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The stable operation of a variable frequency pump is of great importance to the management of a water supply project. Analyzing the operation performance based on monitoring data is necessary for maintaining the stable operation of a variable frequency pump. Several sensors are installed at six monitoring points on the pump to collect signals including vibration velocity, vibration acceleration and vibration displacement. Monitoring signals are preprocessed by smoothing, adjusting waveform trend and filtering on the basis of Fast Fourier Transform (FFT). Then, the vibration features are extracted by power spectrum analysis and cepstrum analysis methods. According to the extracted features, the vibration law and actual operation performance of a variable frequency pump under different operating conditions are analyzed. Results indicate that the vibration amplitude of the pump varies sharply under the operating conditions of [15 Hz, 20 Hz] and [30 Hz, 35 Hz]. The operating condition of [0 Hz, 15 Hz] is the restricted operating area of the pump. The vibration and noise continue increasing under the operating conditions of [35 Hz, 50 Hz] and reach the maximum values at 50 Hz. Therefore, the optimal operating is within the range of [20 Hz, 30 Hz]. Finally, by analyzing the critical values of the operating conditions, the fault diagnosis and the evaluation of the operating status are conducted. [ABSTRACT FROM AUTHOR]

Gorgonians play a fundamental role in the deep sea (below 200 m depth), composing three-dimensional habitats that are characterized by a high associated biodiversity and playing an important part in biogeochemical cycles. Here we describe the use of a benthic lander to monitoring polyps activity, used as a proxy of gorgonian feeding activity of three colonies of Placogorgia sp. Images cover a period of 22 days with a temporal resolution of 30 min. In addition, this seafloor observatory is instrumented with oceanographic sensors that allows continuous monitoring of the hydrographic conditions in the site. Deep-learning is used for automatic detection of the state of the polyps registered in the images. More than 1000 images of 3 large specimens of gorgonians are analyzed, annotating polyps as extended or retracted, using the semantic segmentation algorithm ConvNeXt. The segmentation results are used to describe the feeding patterns of this species. Placogorgia sp. shows a daily pattern of feeding conduct, depending on the hours of day and night. Using a Singular Spectrum Analysis approach, feeding activity is related to currents dynamics and Acoustic Doppler Current Profile (ADCP) return signal intensity, as proxy of suspended matter, achieving a linear correlation of 0.35 and 0.11 respectively. This is the first time that the behavior of the Placogorgia polyps, directly related to their feeding process, is described. [ABSTRACT FROM AUTHOR]

Simple Summary: The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. Analyses of the NEPA provide additional information to the magnetic resonance imaging (MRI) evaluation of the enhancing part of brain tumors. NEPA analyses of central nervous system malignancies with conventional and advanced MRI techniques give interesting highlights in the differential diagnosis of solid contrast-enhanced brain tumors regarding the prognostic stratification and treatment response. Considering the rapid technological changes in advanced MRI imaging, we assume that an update on this topic might be of interest. The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast-conserving surgery (BCS) is an oncological procedure that allows for the excision of breast cancer with a clear margin of healthy tissue whilst optimising the cosmetic appearance. However, BCS is associated with up to a 19% re-excision rate due to incomplete excision ("positive margins") in the United Kingdom. Optical spectroscopy and the optical imaging of BCS specimens could be a potential intraoperative margin assessment tool to help reduce re-excision rates. Hyperspectral sensing is based on the premise that light illuminating biological tissues undergoes several processes that reflect the composition of tissue, thus helping to differentiate between normal and malignant tissues. This review assesses the current literature on the use of hyperspectral sensing in breast cancer. We divide the techniques into either point-based (spectroscopy) or whole field-of-view (imaging) methods. A comparison is made of the effectiveness of these modalities in discriminating between normal and malignant tissue, and we reflect on the usability of these modalities in the intraoperative setting. Up to 19% of patients require re-excision surgery due to positive margins in breast-conserving surgery (BCS). Intraoperative margin assessment tools (IMAs) that incorporate tissue optical measurements could help reduce re-excision rates. This review focuses on methods that use and assess spectrally resolved diffusely reflected light for breast cancer detection in the intraoperative setting. Following PROSPERO registration (CRD42022356216), an electronic search was performed. The modalities searched for were diffuse reflectance spectroscopy (DRS), multispectral imaging (MSI), hyperspectral imaging (HSI), and spatial frequency domain imaging (SFDI). The inclusion criteria encompassed studies of human in vivo or ex vivo breast tissues, which presented data on accuracy. The exclusion criteria were contrast use, frozen samples, and other imaging adjuncts. 19 studies were selected following PRISMA guidelines. Studies were divided into point-based (spectroscopy) or whole field-of-view (imaging) techniques. A fixed-or random-effects model analysis generated pooled sensitivity/specificity for the different modalities, following heterogeneity calculations using the Q statistic. Overall, imaging-based techniques had better pooled sensitivity/specificity (0.90 (CI 0.76–1.03)/0.92 (CI 0.78–1.06)) compared with probe-based techniques (0.84 (CI 0.78–0.89)/0.85 (CI 0.79–0.91)). The use of spectrally resolved diffusely reflected light is a rapid, non-contact technique that confers accuracy in discriminating between normal and malignant breast tissue, and it constitutes a potential IMA tool. [ABSTRACT FROM AUTHOR]

7α- and 7β-hydroxysteroid dehydrogenases (HSDHs) are enzymes that can catalyze the isomerization of hydroxyl groups at site seven of bile acids. In a previous study, we found that the activities of 7α- and 7β-HSDHs can be inhibited by bilirubin. In order to clarify the impact, the effects of bilirubin on enzymes were studied by kinetics, spectrum, and docking analysis. The relative activity of 7α-HSDH remained less than 40% under 1 mM bilirubin, and only 18% activity of 7β-HSDH kept in the same condition. Using taurochenodeoxycholic acid (TCDCA) as substrate, the Km of 7α-HSDH was up to 0.63 mM from 0.24 mM after binding with bilirubin and the Km of 7β-HSDH rose from 1.14 mM to 1.87 mM for the catalysis of tauroursodeoxycholic acid (TUDCA). The affinity of 7α- and 7β-HSDHs to substrates decreased with the effect of bilirubin. The binding of bilirubin with 7α- or 7β-HSDHs was analyzed by UV–vis, fluorescence, and circular dichroism (CD) spectroscopy. The results reflected that bilirubin caused a slight change in the secondary structure of 7α- or 7β-HSDHs, and the changes were correlated with the ratio of bilirubin to enzymes. Ten candidate molecular docking results were presented to reflect the binding of bilirubin with 7α- or 7β-HSDHs and to explore the inhibition mechanism. This research provides a more in-depth understanding of the effect of bilirubin on 7α- and 7β-HSDHs. [ABSTRACT FROM AUTHOR]

The ordinary spectrum is restricted in its applications, since it is based on the second-order moments (auto- and cross-covariances). Alternative approaches to spectrum analysis have been investigated based on other measures of dependence. One such approach was developed for univariate time series by the authors of this paper using the local Gaussian auto-spectrum based on the local Gaussian auto-correlations. This makes it possible to detect local structures in univariate time series that look similar to white noise when investigated by the ordinary auto-spectrum. In this paper, the local Gaussian approach is extended to a local Gaussian cross-spectrum for multivariate time series. The local Gaussian cross-spectrum has the desirable property that it coincides with the ordinary cross-spectrum for Gaussian time series, which implies that it can be used to detect non-Gaussian traits in the time series under investigation. In particular, if the ordinary spectrum is flat, then peaks and troughs of the local Gaussian spectrum can indicate nonlinear traits, which potentially might reveal local periodic phenomena that are undetected in an ordinary spectral analysis. [ABSTRACT FROM AUTHOR]

The stoichiometric ratio 2:1 mix of 1-phenylpiperazine and oxalic acid dihydrate followed by slow evaporation results in a new material, bis(4-phenylpiperazin-1-ium) oxalate dihydrate, with the general chemical formula (C10H15N2)2(C2O4).2H2O, indicated by PPOXH. The title compound's asymmetric unit and three-dimensional network have been determined by single crystal X-ray diffraction. Intermolecular O-H...O, N-H...O and C-H...O hydrogen bonding assist in maintaining and stabilization of the crystal structure of this new compound. Hirshfeld surface analysis and two-dimensional fingerprints have been performed to quantify the non-covalent interactions in the PPOXH structure. The vibrational modes of the different characteristic groups of the title chemical were identified using infrared spectrum analysis. The thermal characterization of this product was studied by a coupled TG/DTA analysis. The ultraviolet-visible absorption spectrum has been used to study the optical properties and the energy gap of this compound. DFT calculations were employed to evaluate the composition and properties of PPOXH. The analysis of HOMO-LUMO frontier orbitals analysis allows us to understand the chemical reactivity of this supramolecular compound and to determine the electrophilic and nucleophilic sites responsible for electron transfer. Topological analysis (AIM), reduced density gradient (RDG), molecular electrostatic potential surface (MEPS) and Mulliken population were analyzed to evaluate the types of non-covalent interactions, localization of electrons in space, atomic charges and molecular polarity in depth. [ABSTRACT FROM AUTHOR]

Orbitrap mass spectrometers have gained widespread popularity in ground-based environmental component analysis. However, their application in atmospheric exploration for space missions remains limited. Existing data acquisition solutions for Orbitrap instruments primarily rely on commercial systems and computer-based spectrum analysis. In this study, we developed a self-designed data acquisition solution specifically tailored for atmospheric molecule detection. The implementation involved directly integrating a spectrum analysis algorithm onto a field programmable gate array (FPGA), enabling miniaturization, real-time performance, and meeting the desired requirements. The system comprises signal conditioning circuits, analog-to-digital conversion (ADC) circuits, programmable logic circuits, and related software. These components facilitate real-time spectrum analysis and signal processing on hardware, enabling high-speed acquisition and analysis of signals generated by the Orbitrap. Experimental results demonstrate that the system can sample front-end analog signals at a rate of 25 MHz and differentiate signal spectra with an error margin of less than 7 kHz. This establishes the viability of the designed data acquisition system for atmospheric mass spectrometry analysis. [ABSTRACT FROM AUTHOR]

The rail conveyor is a new type of energy-saving system for the long-distance transportation of bulk materials. Operating noise is an urgent problem that the current model faces. It will cause noise pollution and affect the health of workers. In this paper, the factors causing vibration and noise are analyzed by modeling the wheel-rail system and the supporting truss structure. Based on the built test platform, the system vibration of the vertical steering wheel, the track support truss, and the track connection were measured, and the vibration characteristics at different positions were analyzed. Based on the established noise and vibration model, the distribution and occurrence rules of system noise under different operating speeds and fastener stiffness conditions were obtained. The experimental results show that the vibration amplitude of the frame near the head of the conveyor is the largest. The amplitude under the condition of 2 m/s running speed at the same position is 4 times that under the condition of 1 m/s. At different welds of the track, the width and depth of the rail gap have a great influence on the vibration impact, which is mainly due to the impact of the uneven impedance at the track gap, and the greater the running speed, the more obvious the vibration impact. The simulation results show the trend of noise generation, the speed of the trolley, and the stiffness of the track fasteners have a positive effect on the generation of noise in the low-frequency region. The research results of this paper will play an important role in the noise and vibration analysis of rail conveyors and help to optimize the structure design of the track transmission system. [ABSTRACT FROM AUTHOR]

Simple Summary: To minimize the risk of cancer recurrence, it is crucial for surgeons to assess the resection margins (surface) of surgical specimens during breast-conserving surgeries to determine whether the tumor has been removed entirely. However, this is often not easy and also current techniques lack to aid the surgeons. In our study, we used a hyperspectral imaging technique to overcome this challenge. To assess the resection margins with hyperspectral imaging, a classification model should be developed, which requires a dataset with accurate ground-truth labels. Since it is difficult to establish such a dataset, we introduced a novel approach based on hyperspectral unmixing to enable an accurate correlation between hyperspectral measurements and histology ground-truth labels. Subsequently, we developed a classification model for tumor tissue detection on the lumpectomy resection surface of 189 patients. We achieved a sensitivity of 94% and a specificity of 85%, which demonstrated the potential of hyperspectral imaging for breast-conserving surgeries. (1) Background: Assessing the resection margins during breast-conserving surgery is an important clinical need to minimize the risk of recurrent breast cancer. However, currently there is no technique that can provide real-time feedback to aid surgeons in the margin assessment. Hyperspectral imaging has the potential to overcome this problem. To classify resection margins with this technique, a tissue discrimination model should be developed, which requires a dataset with accurate ground-truth labels. However, establishing such a dataset for resection specimens is difficult. (2) Methods: In this study, we therefore propose a novel approach based on hyperspectral unmixing to determine which pixels within hyperspectral images should be assigned to the ground-truth labels from histopathology. Subsequently, we use this hyperspectral-unmixing-based approach to develop a tissue discrimination model on the presence of tumor tissue within the resection margins of ex vivo breast lumpectomy specimens. (3) Results: In total, 372 measured locations were included on the lumpectomy resection surface of 189 patients. We achieved a sensitivity of 0.94, specificity of 0.85, accuracy of 0.87, Matthew's correlation coefficient of 0.71, and area under the curve of 0.92. (4) Conclusion: Using this hyperspectral-unmixing-based approach, we demonstrated that the measured locations with hyperspectral imaging on the resection surface of lumpectomy specimens could be classified with excellent performance. [ABSTRACT FROM AUTHOR]

Tanks made of three different brands of rotational polyethylene (DOW, ELTEX, and M350) with three degrees of sintering (normal sintering (NS), incomplete sintering (ICS), and thermally degraded sintering (TDS)) and three thicknesses (7.5 mm, 8.5 mm, and 9.5 mm) were explored. It was found that the thickness of the walls of the tanks did not have a statistically significant effect on the parameters of the ultrasonic signal (USS). An increase in temperature caused a decrease in the USS parameters. According to the temperature coefficient of stability, the ELTEX brand of plastic can be distinguished (from DOW and M350). The ICS degree of the sintering of the tanks was revealed from a significantly lower amplitude of the bottom signal, compared with NS and TDS degree samples. By analyzing the amplitude of the third harmonic of the ultrasonic signal (β), three degrees of the sintering of containers NS, ICS, and TDS were revealed (with an accuracy of about 95%). Equations β = f(T, PIAT) were derived for each brand of rotational polyethylene (PE), and two-factor nomograms were constructed. Based on the results of this research, a method for the ultrasonic quality control of polyethylene tanks manufactured using rotational molding was developed. [ABSTRACT FROM AUTHOR]

As a critical support and fixed component of aero engines, electro-hydrostatic actuators, and other equipment, the operation of aviation bearings is often subject to high speed, high-temperature rise, large load, and other continuous complex fluctuation conditions, which makes their health assessment tasks more difficult. To solve this problem, an intelligent health assessment method based on a new Deep Transfer Graph Convolutional Network (DTGCN) is proposed for aviation bearings under large speed fluctuation conditions. First, a new DTGCN algorithm is designed, which mainly uses the domain adaptation mechanism to enhance the performance of Graph Convolutional Network (GCN) and the generalization performance of transfer properties. Specifically, order spectrum analysis is employed to resample the vibration signals of aviation bearings and transform them into order spectral signals. Then, the trained 1dGCN is used as the feature extractor, and the designed Dynamic Multiple Kernel Maximum Mean Discrepancy (DMKMMD) is calculated to match the difference in edge distribution. Finally, the aligned features are fed into the softmax classifier for intelligent health assessment. The effectiveness of the proposed diagnostic algorithm and method are validated by using aviation bearing fault data set under large speed fluctuation conditions. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, X-ray Photoelectron Spectroscopy (XPS) is used as a fast technique to characterize the composition of nanosized small extracellular vesicles (EVs), with the aim of evaluating its possible application in cancer screening and diagnosis. This spectroscopic technique is an ideal approach to characterize membranes due to its sensitivity and its penetration depth, in the nanometric range, meaning that the results will mainly correspond to the membrane composition, with little interference from the biomolecules in the EV´s lumen. We propose the use of XPS to analyze the membranes of small extracellular vesicles isolated from bodily fluids of cancer patients and compared them to those of healthy cells and donors. Notably, we have focused our analysis on the N chemical environment of EV membranes, as this can be related to previous complex chemical analyses of lipid and protein contents in EVs. We provide preliminary results on a fast and non-invasive novel strategy, as a method or tool for research-based EV investigations with potential application in cancer screening and monitoring. Small extracellular vesicle (EV) membranes display characteristic protein-lipidic composition features that are related to their cell of origin, providing valuable clues regarding their parental cell composition and real-time state. This could be especially interesting in the case of cancer cell-derived EVs, as their membranes could serve as valuable tools in liquid biopsy applications and to detect changes in the tumor malignancy. X-Ray Photoelectron Spectroscopy (XPS) is a powerful surface analysis technique able to detect every chemical element present, being also sensitive to their chemical environment. Here we explore the use of XPS as a fast technique to characterize EV membrane composition, with possible application in cancer research. Notably, we have focused on the nitrogen environment as an indicator of the relative abundance of pyridine-type bonding, primary, secondary and tertiary amines. Specifically, we have analyzed how tumoral and healthy cells have different nitrogen chemical environments that can indicate the presence or absence of malignancy. In addition, a collection of human serum samples from cancer patients and healthy donors was also analyzed. The differential XPS analysis of EVs collected from patients confirmed that the patterns of amine evolution could be related to markers of cancer disease, opening the possibility of their use as a non-invasive blood biomarker. [ABSTRACT FROM AUTHOR]

Heart rate measurement employing photoplethysmography (PPG) is a prevalent technique for wearable devices. However, the acquired PPG signal is often contaminated with motion artifacts, which need to be accurately removed. In cases where the PPG and accelerometer (ACC) spectra overlap at the actual heart rate, traditional discrete Fourier transform (DFT) algorithms fail to compute the heart rate accurately. This study proposed an enhanced heart rate extraction algorithm based on PPG to address the issue of PPG and ACC spectral overlap. The spectral overlap is assessed according to the morphological characteristics of both the PPG and ACC spectra. Upon detecting an overlap, the singular spectrum analysis (SSA) algorithm is employed to calculate the heart rate at the given time. The SSA algorithm effectively resolves the issue of spectral overlap by removing motion artifacts through the elimination of ACC-related time series in the PPG signal. Experimental results reveal that the accuracy of the proposed algorithm surpasses that of the traditional DFT method by 19.01%. The proposed method makes up for the deficiency posed by artifact and heart rate signal overlap in conventional algorithms and significantly improves heart rate extraction accuracy. [ABSTRACT FROM AUTHOR]

Medium-rise reinforced concrete (RC) framed apartment complexes with stories ranging from 15 to 50 are becoming more common in Ethiopia's main cities. In these RC-framed structures, shear walls are included for lateral load resistance. As apertures are frequently provided in shear walls, it is critical to evaluate their influence on story drift, stiffness, shear and moments, and stress within the shear walls. A 3D study with five different cases was carried out with ETABS version 19.00 software to investigate the influence of apertures in a building's shear wall. This study looks at the effects of changing the size and location of these apertures. Based on this analysis, extensive data were acquired, and useful conclusions were formed that will be useful to practicing engineers. The seismic parameter utilized for the response spectrum study was Building Code of Ethiopia ES8-15, which conforms to Eurocode 8-2004 seismic code guidelines (based on EN1998-1) with target response spectrum type-I. The following parameters were used: ground acceleration, ag/g = 0.1, spectrum type = I, ground type = B, soil factor, S = 1.35, spectrum period, Tb, = 0.05 s, spectrum period, Tc = 0.25 s, spectrum period, Td = 1.2 s, lower bound factor, beta = 0.2, behavior factor = 1, and damping ratio = 5%. The outcomes are compared using various parameters such as displacement, story drift, story stiffness, story shear, and story moment both with and without shear wall opening cases. This study will give tremendous insight into the effect of shear wall openings on the performance of the structure. The analysis in this work was carried out on a linear model, which may not represent the complete local response of the structure; thus, future researchers should perform nonlinear analysis based on a performance-based design. It was concluded from this investigation that incorporating shear walls considerably enhanced the performance of the building over framed structures. Shear wall openings in a structure have a significant influence on the building's performance. Due to their significant resistance to earthquake forces, shear wall structures are highly recommended for seismic hazard zones. [ABSTRACT FROM AUTHOR]

The coupling between optically active substances of algae particles and inorganic suspended solids of water makes the characteristics of reflection spectra of water complex and changeable. This makes modeling and inversion of polarization remote sensing in class II water difficult. In our study, considering the influence of the mixing ratio of algae particles and inorganic suspended solids, the sensor incidence angle, and the solar zenith angle on the polarization reflection spectrum, we analyzed the coupling characteristics of the polarized bidirectional reflectance of particulate matter through control experiments of mixed components of water particles in the laboratory. With Chaohu Lake in China as an example, the polarized reflectance coupling characteristics of water particles was investigated by the water-leaving radiation. The results showed that in the characteristic bands of 570, 675, and 705 nm, the degree of linear polarization (DOLP) was sensitive to the water-leaving radiation of the particles rather than to the reflectance. With the variation of observation angle, the reflection spectra were strongly interfered with by solar flare when the sensor zenith angle was close to 50° on the meridian plane with an azimuth angle of 180°, but DOLP was less affected, while also having a low correlation in the high concentration region. Combined with the coupling characteristics of particles at 675 and 705 nm, the model of DOLP ratio was established by partial least squares regression (PLSR) with a determination coefficient (R2) of 0.91, root mean square error (RMSE) 0.035, and a verification accuracy of 0.959. This shows that the model has better prediction ability for the coupling characteristics of water particles by the polarization reflection spectra and provides good support for mixed spectral unmixing of class II water. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the molecular composition of a viable but nonculturable (VBNC) state of a probiotic strain, Lacticaseibacillus paracasei Zhang (L. paracasei Zhang), using single-cell Raman spectroscopy (SCRS). Fluorescent microcopy with live/dead cell staining (propidium iodide and SYTO 9), plate counting, and scanning electron microscopy were used in combination to observe bacteria in an induced VBNC state. We induced the VBNC state by incubating the cells in de Man, Rogosa, and Sharpe broth (MRS) at 4 °C. Cells were sampled for subsequent analyses before VBNC induction, during it, and up to 220 days afterwards. We found that, after cold incubation for 220 days, the viable plate count was zero, but active cells could still be observed (as green fluorescent cells) under a fluorescence microscope, indicating that Lacticaseibacillus paracasei Zhang entered the VBNC state under these conditions. Scanning electron microscopy revealed the altered ultra-morphology of the VBNC cells, characterized by a shortened cell length and a wrinkled cell surface. Principal component analysis of the Raman spectra profiles revealed obvious differences in the intracellular biochemical constituents between normal and VBNC cells. Comparative analysis of the Raman spectra identified 12 main differential peaks between normal and VBNC cells, corresponding to carbohydrates, lipids, nucleic acids, and proteins. Our results suggested that there were obvious cellular structural intracellular macromolecular differences between normal and VBNC cells. During the induction of the VBNC state, the relative contents of carbohydrates (such as fructose), saturated fatty acids (such as palmitic acid), nucleic acid constituents, and some amino acids changed obviously, which could constitute a bacterial adaptive mechanism against adverse environmental conditions. Our study provides a theoretical basis for revealing the formation mechanism of a VBNC state in lactic acid bacteria. [ABSTRACT FROM AUTHOR]

Simple Summary: No measures of the changes occurring in the liver in the case of outflow deprivation during hepatectomies are available. This study investigated four indexes obtained using hyperspectral imaging in a pig model, measured in different liver lobes, before and after hepatic vein occlusion. The variations of StO2% and deoxy-Hb were considerably good markers of venous liver congestion. Introduction. The changes occurring in the liver in cases of outflow deprivation have rarely been investigated, and no measurements of this phenomenon are available. This investigation explored outflow occlusion in a pig model using a hyperspectral camera. Methods. Six pigs were enrolled. The right hepatic vein was clamped for 30 min. The oxygen saturation (StO2%), deoxygenated hemoglobin level (de-Hb), near-infrared perfusion (NIR), and total hemoglobin index (THI) were investigated at different time points in four perfused lobes using a hyperspectral camera measuring light absorbance between 500 nm and 995 nm. Differences among lobes at different time points were estimated by mixed-effect linear regression. Results. StO2% decreased over time in the right lateral lobe (RLL, totally occluded) when compared to the left lateral (LLL, outflow preserved) and the right medial (RML, partially occluded) lobes (p < 0.05). De-Hb significantly increased after clamping in RLL when compared to RML and LLL (p < 0.05). RML was further analyzed considering the right portion (totally occluded) and the left portion of the lobe (with an autonomous draining vein). StO2% decreased and de-Hb increased more smoothly when compared to the totally occluded RLL (p < 0.05). Conclusions. The variations of StO2% and deoxy-Hb could be considered good markers of venous liver congestion. [ABSTRACT FROM AUTHOR]

Harmonic estimation is essential for mitigating or suppressing harmonic distortions in power systems. The most important idea is that spectrum analysis, waveform estimation, harmonic source classification, source location, the determination of harmonic source contributions, data clustering, and filter-based harmonic elimination capacity are also considered. The feature extraction method is a fundamental component of the optimization that improves the effectiveness of the Harmonic Mitigation method. In this study, techniques to extract fundamental frequencies and harmonics in the frequency domain, the time domain, and the spatial domain include 67 literature reviews and an overall assessment. The combinations of signal processing with artificial intelligence (AI) techniques are also reviewed and evaluated in this study. The benefit of the feature extraction methods is that the analysis extracts the powerful basic information of the feedback signals from the sensors with the most redundancy, ensuring the highest efficiency for the next sampling process of algorithms. This study provides an overview of the fundamental frequency and harmonic extraction methods of recent years, an analysis, and a presentation of their advantages and limitations. [ABSTRACT FROM AUTHOR]

The smoke emitted during thermal decomposition of elastomeric composites contains a significant number of carcinogenic and mutagenic compounds from the group of polycyclic aromatic hydrocarbons, PAHs, as well as polychlorinated dibenzo-p-dioxins and furans, PCDDs/Fs. By replacing carbon black with a specific amount of lignocellulose filler, we noticeably reduced the fire hazard caused by elastomeric composites. The lignocellulose filler reduced the parameters associated with the flammability of the tested composites, decreased the smoke emission, and limited the toxicity of gaseous decomposition products expressed as a toximetric indicator and the sum of PAHs and PCDDs/Fs. The natural filler also reduced emission of gases that constitute the basis for determination of the value of the toximetric indicator WLC50SM. The flammability and optical density of the smoke were determined in accordance with the applicable European standards, with the use of a cone calorimeter and a chamber for smoke optical density tests. PCDD/F and PAH were determined using the GCMS-MS technique. The toximetric indicator was determined using the FB-FTIR method (fluidised bed reactor and the infrared spectrum analysis). [ABSTRACT FROM AUTHOR]

Zika virus (ZIKV) diagnosis is currently performed through an invasive, painful, and costly procedure using molecular biology. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustainable method for ZIKV diagnosis is of great relevance. It is critical to prepare a global strategy for the next ZIKV outbreak given its devastating consequences, particularly in pregnant women. Attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy has been used to discriminate systemic diseases using saliva; however, the salivary diagnostic application in viral diseases is unknown. To test this hypothesis, we intradermally challenged interferon-gamma gene knockout C57/BL6 mice with ZIKV (50 µL,105 FFU, n = 7) or vehicle (50 µL, n = 8). Saliva samples were collected on day three (due to the peak of viremia) and the spleen was also harvested. Changes in the salivary spectral profile were analyzed by Student's t test (p < 0.05), multivariate analysis, and the diagnostic capacity by ROC curve. ZIKV infection was confirmed by real-time PCR of the spleen sample. The infrared spectroscopy coupled with univariate analysis suggested the vibrational mode at 1547 cm−1 as a potential candidate to discriminate ZIKV and control salivary samples. Three PCs explained 93.2% of the cumulative variance in PCA analysis and the spectrochemical analysis with LDA achieved an accuracy of 93.3%, with a specificity of 87.5% and sensitivity of 100%. The LDA-SVM analysis showed 100% discrimination between both classes. Our results suggest that ATR-FTIR applied to saliva might have high accuracy in ZIKV diagnosis with potential as a non-invasive and cost-effective diagnostic tool. [ABSTRACT FROM AUTHOR]

Previous studies of GNSS-IR mainly focused on the legacy L1C signal; the potential of modernized signals (L2C and L5Q) has not yet been fully exploited. In this paper, we applied the Multichannel Singular Spectrum Analysis (M-SSA) method to extract common interference patterns from different frequencies simultaneously. The three-frequency (L1C, L2C, and L5Q) signal-to-noise ratio (SNR) measurements from a total of 840 satellite rising and setting arcs, occurring between day of year 250 to 279 in year 2020 and 2021, were used. By comparing GNSS-IR reflector heights obtained from the original and M-SSA-reconstructed SNR time series, we found that M-SSA significantly improves the between-frequency consistency, as shown by an increase in the values of R-squared of linear regression from (0.69, 0.67, 0.89) to (0.95, 0.96, 0.98), and a decrease in RMSE from (0.10 m, 0.10 m, 0.06 m) to (0.04 m, 0.04 m, 0.02 m) for S1C-S2C, S1C-S5Q, and S2C-S5Q pair, respectively. Our results validate (1) the effectiveness of the M-SSA method in extracting common interference patterns from multi-frequency SNR time series, and (2) the superiority of modernized civil signals L2C and L5Q over the legacy L1C signal in GNSS-IR studies. We also emphasize the important role that the L5 signal will play in future GNSS-IR research because of its compatibility and interoperability among different satellite navigation systems. [ABSTRACT FROM AUTHOR]

Simple Summary: Bladder cancer is the sixth most incident neoplasm, and the average five-year survival rate drops to 5% for patients with the metastatic disease. Raman spectroscopy probes molecular vibrations by inelastic scattering of laser light. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates and label-free assessed by Raman microspectroscopic imaging. A data analysis workflow without preprocessing identified the locations and signatures of normal bladder, bladder cancer, necrosis, epithelium, and lipid inclusions. Furthermore, microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. Our approach with minimal user interference offers prospects for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices. Raman spectroscopy offers label-free assessment of bladder tissue for in vivo and ex vivo intraoperative applications. In a retrospective study, control and cancer specimens were prepared from ten human bladder resectates. Raman microspectroscopic images were collected from whole tissue samples in a closed chamber at 785 nm laser excitation using a 20× objective lens and 250 µm step size. Without further preprocessing, Raman images were decomposed by the hyperspectral unmixing algorithm vertex component analysis into endmember spectra and their abundancies. Hierarchical cluster analysis distinguished endmember Raman spectra that were assigned to normal bladder, bladder cancer, necrosis, epithelium and lipid inclusions. Interestingly, Raman spectra of microplastic particles, pigments or carotenoids were detected in 13 out of 20 specimens inside tissue and near tissue margins and their identity was confirmed by spectral library surveys. Hypotheses about the origin of these foreign materials are discussed. In conclusion, our Raman workflow and data processing protocol with minimal user interference offers advantages for future clinical translation such as intraoperative tumor detection and label-free material identification in complex matrices. [ABSTRACT FROM AUTHOR]

Simple Summary: One of the most important and hardest tasks during cancer diagnostics and operations is to differentiate between cancerous and non-malignant tissues. It is important to detect and remove all cancerous cells, but at the same time cut as little as possible non-malignant tissue. That is why there is now a high demand for methods that will help to recognize margins of cancer. One non-invasive, new and promising method is hyperspectral imaging (HSI) with the use of machine learning (ML). However, the output of the ML models is usually fuzzy, especially when pixel-wise classification methods are used. This research shows that, (1) the impact of particular pre-processing techniques on the performance of tissue recognition depends on the ML model used and its architecture and could be explained by the wavelengths emphasized by the models, and (2) that the application of post-processing can strongly improve performance (both sensitivity and specificity) and the ability to easily differentiate between tissue types. Background: Recent studies have shown that hyperspectral imaging (HSI) combined with neural networks can detect colorectal cancer. Usually, different pre-processing techniques (e.g., wavelength selection and scaling, smoothing, denoising) are analyzed in detail to achieve a well-trained network. The impact of post-processing was studied less. Methods: We tested the following methods: (1) Two pre-processing techniques (Standardization and Normalization), with (2) Two 3D-CNN models: Inception-based and RemoteSensing (RS)-based, with (3) Two post-processing algorithms based on median filter: one applies a median filter to a raw predictions map, the other applies the filter to the predictions map after adopting a discrimination threshold. These approaches were evaluated on a dataset that contains ex vivo hyperspectral (HS) colorectal cancer records of 56 patients. Results: (1) Inception-based models perform better than RS-based, with the best results being 92% sensitivity and 94% specificity; (2) Inception-based models perform better with Normalization, RS-based with Standardization; (3) Our outcomes show that the post-processing step improves sensitivity and specificity by 6.6% in total. It was also found that both post-processing algorithms have the same effect, and this behavior was explained. Conclusion: HSI combined with tissue classification algorithms is a promising diagnostic approach whose performance can be additionally improved by the application of the right combination of pre- and post-processing. [ABSTRACT FROM AUTHOR]

In this paper, the stabilization and high efficiency of an unstable Second Harmonic Generation (SHG) of an N d : Y V O 4 laser with a KTP intracavity is demonstrated. By using a passive Q-switching crystal ( C r 4 + : Y A G ) and a parametric modulation method (harmonic modulation), the stabilization of the laser is reached. An harmonic modulation was applied to the pumping of the N d : Y V O 4 -KTP laser to control the amplitude and frequency of the laser emission. The results were characterized by using power spectra analysis, optical spectrum, bifurcation diagrams, and temporal series of the laser intensity. The promising application of this green light source is materialized when such light is necessary for high-density optics, such as in the treatment materials industry or in some aesthetic applications. [ABSTRACT FROM AUTHOR]

This paper reports a study on the Intermediate Isolation System (IIS) applied to existing buildings. This kind of application is particularly suitable when a vertical addition is planned for buildings in seismic zones; in such a case, an isolation system can be placed at the base of the extension to prevent the increase, or, better, to reduce the seismic demand on the existing structure. In previous works, parametric response spectrum analyses have been carried out on lumped mass models by varying the period of the isolation system. As a result, a sort of IIS design spectrum has been derived and used for selecting design solutions for the vertical extension that minimize the overall seismic response. In this paper, the above design indications are assessed in the light of nonlinear time history analyses, accounting for the hysteretic response of the existing structure and the nonlinear behaviour of the isolation system. The IIS configurations are analysed and the results are discussed and compared in terms of peak response. In light of the obtained analysis results, the effectiveness and robustness of IIS applications for vertical extensions are discussed, and design implications are suggested. [ABSTRACT FROM AUTHOR]

The underwater gamma-ray spectrometer KATERINA was calibrated in a special tank and then demonstrated in the Southern Caspian Sea to determine the radioactivity levels in seawater as well as in the sediment. The simulated marine efficiency of the in situ detection system was validated analyzing the high energetic (1764 keV of 214Bi and 2614 keV of 208Tl) gamma-ray peaks using their known activity concentration as determined from the low energy emissions. The analysis of the in situ gamma-ray spectra in a short acquisition time period provided quantitative data for 226Ra and 232Th progenies as well as for 40K. A satisfactory analysis was performed for quantifying the observed energy peaks in the seawater and sediment measurements acquired at the south coast of the Caspian Sea. The spectrum in the water tank was also analyzed using full spectrum analysis methods, and the reproduced spectrum was in a very good agreement with the experimental spectrum giving as an output the activity concentrations of the observed radionuclides. [ABSTRACT FROM AUTHOR]

The area of forgery detection of documents is considered an active field of research in digital forensics. One of the most common issues that investigators struggle with is circled around the selection of the approach in terms of accuracy, complexity, cost, and ease of use. The literature includes many approaches that are based on either image processing techniques or spectrums analysis. However, most of the available approaches have issues related to complexity and accuracy. This article suggests an unsupervised forgery detection framework that utilizes the correlations among the spectrums of documents' matters in generating a weighted network for the tested documents. The network, then, is clustered using several unsupervised clustering algorithms. The detection rate is measured according to the number of network clusters. Based on the obtained results, our approach provides high accuracy using the Louvain clustering algorithms, while the use of the updated version of the DBSAN was more successful when testing many documents at the same time. Additionally, the suggested framework is considered simple to implement and does not require professional knowledge to use. [ABSTRACT FROM AUTHOR]

The intensity and frequency of the acoustic signals generated by different behaviors of largemouth bass (Micropterus salmoides) have different characteristics. The acoustic signals generated during feeding can be used to analyze the characteristic patterns of their used behavior, which can provide a theoretical basis for applications such as automatic feeding based on acoustic signals. We used passive acoustics combined with video to study the feeding acoustic signals of largemouth bass in a recirculating water culture system (4, 8, 12, and 16 fish/m3). The result of the time–frequency and power spectrum analysis of the feeding sound signals showed that the short-time average amplitude of the feeding signal was well distinguished from the background noise, both the swallowing and the chewing sounds were positively correlated with the culture density, and the correlation between the swallowing sound and number of fish was stronger; at different culture densities, the short-time average zero-crossing in the swallowing phase of the largemouth bass suddenly dropped to about 500 and rose to about 1000 in the chewing process. Therefore, both the chewing and the swallowing sounds can be used as parameters to automatically identify the largemouth bass feeding process signal. The spectrum entropy in the feeding process of the largemouth bass was maintained at about 4–6 for different culture densities. In the power spectrum, the main feeding sounding frequencies of the largemouth bass at different farming densities and the distinguishable spectral range of the background noised ranged from 1 to 20 kHz, the main peak frequency of the feeding sound was within the range of 1.2 to 3.0 kHz, and the main power value of the power spectrum was positively correlated with farming density. [ABSTRACT FROM AUTHOR]

The late Eocene succession of the Dongying Depression forms a highly productive hydrocarbon source. However, due to lack of an unambiguous fine chronostratigraphic framework for the late Eocene stratigraphy, it is challenging to understand the paleolake's evolution and the driven mechanism of lake-level variation, a limitation which hinders hydrocarbon exploration. In this work, high-resolution gamma-ray logging data were analyzed to carry out the cyclostratigraphic analysis of the third member (Es3) of the Shahejie Formation in the Dongying Depression. Significant 405-kyr eccentricity cycles were recognized based on time series analysis and statistical modeling of estimated sedimentation rates. We abstracted ~57 m cycles of the GR data in the Es3 member, which were comparable with the long eccentricity cycles (~405-kyr) of the La2004 astronomical solution, yielding a 6.43 Myr long astronomical time scale (ATS) for the whole Es3 member. The calibrated astronomical age of the third/fourth member of the Shahejie Formation boundary (41.21 Ma) was adopted as an anchor point for tuning our astrochronology, which provided an absolute ATS ranging from 34.78 ± 0.42 Ma to 41.21 ± 0.42 Ma in Es3. According to the ATS, sedimentary noise modeling for the reconstruction of lake-level changes was performed through the late Eocene Es3. The lake-level changes obtained based on sedimentary noise modeling and spectrum analysis reveal significant ~1.2 Myr cycles consistent with global sea level variations which were related to astronomical forcing. Potential driven mechanisms of marine incursion and/or groundwater table modulation were linked to explain the co-variation of global sea level changes and regional lake level changes. Our results suggest global sea level fluctuations may have played an important role in driving the hydroclimate and paleolake evolution of the late Eocene Dongying Depression. [ABSTRACT FROM AUTHOR]

In this study, special attention was paid to the correlation between the degree of ionization of the components and the effective formation of the complex under alkaline conditions. Using UV-Vis, 1H NMR, and CD, structural changes of the drug depending on the pH were monitored. In the pH range of 9.0 to 10.0, the G4.0 PAMAM dendrimer can bind 1 to 10 DOX molecules, while the efficiency increases with the concentration of the drug relative to the carrier. The binding efficiency was described by the parameters of loading content (LC = 4.80–39.20%) and encapsulation efficiency (EE = 17.21–40.16%), whose values increased twofold or even fourfold depending on the conditions. The highest efficiency was obtained for G4.0PAMAM-DOX at a molar ratio of 1:24. Nevertheless, regardless of the conditions, the DLS study indicates system aggregation. Changes in the zeta potential confirm the immobilization of an average of two drug molecules on the dendrimer's surface. Circular dichroism spectra analysis shows a stable dendrimer-drug complex for all the systems obtained. Since the doxorubicin molecule can simultaneously act as a therapeutic and an imaging agent, the theranostic properties of the PAMAM-DOX system have been demonstrated by the high fluorescence intensity observable on fluorescence microscopy. [ABSTRACT FROM AUTHOR]

To gain insight into photocatalytic behavior, transient absorption spectroscopy (TAS) was used to study LaCoxMn1−xO3, LaMnxNi1−xO3 and LaNixCo1−xO3 (x = 0, 0.2, 0.4, 0.6, 0.8 and 1.0) on a microsecond time scale. The results show that the electron lifetime is key to determining the photocatalytic reduction of CO2. This is the first time that the photogenerated electron lifetime in perovskite has been proposed to express the performance of the photocatalytic reduction of CO2 with H2O into CH4. In all cases, the decay curve can be well explained by two consecutive first-order kinetics, indicating that the electron exists within two major populations: one with a short lifetime and the other one with a long lifetime. The long-lived electrons are the rate-limiting species for the photocatalytic reaction and are related to the activity of the photocatalytic reduction of CO2 with H2O to produce CH4. For different photocatalysts, we find that the longer the electron decay lifetime is, the stronger the electron de-trapping ability is, and the electrons perform more activity. In this paper, TAS can not only detect the micro-dynamics process of carriers, but it is also demonstrated to be an easy and effective method for screening the most active catalyst in various catalysts for the photocatalytic reduction of CO2 with H2O accurately and quickly. [ABSTRACT FROM AUTHOR]

To provide spectroscopic data for W 13 + , the present work is focused on the analysis of spectra observed in the visible range, using a compact electron beam ion trap (CoBIT). Line identification is done by using a collisional radiative model, along with sophisticated structure calculations from FAC and GRASP2018. Most of the identified lines belong to magnetic dipole (M1) transitions between the levels of the 4 f 12 5 p 1 and 4 f 13 configurations. [ABSTRACT FROM AUTHOR]

The exploitation of urban-material spectral properties is of increasing importance for a broad range of applications, such as urban climate-change modeling and mitigation or specific/dangerous roof-material detection and inventory. A new spectral library dedicated to the detection of roof material was created to reflect the regional diversity of materials employed in Wallonia, Belgium. The Walloon Roof Material (WaRM) spectral library accounts for 26 roof material spectra in the spectral range 350–2500 nm. Spectra were acquired using an ASD FieldSpec3 Hi-Res spectrometer in laboratory conditions, using a spectral sampling interval of 1 nm. The analysis of the spectra shows that spectral signatures are strongly influenced by the color of the roof materials, at least in the VIS spectral range. The SWIR spectral range is in general more relevant to distinguishing the different types of material. Exceptions are the similar properties and very close spectra of several black materials, meaning that their spectral signatures are not sufficiently different to distinguish them from each other. Although building materials can vary regionally due to different available construction materials, the WaRM spectral library can certainly be used for wider applications; Wallonia has always been strongly connected to the surrounding regions and has always encountered climatic conditions similar to all of Northwest Europe. Dataset: https://doi.org/10.5281/zenodo.7414740 Dataset License: CC-BY-ND-SA-1.0 [ABSTRACT FROM AUTHOR]

This work communicates cavity ring-down spectroscopy (CRDS) of methylidyne (CH) in a chemiluminescent plasma that is produced in a microwave cavity. Of interest are the rotational lines of the 0-0 vibrational transition for the A–X band and the 1-0 vibrational transition for the B–X band. The reported investigations originate from research on the CH radical in 1996, which constituted the first case of applying CRDS to the CH radical. The report also includes a recent analysis that shows excellent agreement of the measured and computed data, and it communicates CH line strength data. The CH radical is an important diatomic molecule in hydrocarbon combustion diagnosis and the analysis of stellar plasma emissions, to name just two examples of analytical plasma chemistry. [ABSTRACT FROM AUTHOR]

This paper aims to detect railway vehicle wheel flats and polygonized wheels using an envelope spectrum analysis. First, a brief explanation of railway vehicle wheel problems is presented, focusing particularly on wheel flats and polygonal wheels. Then, three types of wheel flat profiles and three periodic out-of-roundness (OOR) harmonic order ranges for the polygonal wheels are evaluated in the simulations, along with analyses implemented using only healthy wheels for comparison. Moreover, the simulation implements track irregularity profiles modelled based on the US Federal Railroad Administration (FRA). From the numerical calculations, the dynamic responses of several strain gauges (SGs) and accelerometer sensors located on the rail between sleepers are evaluated. Regarding defective wheels, only the right wheel of the first wheelset is considered as a defective wheel, but the detection methodology works for various damaged wheels located in any position. The results from the application of the methodology show that the envelope spectrum analysis successfully distinguishes a healthy wheel from a defective one. [ABSTRACT FROM AUTHOR]

Acoustic emission (AE) testing and Lamb wave inspection techniques have been widely used in non-destructive testing and structural health monitoring. For thin plates, the AEs arising from structural defect development (e.g., fatigue crack propagation) propagate as Lamb waves, and Lamb wave modes can be used to provide important information about the growth and localisation of defects. However, few sensors can be used to achieve the in situ wavenumber–frequency modal decomposition of AEs. This study explores the ability of a new multi-element piezoelectric sensor array to decompose AEs excited by pencil lead breaks (PLBs) on a thin isotropic plate. In this study, AEs were generated by out-of-plane (transverse) and in-plane (longitudinal) PLBs applied at the edge of the plate, and waveforms were recorded by both the new sensor array and a commercial AE sensor. Finite element analysis (FEA) simulations of PLBs were also conducted and the results were compared with the experimental results. To identify the wave modes present, the longitudinal and transverse PLB test results recorded by the new sensor array at five different plate locations were compared with FEA simulations using the same arrangement. Two-dimensional fast Fourier Transforms were then applied to the AE wavefields. It was found that the AE modal composition was dependent on the orientation of the PLB direction. The results suggest that this new sensor array can be used to identify the AE wave modes excited by PLBs in both in-plane and out-of-plane directions. [ABSTRACT FROM AUTHOR]

Observing the curing reaction of epoxy resins is a key to quality assurance in fibre composite production. The evaluation of electrical impedance spectra is an established monitoring method. Such impedance spectra contain the physical effects of dipole relaxation, ionic conduction and electrode polarisation, which shift to lower frequencies as curing progresses. In the early stage of the curing reaction, ionic conductivity and electrode polarisation dominate, and in the later stage of the curing reaction, dipole relaxation dominates. Due to the shift of the effects over several frequency decades, it makes sense to evaluate electrical impedance spectra not exclusively at one frequency but over an entire available frequency spectrum. The measured spectral raw data cannot be easily interpreted by a control algorithm and have to be mapped to simpler key indicators. For this purpose, a frequency-dependent model is proposed to address the aforementioned physical effects. With only five free parameters, measured spectra can be described with a relative error of only 2.3%. The shift of the occurring effects to lower frequencies necessitates switching the key indicator used in the progression of the cure reaction. [ABSTRACT FROM AUTHOR]

Background: Portable electroencephalogram (EEG) systems are often used in health care applications to record brain signals because their ease of use. An electrooculogram (EOG) is a common, low frequency, high amplitude artifact of the eye blink signal that might confuse disease diagnosis. As a result, artifact removal approaches in single EEG portable devices are in high demand. Materials: Dataset 2a from the BCI Competition IV was employed. It contains the EEG data from nine subjects. To determine the EOG effect, each session starts with 5 min of EEG data. This recording lasted for two minutes with the eyes open, one minute with the eyes closed, and one minute with eye movements. Methodology: This article presents the automated removal of EOG artifacts from EEG signals. Circulant Singular Spectrum Analysis (CiSSA) was used to decompose the EOG contaminated EEG signals into intrinsic mode functions (IMFs). Next, we identified the artifact signal components using kurtosis and energy values and removed them using 4-level discrete wavelet transform (DWT). Results: The proposed approach was evaluated on synthetic and real EEG data and found to be effective in eliminating EOG artifacts while maintaining low frequency EEG information. CiSSA-DWT achieved the best signal to artifact ratio (SAR), mean absolute error (MAE), relative root mean square error (RRMSE), and correlation coefficient (CC) of 1.4525, 0.0801, 18.274, and 0.9883, respectively. Comparison: The developed technique outperforms existing artifact suppression techniques according to performance measures. Conclusions: This advancement is important for brain science and can contribute as an initial pre-processing step for research related to EEG signals. [ABSTRACT FROM AUTHOR]

Special species of Burmese amber are highly valued within the gemological market due to their fancy optical characteristics. However, some ordinary amber species are misidentified as precious species, which has disrupted consumers' purchasing behavior and the market order. In this study, seven Burmese amber species (golden, golden-blue, blood-tea, black-tea, green-tea, brownish-red, and 'chameleon' amber) were collected and investigated. By using conventional gemological tests, Fourier transform infrared (FTIR), three-dimensional (3D) fluorescence, and photoluminescence (PL) spectrometers, detailed analyses were performed on unique species. The FTIR spectra identified that there are three groups of peaks that can distinguish Burmese amber from any other origin. Additionally, the 'Chameleon' amber exhibited special patterns in the third group, which might be due to its internal aromatic hydrocarbons structures that are different from any other species. The 3D fluorescence spectra displayed that all seven species presented similar fluorescence behavior—the 334 or 347 nm emission wavelength could be optimally excited by 240 or 294 nm excitation wavelength in the ultraviolet region and the 380 ± 10 nm or 400 ± 10 nm excitation wavelength optimally excited the 430 nm emission wavelength in the violet region. In the red region, green-tea amber, black-tea amber, and brownish-red amber presented totally different fluorescence behavior, which could be regarded as a reference feature for differentiation. Obvious pink fluorescence on the surface of the tea amber was efficiently found under PL spectra, and we firstly suggest this test could be used as an effective way to distinguish black-tea amber from green-tea amber and some ordinary species (such as blood-tea amber). Both the PL and 3D fluorescence measurements demonstrated the different luminescence behavior of tea amber in the red region, which might be related to the type and content of red fluorescent substances in the tea amber. [ABSTRACT FROM AUTHOR]

This study has systematically investigated the atomic number (Z) dependence of spectra from gallium-like (Ga-like) ions of heavy elements. We have mainly analyzed the experimental spectra recorded in high-temperature plasmas produced in the Large Helical Device (LHD) for various elements with atomic numbers from 57 onward. The measured wavelengths are compared with theoretical values calculated with a multi-configuration Dirac Fock code. As a result, we have successfully obtained Z-dependent wavelengths of several prominent transitions of Ga-like ions, including a magnetic dipole (M1) transition. Many of them have been experimentally identified for the first time in this study. The present results manifest the significant effects of configuration interaction and spin–orbit interaction for highly charged heavy ions. [ABSTRACT FROM AUTHOR]

The rolling bearing is an important part of mechanical equipment, and its performance significantly affects the quality and life of the mechanical equipment. This article uses the integrated fiber Bragg grating resonant structure sensor excited by periodic micro-shocks caused by micro faults to realize the extraction of information relating to potential faults. Because the fault signal is weak and can easily be interfered with by ambient noise, in order to extract the effective signal, this article determines the autoregressive model of bearing vibration by the final prediction error criterion and the recursive least squares estimation algorithm. The augmented state space model is established based on the autoregressive model. A Kalman filter is used to reduce the noise interference, and then the reduction noisy signal is analyzed by power spectrum and improved autocorrelation envelope spectrum to realize the detection of bearing faults. Through data analysis and method comparison, the proposed improved autocorrelation envelope spectrum analysis can directly extract the bearing fault frequency, which is superior to other methods such as cepstral analysis. [ABSTRACT FROM AUTHOR]

This paper identifies mechanical vibrations occurring in the operating environment of hydraulic systems used in marine engineering. Particular attention was paid to the influence of periodic vibrations on changes in the amplitude-frequency spectrum in a marine hydraulic system. For the case of analysing the effect of vibration on changes in the pressure pulsation spectrum with a proportional directional valve, a modified mathematical model was used. Experimental results were presented and compared with the results obtained from the mathematical model. A way of limiting the transmission of vibrations to the directional control valve body was proposed. [ABSTRACT FROM AUTHOR]

In this paper, a series of tests were conducted on the bearings of induction motors to investigate vibration signal analysis-based diagnosis of bearing faults, and a thorough analysis was also conducted. In the engineering field, the kurtosis coefficient of vibration acceleration and the root mean square of vibration velocity, as well as resonant demodulated spectrum analysis of vibration acceleration, have been widely used for bearing fault diagnosis. These are integrated in almost any commercially available device for diagnosing bearing faults. However, the unsuitable use of these devices results in many false diagnoses. In light of this, they were selected as research objects and were investigated experimentally. In three induction motors, faults of different severity in the bearing outer race and cage were modeled for tests, and the corresponding results were used to evaluate the performance of the selected diagnosis methods. Some vague information in engineering was clarified, and some instructive rules were outlined to improve the bearing fault diagnosis performance. Taking the kurtosis coefficient of vibration acceleration (Ku) as an example, in engineering, Ku = 4 is generally taken as the diagnostic threshold of bearing faults. This means the following rule applies: if Ku ≤ 4, the bearing is healthy; otherwise, the bearing is faulty. However, the test results in this paper show that even if Ku ≤ 4, the bearing might be faulty; if Ku > 4, the bearing is indeed faulty. Therefore, the diagnostic rule should be improved as follows: if Ku > 4, the bearing is faulty (which can be assured), and if Ku ≤ 4, the status of the bearing is still undetermined. Thus, this paper can be helpful for researchers to gain an experimental understanding of the selected diagnosis methods and provides some improved rules on their use for reducing false diagnoses. [ABSTRACT FROM AUTHOR]

The article deals with the detection of stress using the electrodermal activity (EDA) signal measured at the wrist. We present an approach for feature extraction from EDA. The approach uses frequency spectrum analysis in multiple frequency bands. We evaluate the proposed approach using the 4 Hz EDA signal measured at the wrist in the publicly available Wearable Stress and Affect Detection (WESAD) dataset. Seven existing approaches to stress detection using EDA signals measured by wrist-worn sensors are analysed and the reported results are compared with ours. The proposed approach represents an improvement in accuracy over the other techniques studied. Moreover, we focus on time to detection (TTD) and show that our approach is able to outperform competing techniques, with fewer data points. The proposed feature extraction is computationally inexpensive, thus the presented approach is suitable for use in real-world wearable applications where both short response times and high detection performance are important. We report both binary (stress vs. no stress) as well as three-class (baseline/stress/amusement) results. [ABSTRACT FROM AUTHOR]

Attention refers to the human psychological ability to focus on doing an activity. The attention assessment plays an important role in diagnosing attention deficit hyperactivity disorder (ADHD). In this paper, the attention assessment is performed via a classification approach. First, the single-channel electroencephalograms (EEGs) are acquired from various participants when they perform various activities. Then, fast Fourier transform (FFT) is applied to the acquired EEGs, and the high-frequency components are discarded for performing denoising. Next, empirical mode decomposition (EMD) is applied to remove the underlying trend of the signals. In order to extract more features, singular spectrum analysis (SSA) is employed to increase the total number of the components. Finally, some typical models such as the random forest-based classifier, the support vector machine (SVM)-based classifier, and the back-propagation (BP) neural network-based classifier are used for performing the classifications. Here, the percentages of the classification accuracies are employed as the attention scores. The computer numerical simulation results show that our proposed method yields a higher classification performance compared to the traditional methods without performing the EMD and SSA. [ABSTRACT FROM AUTHOR]

The combination of advanced radar sensor technology and smart grid has broad prospects. It is meaningful to monitor the respiration and heartbeat of grid employees under resting state through radar sensors to ensure that they are in a healthy working state. Ultra-wideband (UWB) radar sensor is suitable for this application because of its strong penetration ability, high range resolution and low average power consumption. However, due to weak heartbeat amplitude and measurement noise, the accurate measurement of the target heart rate is a challenge. In this paper, singular spectrum analysis (SSA) is proposed to reconstruct the eigenvalues of noisy vital signs to eliminate noise peaks around the heartbeat rate; combined with the variational modal decomposition (VMD), the target vital signs can be extracted with high accuracy. The experiment confirmed that the target vital sign information can be extracted with high accuracy from ten subjects at different distances, which can play an important role in short distance human detection and vital sign monitoring. [ABSTRACT FROM AUTHOR]

Addressing insufficient and irregular sampling is a difficult challenge in seismic processing and imaging. Recently, rank reduction methods have become popular in seismic processing algorithms for simultaneous denoising and interpolating. These methods are based on rank reduction of the trajectory matrices using truncated singular value decomposition (TSVD). Estimation of the ranks of these trajectory matrices depends on the number of plane waves in the processing window; however, for the more complicated data, the rank reduction method may fail or give poor results. In this paper, we propose an adaptive weighted rank reduction (AWRR) method that selects the optimum rank in each window automatically. The method finds the maximum ratio of the energy between two singular values. The AWRR method selects a large rank for the highly curved complex events, which leads to remaining residual errors. To overcome the residual errors, a weighting operator on the selected singular values minimizes the effect of noise projection on the signal projection. We tested the efficiency of the proposed method by applying it to both synthetic and real seismic data. [ABSTRACT FROM AUTHOR]

We present a thorough structural characterization of Graphene Nano Particles (GNPs) prepared by means of physical procedures, i.e., ball milling and ultra-sonication of high-purity synthetic graphite. UV-vis absorption/extinction spectroscopy, Dynamic Light Scattering, Transmission Electron Microscopy, IR and Raman spectroscopies were performed. Particles with small size were obtained, with an average lateral size = 70–120 nm, formed by few = 1–10 stacked layers, and with a small number of carboxylic groups on the edges. GNPs relatively more functionalized were separated by centrifugation, which formed stable water dispersions without the need for any surfactant. A critical reading and unified interpretation of a wide set of spectroscopic data was provided, which demonstrated the potential of Specular Reflectance Infrared Spectroscopy for the diagnosis and quantification of chemical functionalization of GNPs. Raman parameters commonly adopted for the characterization of graphitic materials do not always follow a monotonic trend, e.g., with the particle size and shape, thus unveiling some limitations of the available spectroscopic metrics. This issue was overcome thanks to a comparative spectra analysis, including spectra deconvolution by means of curve fitting procedures, experiments on reference materials and the exploitation of complementary characterization techniques. [ABSTRACT FROM AUTHOR]

Simple Summary: Non-muscle-invasive bladder cancer (NMIBC) is a complicated locally treated disease with high recurrence rates and high risk of progression to muscle invasive disease. Current standard diagnostic approach based on white light cystoscopy (WLC) is characterized by high false negative rate, excessive invasion of the bladder and high economic burden. Hereby we present the fiber-based attenuated total reflection infrared (ATR IR) spectroscopy study of healthy and cancerous tissue samples taken from 54 patients to delineate normal and tumorous human bladder tissues under ex vivo conditions. Investigation of the tissue samples immediately after surgical operation allows to examine samples in their native conditions and establish their initial structure and chemical composition avoiding sample degradation. Our study reveals that fiber-based ATR IR spectroscopy could be an addition to current endoscopic approach with increased diagnostic accuracy and with some potential to be applied in vivo. Surgical treatment is widely applied curative approach for bladder cancer. White light cystoscopy (WLC) is currently used for intraoperative diagnostics of malignant lesions but has relatively high false-negative rate. Here we represent an application of label free fiber-based attenuated total reflection infrared spectroscopy (ATR IR) for freshly resected human bladder tissue examination for 54 patients. Defined molecular spectral markers allow to identify normal and urothelial carcinoma tissues. While methods of statistical analysis (Hierarchical cluster analysis (HCA) and Principal component analysis (PCA)) used for spectral data treatment allow to discriminate tissue types with 91% sensitivity and 96–98% specificity. In the present study the described method was applied for tissue examination under ex vivo conditions. However, after method validation the equipment could be translated from laboratory studies to in situ or even in vivo studies in operating room. [ABSTRACT FROM AUTHOR]