other everyday tasks. Every now and then there was a small attempt to return to this topic, but it quickly got lost in the daily hustle and bustle. In 2012, we presented the results at a conference. The death of both of them within two years hit me hard. I very much regret that this work was not published earlier. This special volume was the right motivation for me to finally publish this data. I no longer have access neither to the computer programs used at the time, which ran on large computer systems, nor to the original measurement data. I have not been able to find out what happened to the large quantity of paper (printed list of peak wavenumbers anda printed paper chart of spectra). But I have a bunch of input and output files of the calculations that have become a bit jumbled over the years, which contain a lot of information, as well as our unfinished manuscript. The resulting data contain important information for posterity – particularly since the element is radioactive and the experiments to collect laboratory data are unlikely to be repeated any time soon. I think it is worth publishing these data.Graphic abstractHigh precision FT spectra of Pa: analysis of fine and hyperfine structure

Hyperfine Structure Investigation of Singly Ionized Thulium in Fourier-transform Spectra

The hyperfine structure of 40 spectral lines of singly ionized thulium (Tm ii) in emission spectra from a hollow cathode discharge lamp measured with a Fourier transform spectrometer in the wavelength range from 335 to 2345 nm has been investigated. As a result of the analysis, the magnetic dipole hyperfine structure constants A for 27 fine structure levels of Tm ii were determined for the first time. In addition, the values of two magnetic dipole hyperfine structure constants A from the literature were declared incorrect, and the corrected values were given.

Investigation of super-resolution in microsphere-assisted microscopy with the Poynting vector of the dipole model.

In this paper, the Fourier spectrum of an image in microsphere-assisted microscopy (MAM) and the wavenumber decomposition of the Poynting vector of the dipole model are compared for the first time to study the super-resolution performance within several wavelengths in MAM. Firstly, an experiment using microsphere-assisted microscopy is performed, and the fast Fourier transformation (FFT) spectra of the images along the distance are studied. Then the Poynting vector in the point dipole field is theoretically investigated based on the spectral decomposition of dyadic Green's function. Our study finds that the result of decomposition of the Poynting vector corresponds with the propagation results of components with different transverse wavenumbers kρ in an experiment. Even when kρ reaches 1.7k0, the waves can still arrive outside one wavelength. Our work is the first effort (to our knowledge) to associate the Fourier spectrum and the decomposition of the Poynting vector together, and it may contribute to the quantitative exploration of super-resolution performance in MAM in the future.

Impact of NH4OH treatment on the ion exchange and pore characteristics of a metakaolin-based geopolymer.

We investigated the viability and influence of NH4OH post-synthetic treatment on the pore characteristics of geopolymers. Geopolymers are a class of materials with amorphous aluminosilicate three-dimensional frameworks, regarded as amorphous analogues of zeolites. Similar to zeolites, when geopolymers are used in catalysis or adsorption applications, post-synthetic treatments such as ion exchange with NH4 + salts (e.g., NH4Cl and NH4NO3) and desilication (using strong bases such as NaOH) are necessary to introduce active sites and modify their pore structure, respectively. Recently, it has been shown that treatment with NH4OH combines these two steps, in which acidic sites are introduced and the pore structures of zeolites are modified simultaneously. Considering the increasing interest in geopolymers in catalysis and adsorption applications, understanding the impact of such treatment on the structure of geopolymers is needed. Our diffuse reflectance infrared Fourier-transform spectra show that NH4 + exchanges Na+ in the geopolymer, and laser diffraction with scanning electron microscopy images show that the particle size of the powdered geopolymer decreases after NH4OH treatment. N2 sorption isotherms and 129Xe and 1H NMR measurements revealed information about the changes in pore structures: micropores were larger than mesopores and inborn mesopores increased in diameter, thereby reducing the surface area to volume ratio. However, pore accessibility and pore connectivity were not altered by NH4OH treatment. Since solid-state NMR and X-ray fluorescence revealed desilication, these changes in particle size and pore characteristics are considered to be due to desilication caused by NH4OH treatment.

A study on the development and the application strategy of FT-MIRS-based models for the diagnosis of subclinical mastitis and milk quality classification in buffaloes

Buffalo mastitis detection and buffalo milk quality are of great importance to the world dairy industry. Somatic cell count (SCC) can be employed to assess mammary gland health and milk quality in dairy cows, but SCC detection is costly, and the detection instrument is expensive. The purpose of this study was to develop high and low SCC identification models using Fourier-transform mid-infrared spectrum (FT-MIRS), which could be used to diagnose subclinical mastitis (SCM) in buffalo and to determine the milk quality grade at a low cost. The dataset contained 899 buffalo milk samples collected from two regions in China. Firstly, the samples were divided into positive group above the threshold (SCM or unqualified milk) and negative group below the threshold (healthy or qualified milk) with SCC = 200 × 103 cells/mL (SCM in buffalo), 400 × 103 cells/mL (EU standard for raw cow milk, ES), 500 × 103 cells/mL (Indian standard for raw buffalo milk, IS), and 750 × 103 cells/mL (US standard for raw cow milk, US) as thresholds, respectively. Then, with FT-MIRS as predictive variables, predictive models were developed using Partial Least Squares Discriminant Analysis (PLSDA), Random Forest (RF), and Gradient Boosting Machine (GBM). The main results were as follows: the AUCval of the diagnostic model of SCM in buffalo using SCM criteria as a threshold was 0.84 (PLSDA). The AUCval values of the three buffalo milk quality classification models with ES, IS, and US as thresholds were 0.76 (PLSDA), 0.78 (GBM), and 0.84 (PLSDA), respectively. The predictive models established in this paper had a weak predictive ability for positive samples, and the “stepwise discriminant analysis” was recommended to improve the model application effect: The models were applied to classify samples as positive and negative, and then the samples with higher predictive probability were selected. Finally, the remaining samples were further differentiated using the reference methods of SCC detection. To conclude, FT-MIRS has the potential to predict buffalo mammary gland health status and buffalo milk quality grade, reduce the cost of SCC detection, and improve work efficiency, which will lay the foundation for rapid buffalo milk quality classification by raw milk regulatory authorities and rapid diagnosis of SCM in buffalo by farms.

Fourier-transform spectroscopy and global deperturbation treatment of the A1Σu+ and b3Πu states of K2 in the entire bound energy range.

Rotationally resolved Fourier-transform spectra of laser-induced fluorescence A1Σu+∼b3Πu→X1Σg+ of K2 molecules were recorded and analyzed, yielding 4053 term values of the spin-orbit (SO) coupled A ∼ b complex of the 39K2 isotopologue with ∼0.01 cm-1 accuracy. Their compilation with 1739 term values from previously published sources allowed them to cover the energy range [9955, 17 436] cm-1 from the bottom of the lower-lying b3Πu state up to the vicinity of the atomic asymptote 4s2S12 + 4p2P12, with a rotational quantum number J ∈ [0, 149]. The experimental data were processed by a direct 6 × 6 coupled-channel (CC) deperturbation treatment, which accounted explicitly for both SO and electronic-rotational interactions between all six e-symmetry states: A1Σu+(0u+), b3Πu(0u+,1u,2u), c3Σu(1u), and B1Πu(1u). The initial parameters of the global deperturbation model have been estimated in the framework of abinitio electronic structure calculations applying multi-reference configuration-interaction and coupled-clusters methods. The interatomic potentials analytically defined for A and b states, as well as SO-splitting of the triplet b state and A ∼ b SO-coupling functions, have been particularly refined to fit the 5792 term values of the 39K2 isotopologue, whereas the rest parameters were fixed on their abinitio values. The resulting mass-invariant parameters of the 6 × 6 CC model reproduced the overall rovibronic term energies of the A ∼ b complex of 39K2 with accuracy, which is well within the experimental errors. The quality of the deperturbation analysis was independently confirmed by comparison with the present obtained 705 and 14 term values of respective 39K41K and 41K2 isotopologues, as well as by agreement between measured and predicted relative intensity distributions in long A ∼ b → X(vX) band progressions. This deperturbation analysis provided the refined dissociation energy Tdis = 17 474.569(5) cm-1 and the long-range coefficient C3Σ = 5.501(4) × 105 cm-1 Å3 relevant to the non-relativistic atomic limit 4s + 4p. The derived Tdis yielded the accurate well depth De = 4450.910(5) cm-1 for the ground X1Σg+ state, whereas the new C3Σ value yielded the improved estimates for atomic K(4p2P12;32) radiative lifetimes, τ12 = 26.67(3) and τ32 = 26.32(3) ns.

Effect of Sn(II)/Sn(IV) additive on the catalytic combustion of diethylamine and N2 selectivity over CeZrOx catalyst

The synthesis of CeZrSnOx by co-precipitation with different valence-state of Sn for diethylamine combustion is novel and intriguing. In this research, the Sn(II)/Sn(IV)-doped CeZrOx catalysts (CeZr(Sn)Ox-(Sn2+) and CeZr(Sn)Ox-(Sn4+)) were facilely prepared using the co-precipitation method, and their catalytic activities on destruction of diethylamine were evaluated. Detailed characterizations of the catalysts were conducted using X-ray photoelectron spectrometer (XPS), X-ray powder diffraction (XRD), hydrogen-temperature programmed reduction (H2-TPR), temperature programmed ammonia desorption (NH3-TPD) and so on. For diethylamine combustion, CeZr(Sn)Ox-(Sn2+) showed higher activity and nitrogen selectivity than other catalysts, and a high conversion of diethylamine (>90 %) at 250 °C was obtained. After hydrothermal aging treatment, a high conversion (>90 %) and high N2 selectivity maintained over CeZr(Sn)Ox-(Sn2+)-H at 280 °C, indicating high hydrothermal stability of CeZr(Sn)Ox-Sn2+. Owe to the large specific surface area (SSA), high oxygen mobility and strong redox performance, and the synergy between metal elements in CeZr(Sn)Ox-Sn2+ catalysts, the catalytic properties were enhanced. Moreover, Sn2+/Sn4+ ratio in the catalyst and strong acidic sites on the surface of the catalyst both had significant impacts on the catalytic activity and N2 selectivity of the catalyst. Finally, the mechanism of diethylamine combustion over CeZr(Sn)Ox-Sn2+ was obtained by analyzing the reaction through in-situ diffuse reflection infrared Fourier-transform spectrum (in situ DRIFTS) test.

Influence of the Bismuth Content on the Optical Properties and Photoluminescence Decay Time in GaSbBi Films.

We report the optical properties of GaSbBi layers grown on GaSb (100) substrates with different bismuth contents of 5.8 and 8.0% Bi. Fourier-transform photoluminescence spectra were determined to identify the band gaps of the studied materials. Further temperature- and power-dependent photoluminescence measurements indicated the presence of localized states connected to bismuth clustering. Finally, time-resolved photoluminescence measurements based on single-photon counting allowed the determination of characteristic photoluminescence decay time constants. Because of the increasing bismuth content and clustering effects, an increase in the time constant was observed.

Quantification and Detection of Ground Garlic Adulteration Using Fourier-Transform Near-Infrared Reflectance Spectra.

This study demonstrates the rapid and cost-effective possibility of quantifying adulterant amounts (corn flour or corn starch) in ground and dried garlic samples. Prepared mixtures with different concentrations of selected adulterant were effectively characterized using Fourier-transform near-infrared reflectance spectra (FT-NIR), and multivariate calibration models were developed using two methods: principal component regression (PCR) and partial least squares regression (PLSR). They were constructed for optimally preprocessed FT-NIR spectra, and PLSR models generally performed better regarding model fit and predictions than PCR. The optimal PLSR model, built to estimate the amount of corn flour present in the ground and dried garlic samples, was constructed for the first derivative spectra obtained after Savitzky-Golay smoothing (fifteen sampling points and polynomial of the second degree). It demonstrated root mean squared errors for calibration and validation samples equal to 1.8841 and 1.8844 (i.e., 1.88% concerning the calibration range), respectively, and coefficients of determination equal to 0.9955 and 0.9858. The optimal PLSR model constructed for spectra after inverse scattering correction to assess the amount of corn starch had root mean squared errors for calibration and validation samples equal to 1.7679 and 1.7812 (i.e., 1.77% and 1.78% concerning the calibration range), respectively, and coefficients of determination equal to 0.9961 and 0.9873. It was also possible to discriminate samples adulterated with corn flour or corn starch using partial least squares discriminant analysis (PLS-DA). The optimal PLS-DA model had a very high correct classification rate (99.66%), sensitivity (99.96%), and specificity (99.36%), calculated for external validation samples. Uncertainties of these figures of merit, estimated using the Monte Carlo validation approach, were relatively small. One-class classification partial least squares models, developed to detect the adulterant type, presented very optimistic sensitivity for validation samples (above 99%) but low specificity (64% and 45.33% for models recognizing corn flour or corn starch adulterants, respectively). Through experimental investigation, chemometric data analysis, and modeling, we have verified that the FT-NIR technique exhibits the required sensitivity to quantify adulteration in dried ground garlic, whether it involves corn flour or corn starch.

Speech Emotion Recognition Based on Voice Fundamental Frequency

The human voice is one of the basic means of communication, thanks to which one also can easily convey the emotional state. This paper presents experiments on emotion recognition in human speech based on the fundamental frequency. AGH Emotional Speech Corpus was used. This database consists of audio samples of seven emotions acted by 12 different speakers (6 female and 6 male). We explored phrases of all the emotions – all together and in various combinations. Fast Fourier Transformation and magnitude spectrum analysis were applied to extract the fundamental tone out of the speech audio samples. After extraction of several statistical features of the fundamental frequency, we studied if they carry information on the emotional state of the speaker applying different AI methods. Analysis of the outcome data was conducted with classifiers: K-Nearest Neighbours with local induction, Random Forest, Bagging, JRip, and Random Subspace Method from algorithms collection for data mining WEKA. The results prove that the fundamental frequency is a prospective choice for further experiments.

Prediction of gastroesophageal reflux episodes by smooth muscle electromyography: A translational study in rats and adolescents

AimsOur aim was to measure the myoelectric modifications during gastric acid secretion along with the gastric pH in a rat model and to detect the gastrointestinal (GI) myoelectric changes in adolescents suffering from gastroesophageal reflux disease (GERD) along with the esophageal pH measurement. Main methodsIn anesthetized rats, gastric acid secretion was initiated with intragastric histamine (50 mg/kg), and gastric pH, GI myoelectric activity and mechanical GI contractions were measured with intragastric pH electrode, subcutaneously implanted smooth muscle electromyography (SMEMG) electrodes and organ implanted strain gauges, respectively. In the clinical study, esophageal pH and GI myoelectric activity were measured in adolescents suffering from GERD with intraesophageal pH electrode and SMEMG electrodes placed on the abdominal surface, respectively. The SMEMG records were analyzed by fast Fourier transformation (FFT) and power spectrum density maximum (PsDmax) values were calculated for the GI segments. Key findingsIn rats, histamine initiated an immediate increase in gastric PsDmax, which preceded the significant reduction in gastric pH by 75 min. The myoelectric change was independent of mechanical GI contractions. In adolescents, the GERD episodes were preceded by a significant increase in gastric PsDmax 45 min earlier. These changes were independent of motion or meals. SignificanceIncreased gastric myoelectric activity during histamine stimulation or GERD might be linked to the enhanced activity of the gastric proton pump, indicating a link between gastric acid secretion and GERD episodes. It is supposed that SMEMG might be a tool for predicting forthcoming reflux episodes in GERD.

Frequency Response Enhanced Quantitative Vibration Detection Using Fading-Free Coherent $\varphi$-OTDR With Randomized Sampling

A frequency response enhanced quantitative vibration detection scheme for interference fading suppressed coherent phase-sensitive optical time domain reflectometry (ϕ-OTDR) is proposed and demonstrated. By utilizing randomized sampling, the proposed scheme not only breaks the inherent limitation between the sensing range and the maximum detectable frequency in conventional ϕ-OTDR systems, but also allows for quantitative measurement of the vibration amplitude by tracking the peak intensity of the discrete Fourier transformation spectrum of the phase signals. The operation principle and the measurement accuracy are mathematically analyzed through the frequency spectrum estimator unbiasedness and the estimation standard deviation, which provides a comprehensive guidance for parameter configuration in practical applications. For proof of concept, quantitative detection of vibration signals up to 384 kHz is realized over a 5.4 km fiber, while the conventional solutions only reach 18.5 kHz as restricted by the Nyquist sampling theorem. The proposed sensing scheme paves the way to enable ultra-high frequency quantitative vibration detection using ϕ-OTDR.

Role of Maillard reactions in co-pyrolysis of lignite and spent coffee grounds: Fixation of nitrogen in semicoke and improved adsorption of phenols

Semicoke derived from lignite and biomass has been utilized in soil remediation and activated sludge treatment. Nitrogen-doping treatment has been utilized to improve adsorption capacity of semicoke for phenols (such as humic acids). Known as nitrogen-rich biomass residue, spent coffee grounds (SCG) may serve as nitrogen resources when co-pyrolyzed with lignite. But impacts of SCG on structure and adsorption capacity of semicoke in co-pyrolysis have not been confirmed. In consideration of proteins in SCG, nitrogen fixation and the impacting mechanism have not been sufficiently confirmed. In this work, nitrogen fixation between lignite and SCG during co-pyrolysis were investigated by thermogravimetric analysis (TG) and pyrolysis experiments. Corresponding mechanism were speculated and confirmed by in-situ diffuse reflectance infrared Fourier transformation spectra (DRIFT) and mass spectrum (MS). Impacts of nitrogen fixation on adsorption of phenols on semicoke were investigated by X-ray photoelectron spectroscopy (XPS), adsorption kinetics analysis and density functional theory (DFT) calculations. Compared to theoretical values, higher contents of N have been obtained in co-pyrolyzed semicoke (N: 2.89%; pyridinic N: 44.86%), which implied N fixation and cyclization reactions. Fixation mechanism can be explained by formation of Amadori/Heyns intermediates in Maillard reactions. Release of volatiles and capture of NH3 are crucial in 340–440 °C range, which result in nitrogen fixation. Then formation of pyrrolic and pyridinic N can be explained by cyclization reactions and decomposition of Amadori/Heyns intermediates in 550 °C pyrolysis. Enrichment of pyridinic N, pyrrolic N and CO might enhance adsorption of phenols by offering binding sites for formation of hydrogen bonds. Both C, N fixation and improved adsorption capacity (27.80 mg/g) have been realized for 7:3–550 semicoke. Consequently, doping treatment with typical nitrogen-rich biomass (SCG) may be feasible to enhance adsorption of phenols onto semicoke, based on selection of raw materials and pyrolysis conditions.

Low Complexity Non-Linear Spectral Features and Wear State Models for Remaining Useful Life Estimation of Bearings

Improving the reliability and performance of electric and rotating machines is crucial to many industrial applications. This will lead to improved robustness, efficiency, and eco-sustainability, as well as mitigate significant health and safety concerns regarding sudden catastrophic failure modes. Bearing degradation is the most significant cause of machine failure and has been reported to cause up to 75% of low-voltage machine failures. This paper introduces a low complexity machine learning (ML) approach to estimate the remaining useful life (RUL) of rolling element bearings using real vibration signals. This work explores different ML recipes using novel feature engineering coupled with various k-Nearest Neighbour (k-NN), and Support Vector Machines (SVM) kernel and weighting functions in order to optimise this RUL approach. Original non-linear wear state models and feature sets are investigated, the latter are derived from Short-time Fourier Transform (STFT) and Hilbert Marginal Spectrum (HMS). These feature sets incorporate one-third octave band filtering for low complexity multivariate feature subspace compression. Our proposed ML algorithm stage has employed two robust supervised ML approaches: weighted k-NN and SVM. Real vibration data were drawn from the Pronostia platform to test and validate this prognostic monitoring approach. The results clearly demonstrate the effectiveness of this approach, with classification accuracy results of up to 82.8% achieved. This work contributes to the field by introducing a robust and computationally inexpensive method for accurate monitoring of machine health using low-cost vibration-based sensing.

Influence of Operationally Consumed Propellers on Multirotor UAVs Airworthiness: Finite Element and Experimental Approach

Unmanned aerial vehicles (UAVs) are widely used in many applications due to the current technological trend. In these applications, understanding the concept of the operating frequency range is vital to ensure UAV safety. Although most current studies are focused on health monitoring and fault diagnostic methodologies, none of them has included a comprehensive knowledge of the behavior of the natural frequency behavior. This research examines the effectiveness of computer-aided design (CAD) and computer-aided engineering (CAE) in advancing finite element modal analysis. Theoretical results were further evaluated on an experimentally operated drone to understand the interference concept of natural and operational frequencies. Extensive, high-quality, and comprehensive soft-labeled data was acquired in the time-domain from the selected hovering quad-copter equipped with an accelerometer sensor connected to a data acquisition system and a PC platform. Healthy propellers and operationally consumed propellers vibration signal datasets were recorded. The collected datasets were transformed to frequency-domain using Fast Fourier Transform (FFT) spectrum analysis. In summary, the finite element modal analysis provided a thorough behavior understanding of the faulty operating drone status by comparing the natural frequencies to those acquired experimentally based on a detailed discussion. The relationship between natural and operational frequencies is then investigated and presented.