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To optimize the seismic performance of a new type of steel-concrete tower, a 120 m steel-concrete composite tower model with a tuned mass damper (TMD) was constructed in ABAQUS for simulation analysis. Firstly, a time history analysis was conducted to study the towers with and without a TMD to determine the difference in their accelerations, velocities, and displacements. Then, a frequency spectrum analysis was performed to determine the tower vibration reduction effect of TMDs with different mass ratios. Five different cases were considered to explore the impact of different layouts on the dynamic performance of the tower. The results showed that the TMD had a significant vibration reduction effect on the tower accelerations, velocities, and displacements. The acceleration was reduced the most, while the vibration reduction effect in the middle of the tower was more significant than that at the top of the tower. For the steel-concrete tower studied in this paper, the optimal mass ratio of TMD was found to be 0.01. Placing one TMD at the top and another in the middle of the tower was found to be the optimal TMD arrangement for tower vibration reduction. [ABSTRACT FROM AUTHOR]

Humic substances have a potential role in the fate and transport of toxic metal ions in the environment due to their colloidal characteristics and abundant surface functional groups. Batch techniques (DLS, EPM, FT-IR and fluorescence EEM) were developed to assess the aggregation mechanisms of humic acid (HA) reacting with Cs+ or Co2+ electrolyte ions in this work. The kinetic experimental results indicated that a much lower Co2+ ion concentration (0.03–1.50 mmol/L) induced rapid aggregation of HA compared to that of Cs+ (3.0–15 mmol/L), and the divalent Co2+ ion was far more effective in enhancing HA aggregation than monovalent Cs+. The aggregation kinetics of HA were also found to be pH-dependent, and a much lower pH condition (pH 5.0) caused more rapid aggregation (the largest hydrodynamic diameter of ~3000 nm) compared to those at pH 7.0 (the largest hydrodynamic diameter of ~2000 nm). Positively charged metal ions in the solution can lower the electrostatic repulsive force between HA molecules through charge neutralization, thus leading to the rapid aggregation of HA aggregates. Furthermore, the carboxylic and phenolic groups on the HA surface were also involved in the aggregation reaction to form inner complexes and accelerate the aggregation process. [ABSTRACT FROM AUTHOR]

In general, studies on short-term hourly electricity load modeling and forecasting do not investigate in detail the sources of uncertainty in forecasting. This study aims to evaluate the impact and benefits of applying bootstrap aggregation in overcoming the uncertainty in time series forecasting, thereby increasing the accuracy of multistep ahead point forecasts. We implemented the existing and proposed clustering-based bootstrapping methods to generate new electricity load time series. In the proposed method, we use singular spectrum analysis to decompose the series between signal and noise to reduce the variance of the bootstrapped series. The noise is then bootstrapped by K-means clustering-based generation of Gaussian normal distribution (KM.N) before adding it back to the signal, resulting in the bootstrapped series. We apply the benchmark models for electricity load forecasting, SARIMA, NNAR, TBATS, and DSHW, to model all new bootstrapped series and determine the multistep ahead point forecasts. The forecast values obtained from the original series are compared with the mean and median across all forecasts calculated from the bootstrapped series using the Malaysian, Polish, and Indonesian hourly load series for 12, 24, and 36 steps ahead. We conclude that, in this case, the proposed bootstrapping method improves the accuracy of multistep-ahead forecast values, especially when considering the SARIMA and NNAR models. [ABSTRACT FROM AUTHOR]

Simple Summary: In order to realize rapid and complete pre-screening in the pathological examination of gastric cancer and assist in quickly determining the boundary between cancerous and healthy cells, we developed a fast-scanning near-field terahertz (THz) imaging system. This imaging system is compact, low-cost, and easy to operate. THz examination does not need any processing after sectioning, and the diagnostic results are directly displayed in images within one minute. Compared with the H&E staining method, THz imaging diagnosis uses a quantitative absorption coefficient to distinguish cancer tissue and healthy tissue, which makes the automation of the tissue sampling pre-screening procedure possible and will save valuable time to help quickly define cancer tissue. At the same time, the spatial resolution of our near-field imaging system reaches λ/17. Using THz imaging to accurately define the margins of cancer can not only conserve healthy tissues but also minimize the number of second surgical procedures, which would save a lot of additional hospital resources. The distinguishable absorption contrast among healthy gastric tissues, carcinoma in situ and cancer tissues in the THz frequency range is one of the keys to realizing gastric cancer diagnosis by THz imaging. Based on microwave devices and a sub-wavelength fiber, we developed a fast-scanning THz imaging system combined with the principle of surface plasmon resonance enhancement. This imaging system has a near-field λ/17 spatial resolution and imaging S/N ratio as high as 108:1, and the image results are directly displayed within 1 min. We also successfully demonstrated the image diagnostic capability on sliced tissues from eight patients with gastric cancer. The results indicate that THz absorption images can not only clearly distinguish cancer tissue from healthy tissues but also accurately define the margins of cancer. Through a medical statistical study of 40 sliced tissues from 40 patients, we prove that THz imaging can be used as a standalone method to diagnose gastric cancer tissues with a diagnostic specificity and sensitivity of 100%. Compared with the H&E staining method, THz imaging diagnosis makes the automation of tissue-sampling pre-screening procedure possible and assists in quickly determining the boundary between cancerous and healthy tissues. [ABSTRACT FROM AUTHOR]

This study is the first in the region to use Global Precipitation Mission Dual-Frequency Precipitation Radar (GPM-DPR) and Fengyun-2G (FY-2G) observations to qualitatively and quantitatively study the Southwest Vortex evolution characteristics during the flood season from 2019 to 2021. Furthermore, vertical characteristics of the two main precipitation types in the Southwest Vortex, stratiform and convective, were statistically analyzed at different life stages, including horizontal and vertical distribution of precipitation particles, droplet spectrum characteristics, and vertically layered precipitation contribution. The results showed that: (1) The typical convective precipitation (CP) in the developing and mature stages has strong reflectivity distribution centers in the upper and lower layers, showing characteristics related to terrain. Additionally, the high-level hydrometeor particles are mainly solid precipitation particles, and particles in the lower layers collide and coalesce in the violent vertical motion of the airflow. (2) For the three stages of CP, the reflectivity below melting layer (ML) first showed a rapid weakening trend toward the surface and then remained unchanged, significantly changing its vertical structure. The main rainfall type of the Southwest Vortex system was stratiform precipitation (SP) in the three stages. (3) In the two types of cloud precipitation, the developing stage is generally composed of large and sparse precipitation particles, the mature stage of large and dense precipitation particles, and the dissipating stage of small and sparse precipitation particles. The findings of this study reveal the three-dimensional refined structure and vertical variation characteristics of different life stages of the Southwest Vortex precipitation cloud system and provide important tools and references for improving the accuracy of numerical models and the forecast level of short-term heavy precipitation under complex terrain. [ABSTRACT FROM AUTHOR]

Mobility spectrum analysis (MSA) is a method that enables the carrier density (and mobility) separation of the majority and minority carriers in multicarrier semiconductors, respectively. In this paper, we use the p-GaAs layer in order to demonstrate that the MSA can perform unique facilities for the defect analysis by using its resolvable features for the carriers. Using two proven methods, we reveal that the defect state can be anticipated at the characteristic temperature T d e e p , in which the ratio ( R N n / N h ) that is associated with the density of the minority carrier N n , to the density of the majority carrier N h , exceeds 50%. (1) Using a p-GaAs Schottky diode in a reverse bias regime, the position of the deep level transient spectroscopy (DLTS) peak is shown directly as the defect signal. (2) Furthermore, by examining the current–voltage–temperature (I–V–T) characteristics in the forward bias regime, this peak position has been indirectly revealed as the generation–recombination center. The DLTS signals are dominant around the T d e e p , according to the window rate, and it has been shown that the peak variation range is consistent with the temperature range of the temperature-dependent generation–recombination peak. The T d e e p is also consistent with the temperature-dependent thermionic emission peak position. By having only R N n / N h through the MSA, it is possible to intuitively determine the existence and the peak position of the DLTS signal, and the majority carrier's density enables a more accurate extraction of the deep trap density in the DLTS analysis. [ABSTRACT FROM AUTHOR]

The developed method of steganographic hiding of text information in an audio signal based on the wavelet transform acquires a deep meaning in the conditions of the use by an attacker of deliberate unauthorized manipulations with a steganocoded audio signal to distort the text information embedded in it. Thus, increasing the robustness of the stego-system by compressing the steganocoded audio signal subject to the preservation of the integrity of text information, taking into account the features of the psychophysiological model of sound perception, is the main objective of this scientific research. The task of this scientific research is effectively solved using a multilevel discrete wavelet transform using adaptive block normalization of text information with subsequent recursive embedding in the low-frequency component of the audio signal and further scalar product of the obtained coefficients with the Daubechies wavelet filters. The results of the obtained experimental studies confirm the hypothesis, namely that it is proposed to use recursive embedding in the low-frequency component (approximating wavelet coefficients) followed by their scalar product with wavelet filters at each level of the wavelet decomposition, which will increase the average power of hidden data. It should be noted that upon analyzing the existing method, which is based on embedding text information in the high-frequency component (detailed wavelet coefficients), at the last level of the wavelet decomposition, we obtained the limit CR = 6, and in the developed, CR = 20, with full integrity of the text information in both cases. Therefore, the resistance of the stego-system is increased by 3.3 times to deliberate or passive compression of the audio signal in order to distort the embedded text information. [ABSTRACT FROM AUTHOR]

To study the specific features of free surface oscillations in the northwestern part of Posyet Bay (the Sea of Japan), a series of experimental works using an installation with a laser meter for measuring hydrosphere pressure variations were carried out in 2012 and 2014. In the course of the joint analysis, measurement results for oscillations with periods of 10–30 min and the results of calculations using a numerical model of shallow water with a difference approximation on an irregular triangular space grid, datasets of the space–time parameters for the resonance oscillations of the studied water area were obtained. The results of the numerical simulations confirm the manifestation of the resonance properties of Novgorodskaya, Expedicii, and Reyd Pallada Bays water areas on the oscillations singled out during the experimental studies. The positions of the peaks on the model resonance curves are consistent with the positions of the clearly pronounced peaks of the energy spectrum in the field data. [ABSTRACT FROM AUTHOR]

We studied the spectral-luminescent properties of (ZrO2)0.805(Y2O3)0.188(Pr2O3)0.007 and (ZrO2)0.802(Y2O3)0.195(Pr2O3)0.003 crystals grown by directional melt crystallization in a cold skull. Analysis of the absorption spectra of the crystals suggested the presence of Pr3+ and Pr4+ ions. Measurement of the relative intensities of the luminescence bands corresponding to the 3P0 → 3H4,5, 3P0 → 3F2,3,4, 3P1 → 3H5 and 1D2 → 3H4 optical transitions of the Pr3+ ions, and analysis of luminescence extinction kinetics for the 3P0 and 1D2 levels of the Pr3+ ions, suggests the presence of cross-relaxation (1D2 → 1G4) → (3H4 → 3F4) of the Pr3+ ions in the ZrO2-Y2O3-Pr2O3 crystals. [ABSTRACT FROM AUTHOR]

The development of primary frequency regulation (FR) technology has prompted wind power to provide support for active power control systems, and it is critical to accurately assess and predict the wind power FR potential. Therefore, a prediction model for wind power virtual inertia and primary FR potential is proposed. Firstly, the primary FR control mode is divided and the mapping relationship of operating wind speed and FR potential is constructed. Secondly, a hybrid prediction method of singular spectrum analysis (SSA) and Gaussian process regression (GPR) is proposed for predicting the speed of wind. Finally, the wind speed sequence is adopted to calculate the FR potential with various regulation modes in future time. The results show the advantages of the proposed method in the prediction accuracy of wind power FR potential and the ability to characterize the uncertainty information of the prediction results. Accurate modeling and prediction of wind power FR potential can significantly promote wind turbines to implement fine control of primary FR and optimal allocation of FR capacity within wind farm and group. Based on the actual operation data, the deterministic prediction and probability prediction of the FR potential of wind farms are conducted in this paper. [ABSTRACT FROM AUTHOR]

Simple Summary: The complete removal of cancerous tissue is an important predictor of patient outcomes after surgery, in particular for head and neck cancer surgery. Normally, surgical tissues are examined by a pathologist to determine whether a full removal of the cancer was performed. However, these analyses are often imperfect due to time constraints, limitations in frozen sections, and tissue orientation challenges. Newer intraoperative imaging techniques have shown great promise for increasing both the accuracy and efficiency of this process while in the operating room. This review summarizes and analyzes the current state of the literature on intraoperative imaging in determining cancer margins in head and neck cancers. Surgical margin status is one of the strongest prognosticators in predicting patient outcomes in head and neck cancer, yet head and neck surgeons continue to face challenges in the accurate detection of these margins with the current standard of care. Novel intraoperative imaging modalities have demonstrated great promise for potentially increasing the accuracy and efficiency in surgical margin delineation. In this current study, we collated and analyzed various intraoperative imaging modalities utilized in head and neck cancer to evaluate their use in discriminating malignant from healthy tissues. The authors conducted a systematic database search through PubMed/Medline, Web of Science, and EBSCOhost (CINAHL). Study screening and data extraction were performed and verified by the authors, and more studies were added through handsearching. Here, intraoperative imaging modalities are described, including optical coherence tomography, narrow band imaging, autofluorescence, and fluorescent-tagged probe techniques. Available sensitivities and specificities in delineating cancerous from healthy tissues ranged from 83.0% to 100.0% and 79.2% to 100.0%, respectively, across the different imaging modalities. Many of these initial studies are in small sample sizes, with methodological differences that preclude more extensive quantitative comparison. Thus, there is impetus for future larger studies examining and comparing the efficacy of these intraoperative imaging technologies. [ABSTRACT FROM AUTHOR]

The accurate mapping of urban impervious surfaces from remote sensing images is crucial for understanding urban land-cover change and addressing impervious-surface-change-related environment issues. To date, the authors of most studies have built indices to map impervious surfaces based on shortwave infrared (SWIR) or thermal infrared (TIR) bands from middle–low-spatial-resolution remote sensing images. However, this limits the use of high-spatial-resolution remote sensing data (e.g., GaoFen-2, Quickbird, and IKONOS). In addition, the separation of bare soil and impervious surfaces has not been effectively solved. In this article, on the basis of the spectra analysis of impervious surface and non-impervious surface (vegetation, water, soil and non-photosynthetic vegetation (NPV)) data acquired from world-recognized spectral libraries and Sentinel-2 MSI images in different regions and seasons, a novel spectral index named the Normalized Impervious Surface Index (NISI) was proposed for extracting impervious area information by using blue, green, red and near-infrared (NIR) bands. We performed comprehensive assessments for the NISI, and the results demonstrated that the NISI provided the best studied performance in separating the soil and impervious surfaces from Sentinel-2 MSI images. Furthermore, regarding impervious surfaces mapping accuracy, the NISI had an overall accuracy (OA) of 89.28% (±0.258), a producer's accuracy (PA) of 89.76% (±1.754), and a user's accuracy (UA) of 90.68% (±1.309), which were higher than those of machine learning algorithms, thus supporting the NISI as an effective measurement for urban impervious surfaces mapping and analysis. The results indicate the NISI has a high robustness and a good applicability. [ABSTRACT FROM AUTHOR]

Due to the relative insufficiencies of conventional time-domain waveform and spectrum analysis in fault diagnosis research, a diesel engine fault diagnosis method based on the Stacked Sparse Autoencoder and the Support Vector Machine is proposed in this study. The method consists of two main steps. The first step is to utilize the Stacked Sparse Autoencoder (SSAE) to reduce the feature dimension of the multi-sensor vibration information; when compared with other dimension reduction methods, this approach can better capture nonlinear features, so as to better cope with dimension reduction. The second step consists of diagnosing faults, implementing the grid search, and K-fold cross-validation to optimize the hyperparameters of the SVM method, which effectively improves the fault classification effect. By conducting a preset failure experiment for the diesel engine, the proposed method achieves an accuracy rate of more than 98%, better engineering application, and promising outcomes. [ABSTRACT FROM AUTHOR]

Hot-wire anemometric measurements are often related to the determination of flow parameters in a high frequency range. Such knowledge is particularly important when analyzing the flow phenomena in the vicinity of wind turbines. The reliability of obtained results is determined by the knowledge of the properties of the system used for measurements. It concerns both the static and dynamic characteristics of individual measurement channels. In studies of hot-wire anemometric systems, a problem related to the unstable transmission bands of such systems and their high dependence on measurement conditions and the system configuration itself has been commonly indicated. This paper presents the results of an investigation of a new type of hot-wire anemometer, allowing for automatic adjustment of its dynamic characteristics under real working conditions. The presented system is dedicated to the analysis of the wind energy spectrum in experimental laboratory tests on reduced-scale models and to specialized in situ measurements. [ABSTRACT FROM AUTHOR]

Solvent-free preparation types for cyclodextrin complexation, such as co-grinding, are technologies desired by the industry. However, in-depth analytical evaluation of the process and detailed characterization of intermediate states of the complexes are still lacking in areas. In our work, we aimed to apply the co-grinding technology and characterize the process. Fenofibrate was used as a model drug and dimethyl-β-cyclodextrin as a complexation excipient. The physical mixture of the two substances was ground for 60 min; meanwhile, samples were taken. A solvent product of the same composition was also prepared. The intermediate samples and the final products were characterized with instrumental analytical tools. The XRPD measurements showed a decrease in the crystallinity of the drug and the DSC results showed the appearance of a new crystal form. Correlation analysis of FTIR spectra suggests a three-step complexation process. In vitro dissolution studies were performed to compare the dissolution properties of the pure drug to the products. Using a solvent-free production method, we succeeded in producing a two-component system with superior solubility properties compared to both the active ingredient and the product prepared by the solvent method. The intermolecular description of complexation was achieved with a detailed analysis of FTIR spectra. [ABSTRACT FROM AUTHOR]

Simple Summary: Beckwith–Wiedemann syndrome (BWS, OMIM 130650) is an inborn overgrowth disorder caused by molecular alterations in chromosome 11p15.5. These molecular changes affect so-called imprinted genes, i.e., genes which underlie a complex regulation which is linked to the parental origin of the gene copy. Thus, either the maternal gene copy is expressed or the paternal, but this balanced regulation is prone to disturbances. In fact, different types of molecular variants have been identified in BWS, resulting in a variable phenotype; thus, it was consented that the syndromic entity was extended to the Beckwith–Wiedemann spectrum (BWSp). Some molecular subgroups of BWSp are associated with an increased embryonic tumor risk and have different likelihoods for specific tumors. Therefore, the precise determination of the molecular subgroup is needed for precise monitoring and treatment, but the molecular diagnostic procedure has several limitations and challenges which have to be considered. Beckwith–Wiedemann syndrome (BWS, OMIM 130650) is a congenital imprinting condition with a heterogenous clinical presentation of overgrowth and an increased childhood cancer risk (mainly nephroblastoma, hepatoblastoma or neuroblastoma). Due to the varying clinical presentation encompassing classical, clinical BWS without a molecular diagnosis and BWS-related phenotypes with an 11p15.5 molecular anomaly, the syndromic entity was extended to the Beckwith–Wiedemann spectrum (BWSp). The tumor risk of up to 30% depends on the molecular subtype of BWSp with causative genetic or epigenetic alterations in the chromosomal region 11p15.5. The molecular diagnosis of BWSp can be challenging for several reasons, including the range of causative molecular mechanisms which are frequently mosaic. The molecular basis of tumor formation appears to relate to stalled cellular differentiation in certain organs that predisposes persisting embryonic cells to accumulate additional molecular defects, which then results in a range of embryonal tumors. The molecular subtype of BWSp not only influences the overall risk of neoplasia, but also the likelihood of specific embryonal tumors. [ABSTRACT FROM AUTHOR]

Realizing the rapid measurement of coal moisture content (MC) is of great significance. However, existing measurement methods are time-consuming and damage the original properties of the samples. To address these concerns, a coal MC intelligent measurement system is designed in this study that integrates microwave spectrum analysis and the distance-weighted k-nearest neighbor (DW-kNN) algorithm to realize rapid and non-destructive measurement of coal MC. Specifically, the measurement system is built using portable microwave analysis equipment, which can efficiently collect the microwave signals of coal. To improve the cleanliness of modeling data, an iterative clipping method based on Mahalanobis distance (MD-ICM) is used to detect and eliminate outliers. Based on multiple microwave frequency bands, various machine learning methods are evaluated, and it is found that coal MC measurement using broad frequency signals of 8.05–12.01 GHz yields the best results. Experiments are also carried out on coals from different regions to examine the regional robustness of the proposed method. The results of on-site testing with 27 additional samples show that the method based on the combination of microwave spectrum analysis and DW-kNN has a potential application prospect in the rapid measurement of coal MC. [ABSTRACT FROM AUTHOR]

Smart factories and big data are important factors in the Fourth Industrial Revolution. Smart factories aim for automation and integration; however, the most important part is the application of data. Despite extensive research on the maintenance and quality management of big data-based production equipment, industrial data gathered for analysis contain more normal data than abnormal data. In addition, a significant amount of energy is expended in the data pre-processing process to analyze the acquired data. Therefore, to maintain production equipment and quality management, data classification technology that allows easy data analysis by classifying abnormal data into normal data is required. In this paper, we propose an abnormal data classification architecture for cycle data sets gathered from production facilities through SSA-CAE along with data storage methods for each product unit. SSA-CAE is a hybrid technique that combines singular spectrum analysis (SSA) techniques that are effective in reducing noise in time series data with convolutional auto encoder (CAE) that have performed well in time series. [ABSTRACT FROM AUTHOR]

A variety of modulation strategies for suppressing output common-mode voltage (CMV) of indirect matrix converters (IMC) have been proposed, but most of them mainly reduce the peak of CMV by 42.3%. The frequency-domain characteristics of CMV have not been deeply analyzed. In order to improve the theory of frequency-domain characteristics of output common-mode voltage of IMC, this paper proposed a common-mode frequency domain analysis of five common-mode voltage peak suppression modulation methods for IMC. The common-mode voltage spectrum corresponding to the five modulation methods is obtained by the triple Fourier series, and the variation laws of the output common-mode components of the five modulation methods under different modulation indexes are compared and analyzed. By comparing and analyzing the low-frequency amplitude characteristics and high-frequency amplitude characteristics of five modulation methods, the suppression performance of the five modulation methods is evaluated. Finally, experiments verify the correctness of the theoretical analysis of the frequency domain characteristics of the output common-mode voltage of the indirect matrix converter. [ABSTRACT FROM AUTHOR]

We describe an extension of methods used for the derivation of wave information from compact high frequency radar systems and give examples of observations which are compared to measurements from wave buoys close to the radar coverage area. Previous methods were based on the application of the Pierson–Moskowitz wave energy model in the analysis of radar spectra. We describe the extension of the methods to apply a bimodal ocean wave spectral model which includes two different spectra covering different wave frequencies, e.g., from swell and wind-waves. Results are presented from data sets obtained from radar stations located in the USA and Portugal. [ABSTRACT FROM AUTHOR]

Singular spectrum analysis (SSA) is a method of time series analysis and is used in various fields, including medicine. A tremorogram is a biological signal that allows evaluation of a person's neuromotor reactions in order to infer the state of the motor parts of the central nervous system (CNS). A tremorogram has a complex structure, and its analysis requires the use of advanced methods of signal processing and intelligent analysis. The paper's novelty lies in the application of the SSA method to extract diagnostically significant features from tremorograms with subsequent evaluation of the state of the motor parts of the CNS. The article presents the application of a method of singular spectrum decomposition, comparison of known variants of classification, and grouping of principal components for determining the components of the tremorogram corresponding to the trend, periodic components, and noise. After analyzing the results of the SSA of tremorograms, we proposed a new algorithm of grouping based on the analysis of singular values of the trajectory matrix. An example of applying the SSA method to the analysis of tremorograms is shown. Comparison of known clustering methods and the proposed algorithm showed that there is a reasonable correspondence between the proposed algorithm and the traditional methods of classification and pairing in the set of periodic components. [ABSTRACT FROM AUTHOR]

In a batch reactor, the EF advanced oxidation decolorization of aqueous solutions of methyl orange MO, a commercial azo reactive textile dye, was investigated in the presence of two different electrodes. The evaluation included various operational variables such as the IC current intensity (60 mA, 80 mA, and 100 mA), initial concentration of pollutant MO (20 mg/L, 40 mg/L, and 60 mg/L), initial pH of solution (3, 5, and 7), temperature of solution (20 °C, 30 °C, and 50 °C), and initial concentration of catalyst [Fe2+] (0.1 mM, 0.2 mM, and 0.3 mM) on the discoloration rate. A Box-Behnken Design of Experiment (BBD) was used to optimize the parameters that directly affect the Electro-Fenton (EF) process. Under the optimal experimental conditions such as [Fe2+] = 0.232 mM, pH = 3, IC = 80 mA, [MO] = 60 mg/L, and T = 30 ± 0.1 °C, the maximum discoloration rate achieved was 94.9%. The discoloration of the aqueous MO solution during the treatment time was confirmed by analysis of the UV-visible spectrum. After a review of the literature on organic pollutant degradation, the EF system provided here is shown to be one of the best in terms of discoloration rate when compared to other AOPs. [ABSTRACT FROM AUTHOR]

Spectral analysis is successfully adopted in several fields. However, the requirements and the constraints of the different cases may be so varied that not only the tuning of the analysis parameters but also the choice of the most suitable technique can be a difficult task. For this reason, it is important that a designer of a measurement system for spectral analysis has knowledge about the behaviour of the different techniques with respect to the operating conditions. The case that will be considered is the realization of a numerical instrument for the real-time measurement of the spectral characteristics of a multi-tone signal (amplitude, frequency, and phase). For this purpose, different signal processing techniques can be used, that can be classified as parametric or non-parametric methods. The first class includes those methods that exploit the a priori knowledge about signal parameters, such as the spectral shape of the signal to be processed. Thus, a self-configuring procedure based on a parametric algorithm should include a preliminary evaluation of the number of components. The choice of the right method among several proposals in the literature is fundamental for any designer and, in particular, for the developers of spectral analysis software, for real-time applications and embedded devices where time and reliability constrains are arduous to fulfil. Different aspects should be considered: the desired level of accuracy, the available elaboration resources (memory depth and processing speed), and the signal parameters. The present paper details a comparison of some of the most effective methods available in the literature for the spectral analysis of signals (IFFT-2p, IFFT-3p, and IFFTc, all based on the use of an FFT algorithm, while improving the spectral resolution of the DFT with interpolation techniques and three parametric algorithms—MUSIC, ESPRIT, and IWPA). The methods considered for the comparison will be briefly described, and references to literature will be given for each one of them. Then, their behaviour will be analysed in terms of systematic contribution and uncertainty on the evaluated frequencies of the spectral tones of signals created from superimposed sinusoids and white Gaussian noise. [ABSTRACT FROM AUTHOR]

Bed shear stress is an important measure of benthic habitats since it is related to many ecological processes. In this study, we focused on the fluctuating characteristics of shear stress in rough-bed open-channel flows. The roughness element method was adopted to mimic natural rough beds and the Improved Delayed Detached Eddy Simulation (IDDES) model was used to obtain comprehensive information about shear stress near the rough bed. Three arrangement patterns of the roughness elements were simulated to compare their effects on flow structure and shear stresses. The arrangements of the roughness elements altered the Reynold stress and turbulent kinetic energy characteristics, due to the variance of blockage in lateral directions that led to flow detachment and changes in the flow directions. Quadrant analysis revealed the spatial variations of the instantaneous shear stress burst events at different locations in the wake. By using spectrum analysis, the accumulation of shear-stress energy from small to large vortex scales was estimated, which revealed that the instantaneous effect of the shear stress was significantly stronger than the effect of the time-averaged shear stress, especially on small scales. The results of this study suggest the significance of the fluctuation part of shear stress in further studies on ecological processes. [ABSTRACT FROM AUTHOR]

In this study, a multi-station and multi-instrument system, organized and proposed for ionospheric scintillation and equatorial spread-F (ESF) specification and their associated motions in the Taiwan–Philippines sector, is outlined. The issues related to the scintillation and ESF event observed on 26 October 2021, at magnetic quiet conditions are presented and discussed. We first indicate the existence of a plasma bubble in the Taiwan–Philippines sector by using the FormoSat-7/Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (FS7/COSMIC2) GPS/GLONASS radio occultation observations. We verify the latitudinal extent of the tracked plasma bubble using the recorded ionograms from the Vertical Incidence Pulsed Ionospheric Radar located at Hualien, Taiwan. We further discuss the spatial and temporal variabilities of two-dimensional vertical scintillation index VS4 maps based on the simultaneous GPS L1-band signal measurements from 133 ground-based receivers located in Taiwan and the surrounding islands. We also operate two high-sampling, software-defined GPS receivers and characterize the targeted plasma irregularities by carrying out spectrum analyses of the received signal. As a result, the derived plasma irregularities moved eastward and northward. Furthermore, the smaller the irregularity scale, the higher the spectral index and the stronger the scintillation intensity were at lower latitudes on the aimed irregularity feature. [ABSTRACT FROM AUTHOR]

The Qiongdongnan (QDN) basin in the northwestern South China Sea has been shown to be rich in petroleum resources and has significant exploration potential for deepwater oil and gas resources. Therefore, it is of great significance to clarify the gas accumulation process in the deepwater area of the QDN basin, specifically the Y8 area. In this study, fluid inclusion analysis, including the identification and localization of fluid inclusions under a microscope, laser Raman spectrum analysis and homogenization temperature (Th) measurement, reconstruction of the thermal evolution burial history, geochemical analysis, and typical seismic section analysis were comprehensively used to interpret the gas accumulation process of the Y8 area. The laser Raman spectrum analysis results of fluid inclusions verified the existence of methane and confirmed the hydrocarbon charging event in this area. However, the Th of fluid inclusions in the reservoir, the mixed compositions of hydrothermal compositions (H2S + SO2) and hydrocarbons (methane) in the fluid inclusions, and the low Tmax values of some wells in the Y8 area comprehensively confirmed that the coincidence of hydrothermal activity with the accumulation process affected the long-distance gas accumulation of the Y8 area. The hydrothermal activity was also confirmed by the presence of fluid diapirs in seismic profiles of the Y8 area. Furthermore, the hydrocarbon accumulation process was reconstructed using the modified thermal evolution history considering the effect of hydrothermal activity. Overall, this study attributed the high Th of fluid inclusions in the reservoirs of the Y8 area to hydrothermal activity and proposed a long-distance migration model of hydrocarbon accumulation coinciding with hydrothermal activity, both of which are beneficial to understanding the accumulation process of the Y8 area. [ABSTRACT FROM AUTHOR]

The technological mineralogical characteristics of cesium-containing minerals in tailings were examined by means of chemical analysis, the energy spectrum analysis method, and MLA (mineral liberation analyzer) to determine the element content, phase analysis, associated mineral components, degree of liberation, particle size, etc. The results showed that the samples mainly contained spodumene, quartz, feldspar, mica, and other minerals. Pollucite was the main cesium-containing mineral in the sample, which had a cesium oxide content that was as high as 34.58%. The mineral content of pollucite in the sample was relatively low—only 1.23%. The pollucite monomer content and the amount of rich intergrowth was 85.25%, and the metal distribution of cesium in the +0.074 mm sample was as high as 87.06%. Spodumene was the main mineral associated with pollucite. The beneficiation evaluation of this tailing sample was conducted using a combined process that integrated desliming, magnetic separation, and froth flotation, and a pollucite concentrate containing 4.45% Cs2O was obtained with a 63.71 recovery rate. This indicates that little pollucite was removed by means of desliming and magnetic separation before froth flotation recovery, but during the froth flotation stage in spodumene and feldspar, a large pollucite loss was observed. Therefore, to improve pollucite recovery, a pollucite-specific adsorption reagent should be synthesized. [ABSTRACT FROM AUTHOR]

For the first time in the sixty years since the synthesis of stishovite, we report unambiguous evidence of stishovite formed in the deep Earth. A minimum pressure of about 7.5 GPa at 1000 °C is necessary for the formation of stishovite, corresponding to a depth of about 230 km. In this manuscript we report the identification of stishovite along with coesite as inclusions in mineral grains from the Waldheim granulite. This implies that the stishovite was transported upwards, probably very rapidly to a depth of about 130 km, corresponding to the highest pressure indicated by newly identified coesite in the prismatine of the Waldheim granulite, and continuing up to the depth of emplacement of the Waldheim prismatine granulite. The analysis of the Raman spectra obtained from a metastable trapped stishovite micro-crystal show that all the diagnostic Raman bands are present. However, given the metastability of the stishovite at room temperatures and pressures, this mineral breaks down step-by-step into stable polymorphs, first coesite and then quartz and cristobalite, during the Raman stimulation. The rare coesite crystals in prismatine have also resulted from the irreversible transformation from stishovite. Although the Waldheim occurrence may be unique, we suggest that Raman analysis of co-trapped crystals in similar deep-seated rocks, an area of limited previous research, may prove an important innovation in the study of mantle processes. [ABSTRACT FROM AUTHOR]

Due to their excellent seismic behavior, shear wall-type concrete buildings are very popular in earthquake-prone countries like Chile. According to current seismic regulations, the performance of such structures can be indifferently assessed through linear or non-linear methods of analysis. Although all the code-compliant approaches supposedly lead to a safe design, linear approaches may be in fact less precise for catching the actual seismic performance of ductile and dissipative structures, which can even result in unconservative design where comparatively stiff buildings like reinforced-concrete shear-wall (RC-SW) buildings are concerned. By referring to a mid-rise multistory RC-SW building built in Chile and designed according to the current seismic Chilean code, the paper investigates the effectiveness of the linear dynamic analyses to predict the seismic performance of such kind of structures. The findings show that the code-compliant linear approaches (Modal Response Spectrum Analysis and Linear Time-History Analysis) may significantly underestimate the displacement demand in RC-SW buildings. This is highlighted by the comparison with the results obtained from the Non-Linear Time-History Analysis, which is expected to give more realistic results. A set of ten spectrum-consistent Chilean earthquakes was considered to carry out the time-history analyses while a distributed-plasticity fiber-based approach was adopted to model the non-linear behavior of the considered building. The paper highlights how the risk of an unsafe design may become higher when reference is made to the Chilean code, the latter considering only the Modal Response Spectrum Analysis (MRSA) without even providing corrective factors to estimate the inelastic displacement demand. The paper checks the effectiveness of some amplifying factors taken from the literature with reference to the case-study shear-wall building, concluding that they are not effective enough. The paper also warns against the danger of local soft-story collapse mechanisms, which are typical of reinforced concrete frames but may also affect RC-SW buildings when weaker structural parts made by column-like walls are present at the ground floor. [ABSTRACT FROM AUTHOR]

The relationship between significant wave height ( H 1 / 3 ) and period ( T 1 / 3 ) was obtained using wave data from the East and Yellow coasts of the Korean Peninsula to facilitate the calculations of the wave parameters. In addition, the JONSWAP spectral parameters were estimated and analyzed for all wave height ranges. The relational expression between the two wave variables ( H 1 / 3 ~ T 1 / 3 ) obtained from this study showed a significant difference from the previously proposed relational expressions, most of which tended to follow the lower limit of the data. Meanwhile, the suggested peak enhancement factor (PEF,   γ ) is 1–7; however, for this study, a peak control factor (PCF,   γ c ) with a range of 0–10 was introduced. As a result of the analysis, the PCF was determined to be 1.13–1.42, which is approximately 40% smaller than the previously proposed γ   =   3.3 . The probability density distribution of the appropriate PCF was then calculated, and the gamma and log-normal distributions for the East and Yellow coasts of the Korean Peninsula were found, respectively. This study covered waves of all range heights, and the analysis results can be used as important data to explain the characteristics of the sea area. [ABSTRACT FROM AUTHOR]

Among the smart factory studies, we describe defect detection research conducted on bearings, which are elements of mechanical facilities. Bearing research has been consistently conducted in the past; however, most of the research has been limited to using existing artificial intelligence models. In addition, previous studies assumed the factories situated in the bearing defect research were insufficient. Therefore, a recent research was conducted that applied an artificial intelligence model and the factory environment. The transformer model was selected as state-of-the-art (SOTA) and was also applied to bearing research. Then, an experiment was conducted with Gaussian noise applied to assume a factory situation. The swish-LSTM transformer (Sl transformer) framework was constructed by redesigning the internal structure of the transformer using the swish activation function and long short-term memory (LSTM). Then, the data in noise were removed and reconstructed using the singular spectrum analysis (SSA) preprocessing method. Based on the SSA-Sl transformer framework, an experiment was performed by adding Gaussian noise to the Case Western Reserve University (CWRU) dataset. In the case of no noise, the Sl transformer showed more than 95% performance, and when noise was inserted, the SSA-Sl transformer showed better performance than the comparative artificial intelligence models. [ABSTRACT FROM AUTHOR]

A copper helical coil antenna was developed, characterized, and optimized for 2.45 GHz operations supplied by a microwave semiconductor oscillator. The application field of interest is laser-induced breakdown spectroscopy enhanced by microwave. Simulations using the Ansys HFSS demonstrate the superior localized E-field strength of the helical coil antenna, compared with other antenna-type structures. Simulation results show that E-field strength at the tip of the antenna has a logarithmic trend for increasing the coil pitch. The optimum pitch is 5 mm for a coil diameter of 6.5 mm upon consideration of the system compactness. Despite the antenna's open-circuit end, the presence of target samples does not interfere with the E-field and H-field distribution of the antenna and the surrounding environment. Applications in microwave-enhanced laser-induced breakdown spectroscopy (MWLIBS) confirm the importance of the antenna reflector. The electric field strength was over 100 times higher than the previous capacitor-like antenna. The antenna configuration angle was then experimentally optimized for maximum enhancement effects in the spectrochemical analysis of Al2O3. The antenna angle of 60° from the laser beam propagation achieved maximum enhancement in the emission signal of Al I. [ABSTRACT FROM AUTHOR]

Simple Summary: Hepatocellular carcinoma is the most common primary liver malignancy in the United States. Macrophages are immune cells that play a critical role in the promotion of cancer growth and configuration of the hepatic microenvironment. Studying intrahepatic macrophages is challenging because they are difficult to isolate, they transform their phenotype upon manipulation, and in vivo animal models poorly replicate the liver microenvironment. Understanding the complexity of intrahepatic macrophage populations is crucial because they coordinate antitumoral immunity. Application of novel methods that can detect immune cell phenotypes, along with their spatial co-localization in situ is critical and timely. The role of tumor-associated macrophages (TAMs) in the pathogenesis of hepatocellular carcinoma (HCC) is poorly understood. Most studies rely on platforms that remove intrahepatic macrophages from the microenvironment prior to evaluation. Cell isolation causes activation and phenotypic changes that may not represent their actual biology and function in situ. State-of-the-art methods provides new strategies to study TAMs without losing the context of tissue architecture and spatial relationship with neighboring cells. These technologies, such as multispectral imaging (e.g., Vectra Polaris), mass cytometry by time-of-flight (e.g., Fluidigm CyTOF), cycling of fluorochromes (e.g., Akoya Biosciences CODEX/PhenoCycler-Fusion, Bruker Canopy, Lunaphore Comet, and CyCIF) and digital spatial profiling or transcriptomics (e.g., GeoMx or Visium, Vizgen Merscope) are being utilized to accurately assess the complex cellular network within the tissue microenvironment. In cancer research, these platforms enable characterization of immune cell phenotypes and expression of potential therapeutic targets, such as PDL-1 and CTLA-4. Newer spatial profiling platforms allow for detection of numerous protein targets, in combination with whole transcriptome analysis, in a single liver biopsy tissue section. Macrophages can also be specifically targeted and analyzed, enabling quantification of both protein and gene expression within specific cell phenotypes, including TAMs. This review describes the workflow of each platform, summarizes recent research using these approaches, and explains the advantages and limitations of each. [ABSTRACT FROM AUTHOR]

Conventional experimental modal analysis uses excitation and response information to estimate the frequency response function. However, many engineering structures face excitation signals that are difficult to measure, so output-only modal estimation is an important issue. In this paper, singular spectrum analysis is employed to construct a Hankel matrix of appropriate dimensions based on the measured response data, and the observability of the system state space model is used to treat the Hankel matrix as three components containing system characteristics, excitation and noise. Singular value decomposition is used to factorize the data matrix and use the characteristics of the left and right singular matrices to reduce the dimension of the data matrix to improve calculation efficiency. Furthermore, the singular spectrum is employed to estimate the minimum order to reconstruct the Hankel matrix; then, the excitation and noise components can be removed, and the system observability matrix can be obtained. By appropriately a factorizing system observability matrix, we obtain the system matrix to estimate the modal parameters. In addition, the fictitious modes produced by increasing the order of the matrix can be eliminated through the stabilization diagram. [ABSTRACT FROM AUTHOR]

We used high-resolution rotational spectroscopy coupled to a laser ablation source to study the conformational panorama of perillartine, a solid synthetic sweetener. Four conformers were identified under the isolation conditions of the supersonic expansion, showing that all of them present an E configuration of the C=N group with respect to the double bond of the ring. The observed structures were verified against Shallenberger–Acree–Kier's sweetness theory to shed light on the structure–sweetness relationship for this particular oxime, highlighting a deluge of possibilities to bind the receptor. [ABSTRACT FROM AUTHOR]

Simple Summary: Survival of ovarian cancer patients largely relies on the surgical removal of all cancer cells. To achieve this, good vision is crucial. In this study, we evaluate the ability of hyperspectral imaging to detect ovarian cancer. Images of surgically removed tissue samples of 11 patients were taken and compared to histopathology in order to train machine learning software. For training purposes, only healthy tissues and tissues with high tumor cell content (>50%) were included. In total, 26 tissue samples and 26,446 data points of 10 patients were included. Tissue classification as either tumorous or healthy was evaluated by leave-one-out cross-validation. This resulted in a power of 0.83, a sensitivity of 0.81, a specificity of 0.70 and a Matthew's correlation coefficient of 0.41. To conclude, this study shows that hyperspectral imaging can be used to recognize ovarian cancer. In the future, the technique may enable real-time image guidance during surgery. The most important prognostic factor for the survival of advanced-stage epithelial ovarian cancer (EOC) is the completeness of cytoreductive surgery (CRS). Therefore, an intraoperative technique to detect microscopic tumors would be of great value. The aim of this pilot study is to assess the feasibility of near-infrared hyperspectral imaging (HSI) for EOC detection in ex vivo tissue samples. Images were collected during CRS in 11 patients in the wavelength range of 665–975 nm, and processed by calibration, normalization, and noise filtering. A linear support vector machine (SVM) was employed to classify healthy and tumorous tissue (defined as >50% tumor cells). Classifier performance was evaluated using leave-one-out cross-validation. Images of 26 tissue samples from 10 patients were included, containing 26,446 data points that were matched to histopathology. Tumorous tissue could be classified with an area under the curve of 0.83, a sensitivity of 0.81, a specificity of 0.70, and Matthew's correlation coefficient of 0.41. This study paves the way to in vivo and intraoperative use of HSI during CRS. Hyperspectral imaging can scan a whole tissue surface in a fast and non-contact way. Our pilot study demonstrates that HSI and SVM learning can be used to discriminate EOC from surrounding tissue. [ABSTRACT FROM AUTHOR]

In this work, a general method for the design of concentric braced steel frames (CBF) with active tension diagonal bracings, applicable to single- and multi-storey structures, is presented. The method is based on the use of an elastic modal analysis with a response spectrum, which is carried out using an appropriate modified elastic stiffness of diagonal bracings. The reliability of the proposed method is validated through the analysis of significant case studies, making a series of numerical comparisons carrying out time-history non-linear dynamic analysis. [ABSTRACT FROM AUTHOR]

Each olefin (ethylene, trans-1,3-butadiene, isoprene, dimethyl butadiene (DMB)) and ozone molecules were codeposited on a CsI window at cryogenic temperature, and the products of photolysis with ultraviolet-visible light were observed using Fourier-transform infrared spectroscopy. The products of the C2H4-O3 system could be assigned to glyoxal (CHO-CHO), ethylene oxide (c-C2H4O), CO, and CO2. The formation of CHO-CHO and c-C2H4 and the absence of H2CO and HCOOH indicated that the main reaction channels did not involve C-C bond breaking. Based on this simple scheme, the photoproducts of different olefin-O3 systems were assigned, and the vibrational features predicted by density functional theory calculations were compared with the observed spectra. Regarding butadiene, spectral matches between the observations and calculations seemed reasonable, while assignments for isoprene ambiguities of and DMB remain, mainly because of the limited availability of authentic sample spectra. [ABSTRACT FROM AUTHOR]

The description of the inhomogeneity of the cosmic ray spectrum in the region of 10 TV, which is observed in experimental data, in terms of isotropic diffusion from a single close source is considered. It is shown that such a description is possible, and the area of possible localization of the source in space and time and its energy are found. The method of penalty functions is used to account for the data on the spectrum of all particles. [ABSTRACT FROM AUTHOR]

In this paper, carbon thin films were grown using the plasma-enhanced atomic layer deposition (PE-ALD). Methane (CH4) was used as the carbon precursor to grow the carbon thin film. The grown film was analyzed by the high-resolution transmission electron micrograph (TEM), X-ray photoelectron spectroscopy (XPS) analysis, and Raman spectrum analysis. The analyses show that the PE-ALD-grown carbon film has an amorphous structure. It was found that the existence of defective sites (nanoscale holes or cracks) on the substrate of copper foil could facilitate the formation of nanolayered carbon films. The mechanism for the formation of nanolayered carbon film in the nanoscale holes was discussed. This finding could be used for the controlled growth of nanolayered carbon films or other two-dimensional nanomaterials while combining with modern nanopatterning techniques. [ABSTRACT FROM AUTHOR]

Downward continuation is an effective technique that can be used to transform the magnetic data measured on one surface to the data that would be measured on another arbitrary lower surface. However, it suffers from amplitude attenuation and is susceptible to noise, especially when the continuation distance is large. To solve these problems, we present a stable and high-precision downward continuation method combining the ideas of equivalent source technique, Tikhonov regularization, radial logarithmic power spectrum analysis, and constrained strategy. To implement this method, the observed data is used to construct the equivalent source in the study area, and the small amount of measured magnetic data at the lower surface (relative to the original observation surface) is employed to constrain the calculation procedure simultaneously. Then the magnetic data at the target surface can be obtained by using a forward calculation procedure instead of the risky downward continuation procedure. The proposed method is tested on both synthetic model data and real magnetic data collected in the South China sea. Various obtained results demonstrate that the method reported in this study has higher accuracy and better noise resistance than the traditional downward continuation methods. [ABSTRACT FROM AUTHOR]

In the processing of remotely sensed data, classification may be preceded by feature extraction, which helps in making the most informative parts of the data emerge. Effective feature extraction may boost the efficiency and accuracy of the following classification, and hence various methods have been proposed to perform it. Recently, Singular Spectrum Analysis (SSA) and its 2-D variation (2D-SSA) have emerged as popular, cutting-edge technologies for effective feature extraction in Hyperspectral Images (HSI). Using 2D-SSA, each band image of an HSI is initially decomposed into various components, and then the image is reconstructed using the most significant eigen-tuples relative to their eigen-values, which represent strong spatial features for the classification task. However, instead of performing reconstruction on the whole image, it may be more effective to apply reconstruction to object-specific spatial regions, which is the proposed objective of this research. As an HSI may cover a large area, multiple objects are generally present within a single scene. Hence, spatial information can be highlighted accurately by specializing the reconstruction based on the local context. The local context may be defined by the so-called superpixels, i.e., finite sets of pixels that constitute a homogeneous set. Each superpixel may undergo tailored reconstruction, with a process expected to perform better than non-spatially-adaptive approaches. In this paper, a Superpixel-based SSA (SP-SSA) method is proposed where the image is first segmented into multiple regions using a superpixel segmentation approach. Next, each segment is individually reconstructed using 2D-SSA. In doing so, the spatial contextual information is preserved, leading to better classifier performance. The performance of the reconstructed features is evaluated using an SVM classifier. Experiments on four popular benchmark datasets reveal that, in terms of the classification accuracy, the proposed approach overperforms the standard SSA technique and various common spatio-spectral classification methods. [ABSTRACT FROM AUTHOR]

This paper presents a catalogue of gamma-ray bursts (GRBs) that were detected by the instruments onboard the Lomonosov space observatory. The Lomonosov mission gave the first experience of not only multi-wavelength (from optical to gamma) observations of GRBs but also multi-messenger observations of extreme phenomena and GRBs. The detailed light curves and energy spectra of the detected GRBs are presented. The results of the prompt, early an afterglow optical observations of several GRBs are discussed. [ABSTRACT FROM AUTHOR]

The threshing mechanism is the main component of the combine harvester on which the grain separation and cleaning qualitative work indicators depend. It is important to ensure that all threshing mechanism components, including the threshing drum bearings and all other bearings of the combine, are working properly and reliably. There are many places in the combine where it is not possible to measure bearing vibrations directly without dismounting them, since there is no suitable spot to mount a sensor. The paper investigates the threshing drum rolling bearing condition of combines, which are difficult to access, by using a vibration diagnostics technique utilizing a newly manufactured steel bracket. The vibration measurements and analysis were conducted by the Adash A4900 Vibrio M analyzer (Adash spol. s.r.o., Ostrava, Czech Republic). The vibration source measurement was based on the fast Fourier transform (FFT) spectrum analysis. Analysis of the experimental results showed that average squared velocity values (in the frequency interval of 10–1000 Hz), together with other measured vibration parameters, can be used for the combine threshing drum's bearing condition evaluation. [ABSTRACT FROM AUTHOR]

Improving the efficiency and longevity of energy storage systems based on Li- and Na-ion rechargeable batteries presents a major challenge. The main problems are essentially capacity loss and limited cyclability. These effects are due to a hierarchy of factors spanning various length and time scales, interconnected in a complex manner. As a consequence, and in spite of several decades of research, a proper understanding of the ageing process has remained somewhat elusive. In recent years, however, combinations of advanced spectroscopy techniques and first-principles simulations have been applied with success to tackle this problem. In this Special Issue, we are pleased to present a selection of articles that, by precisely applying these methods, unravel key aspects of the reduction--oxidation reaction and intercalation processes. Furthermore, the approaches presented provide improvements to standard diagnostic and characterisation techniques, enabling the detection of possible Li-ion flow bottlenecks causing the degradation of capacity and cyclability. [ABSTRACT FROM AUTHOR]

With the aim of determining the best input geometry for DFT calculations of [60]PCBM, the geometry of 24 chemically possible [60]PCBM conformers were optimised and their electronic energies and average bond strains were determined. A DFT analysis of the relevant dihedral angles provided insights into the dynamical behaviour of the ester group through sterically restricted bond rotations. In addition, the 13C NMR spectra of the six better performing conformers were simulated and compared with an experiment. There is a close correlation between average bond strain, total electronic energy and mean absolute error of the simulated 13C NMR spectra of the ester carbons. The best overall candidate conformer for the input geometry had the C61-C4, C4-C3 and C3-C2 single bonds of the alkyl chain in syn, anti and anti arrangements, respectively, and had the C2-C1 and C1-O single bonds of the ester in syn and anti arrangements, respectively. This contrasts strikingly with most representations of PCBM in the literature, which depict all relevant bonds in anti arrangements. [ABSTRACT FROM AUTHOR]

The surface chemistry of carbon materials is predominantly explored using x-ray photoelectron spectroscopy (XPS). However, many published papers have critical failures in the published analysis, stemming from an ill-informed approach to analyzing the spectroscopic data. Herein, a discussion on lineshapes and changes in the spectral envelope of predominantly graphitic materials are explored, together with the use of the D-parameter, to ascertain graphitic content, using this information to highlight a simple and logical approach to strengthen confidence in the functionalization derived from the carbon core-level spectra. [ABSTRACT FROM AUTHOR]

Audio carriers are subject to a fast and irreversible decay. In order to save valuable historical recordings, the audio signal and other relevant information can be extracted from the source audio document and stored on another medium, normally a redundant digital storage system. This procedure is called 'content transfer'. It is a costly and time-consuming procedure. There are several solutions with which the cost can be reduced. One consists of picking up all tracks from a two-sided tape in one pass. This means that some tracks will be digitized forward and some backwards, to be subsequently corrected in the digital workstation. This article is concerned with the question of whether reading tracks backwards introduces unwanted effects into the signal. In particular, it investigates whether a difference can be observed between audio signals read forward or backwards and, if so, whether the difference is measurable. The results show that a difference can be observed, yet this is not enough to conclude that this "backwards" approach should not be used. The complexity of the situation is presented in the discussion. Future work includes reproducing this experiment with different audio equipment, as well as a perception test with human subjects. [ABSTRACT FROM AUTHOR]

In this study, a method for detecting the railway surface defects called "squats" using the ABA (Axle Box Acceleration) measurement of trains was proposed. ABA prototype design, implementation, and field tests were conducted to derive and verify the results. The field test was performed using a proven precision measurement system, and the measured data were signal-processed using a Matlab program. The algorithm used to determine the position of the squats was developed based on wavelet spectrum analysis. This study was verified for a section of a domestic general line and, following field verification for the section, squats was detected with a hit rate of about 88.2%. The main locations where the squats occurred were the rail welds and the joint section, and it was confirmed that in some sections, unsupported sleepers occurred at the locations where the squats occurred. [ABSTRACT FROM AUTHOR]

Featured Application: Control of certain non-proportionality indices can be used to limit response errors when classical modal analysis is applied to non-proportionally damped structures. Use of modal procedures in systems with non-proportional damping (such as structures with added viscous damping systems) results in response errors, shown in this study to depend on dissimilar and often conflicting conditions for different variables and stories; thus, it is not possible to propose simple rules based on structural or damping properties to limit the error in a global way. However, four existing indices (originally proposed to measure damping non-proportionality) present a positive correlation with the extreme errors in modal procedures for all variables and stories. Thus, limiting the index value is a sufficient condition to keep the error in all variables within a given threshold. For practical application, limit values for these indices are tabulated as a function of error and can be used as an acceptance criterion for the validity of modal procedures. [ABSTRACT FROM AUTHOR]