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New strategies for converting signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Traditional approaches to optical-to-microwave transduction typically perturb or destroy the information encoded on intensity of the light field, eliminating the possibility for further processing or distribution of these signals. In this paper, we introduce an optical-to-microwave conversion method that allows for both detection and spectral analysis of microwave photonic signals without degradation of their information content. This functionality is demonstrated using an optomechanical waveguide integrated with a piezoelectric transducer. Efficient electromechanical and optomechanical coupling within this system permits bidirectional optical-to-microwave conversion with a quantum efficiency of up to −54.16 dB. Leveraging the preservation of the optical field envelope in intramodal Brillouin scattering, we demonstrate a multi-channel microwave photonic filter by transmitting an optical signal through a series of electro-optomechanical waveguide segments, each with distinct resonance frequencies. Such electro-optomechanical systems could offer flexible strategies for remote sensing, channelization, and spectrum analysis in microwave photonics. The authors showcase an optical-to-microwave conversion method using an optomechanical waveguide integrated with a piezoelectric transducer. The presented system allows bidirectional optical-to-microwave conversion with a quantum efficiency of up to—54.16 dB. [ABSTRACT FROM AUTHOR]

Wireless medical telemetry systems (WMTSs) are typical radio communication–based medical devices that monitor various biological parameters, such as electrocardiograms and respiration rates. In Japan, the assigned frequency band for WMTSs is 400 MHz. However, the issues accounting for poor reception in WMTS constitute major concerns. In this study, we analyzed the effects of electromagnetic interferences (EMIs) caused by other radio communication systems, the intermodulation (IM) effect, and noises generated from electrical devices on WMTS and discussed their management. The 400-MHz frequency band is also shared by other radio communication systems. We showed the instantaneous and impulsive voltages generated from the location-detection system for wandering patients and their potential to exhibit EMI effects on WMTS. Further, we presented the IM effect significantly reduces reception in WMTS. Additionally, the electromagnetic noises generated from electrical devices, such as light-emitting diode lamps and security cameras, can exceed the 400 MHz frequency band as these devices employ the switched-mode power supply and/or central processing unit and radiate wideband emissions. Moreover, we proposed and evaluated simple and facile methods using a simplified spectrum analysis function installed in the WMTS receiver and software-defined radio for evaluating the electromagnetic environment. [ABSTRACT FROM AUTHOR]

A Fourier-transform recording of protactinium in the infrared range is reanalysed with high precision in order to determine the hyperfine interaction constants A and B. Starting with a selection of best lines and least-squares fits of hyperfine structure intervals, large systems of linear equations compare experimental hyperfine peak wavenumbers with a theoretical representation. The theoretical representation is based on Ritz's combination principle and Casimir's formula according to the existing classification. Weighted least-squares fits allow a discrimination between unperturbed and perturbed data such as blended hyperfine structure components. For the first time, the wavenumbers of the hyperfine components of more than 600 lines are fitted using the characteristics of about 250 levels as parameters. When adding adjustable wavenumber-scale correction parameters, global consistency for the whole IR spectrum is obtained with local limits of about 0.3 × 10 - 3 cm - 1 . This demonstrates the high precision in both recording and analysis. The values of the fine structure energies are revised. Standard errors around 0.1 × 10 - 3 cm - 1 for the A constants and 10 - 3 cm - 1 for the B constants and the fine structure energies are achieved. Representative examples illustrate extensive results obtained for atomic protactinium. This high precision facilitates further search for new energy levels, and 20 new levels were presented. Foreword The data presented here are the results of a study carried out at the Laboratoire Aimé Cotton (LAC) at Paris-Orsay in the years 2003 and 2004, when I was there for a research stay. At this time, I worked together with Jean-François Wyart and Annie Ginibre on the re-examination of protactinium spectra that have been measured about 30 years earlier and that were available in the form of a printed list of peak wavenumbers and a printed paper chart of the intensity profile. The spectra had already been analysed, but there was still a lot of additional information that could be extracted from the spectra with time and effort. The review of the data, the selection of the data and the step-by-step optimization of the data set took a lot of time. When I returned to Berlin in 2004, we had made good progress, but in principle, it is like a bottomless pit. We continued together to optimize the data and tried to the finishing touches to it. At some point, we decided that we had reached a 'level of maturity' where the data could be published. We have discussed a lot about how detailed the text should be. This discussion has dragged on over the years and this project has repeatedly been lost in the stream of other everyday tasks. Every now and then there was a small attempt to return to this topic, but it quickly got lost in the daily hustle and bustle. In 2012, we presented the results at a conference. The death of both of them within two years hit me hard. I very much regret that this work was not published earlier. This special volume was the right motivation for me to finally publish this data. I no longer have access neither to the computer programs used at the time, which ran on large computer systems, nor to the original measurement data. I have not been able to find out what happened to the large quantity of paper (printed list of peak wavenumbers anda printed paper chart of spectra). But I have a bunch of input and output files of the calculations that have become a bit jumbled over the years, which contain a lot of information, as well as our unfinished manuscript. The resulting data contain important information for posterity – particularly since the element is radioactive and the experiments to collect laboratory data are unlikely to be repeated any time soon. I think it is worth publishing these data. High precision FT spectra of Pa: analysis of fine and hyperfine structure [ABSTRACT FROM AUTHOR]

Blended acquisition offers significant cost and period reduction in seismic data acquisition. However, fired blended sources are usually deployed at off-the-grid (OffG) samples due to obstacle limitation and economic cost considerations. The irregular distribution of coordinates, along with the blending noise, has a detrimental effect on the performance of subsequent seismic processing and imaging. The interpolated multichannel singular spectrum analysis (I-MSSA) algorithm effectively provides on-the-grid deblended results by employing an interpolator, in conjunction with a projected gradient descent strategy. However, the deblending accuracy and computational efficiency of the I-MSSA are still a concern due to the limitations of the traditional singular value decomposition (SVD). To address these limitations, we propose an interpolated fast damped multichannel singular spectrum analysis (I-FDMSSA) rank-reduction algorithm. The proposed algorithm incorporates the damping operator, the randomized SVD (RSVD) and the fast Fourier transform (FFT) strategy. The damping operator can further attenuate the remaining noise in the estimated signal obtained from the truncated SVD, resulting in an improved deblending performance. The RSVD accelerates the rank-reduction process by shrinking the size of the Hankel matrix. To expedite the rank-reduction and anti-diagonal averaging stages without explicitly constructing large-scale block Hankel matrices, the FFT strategy is employed. By incorporating a 2D separable sinc interpolator, the I-FDMSSA enables an efficient and accurate deblending of 3D OffG blended data. The deblending performance and operational efficiency improvements of the proposed I-FDMSSA algorithm over the traditional I-MSSA algorithm are demonstrated through OffG synthetic and field blended data examples. [ABSTRACT FROM AUTHOR]

Filter elements based on metamaterial structure are one of the essential schemes for researching the miniaturization of spectral detection systems. The aim of this study is to meet the application requirements of different long-wave infrared signal frequency filtering and improve the detection efficiency of micro-filters. In this paper, a periodic micro-nano-cross-linked hole structure is designed, based on the surface plasmonic polariton resonance effect to realize the extraordinary optical transmission performance of 8 ~ 12 μm long-wave infrared. Based on the surface plasmonic polariton excitation mechanism of periodic micro-nano-structures, the tunable performance of the transmission spectra at five central wavelengths of 8, 9, 10, 11, and 12 μm was achieved by changing the simulation period and the overall period of the model, and the optimal peak transmittance was 88.31% with a half-wave width of 1.31 ± 0.01 μm. The present study summarizes the tuning mode and rule of the micro-nano-cross-linked structure to realize the blue/redshift under the performance of the extraordinary optical transmission, which provides an important reference for the miniaturized structure design of infrared spectral detectors and tunable filtering research and is conducive to the application of broadband filtering spectral chips. [ABSTRACT FROM AUTHOR]

Novel zeolitic imidazolate frameworks (ZIFs), classical subtypes of metal organic frameworks (MOFs), and nanostructures are electro-engineered onto carbon fiber (CF), leading to a unique freestanding electrochemical platform of budlike nano Zn-ZIFs decorated CF (BN-Zn-ZIFs/CF). The unique morphology, structure, and composition are characterized by electron microscopy and energy spectrum analysis. Notably, the BN-Zn-ZIFs/CF platform displays superb electrocatalysis towards the oxidation of isoeugenol with encouragingly low overpotential and high current response. The strong electrocatalytic oxidation capability of BN-Zn-ZIFs/CF makes it an excellent sensing platform for isoeugenol detection. BN-Zn-ZIFs/CF sensor exhibits high-performance isoeugenol sensing with an extremely low limit of detection (13 nM) and wide detection range (0.1–700 µM). Besides, the BN-Zn-ZIFs/CF sensor can greatly resist interference from common ions, major biomolecules, and some amino acids. Moreover, excellent reliability, stability, and practicality are obtained. Our work demonstrates that the as-prepared BN-Zn-ZIFs/CF can act as an high-performance electrochemical sensor for the isoeugenol detection, the well-developed ZIF nanocrystal-modified conductive substrates can be a unique platform for the efficient sensing of other molecules, and the electrochemical engineering strategy can be an effective method for the growing of fresh MOF nanocrystals at conductive substrates in various electrochemical applications. [ABSTRACT FROM AUTHOR]

In recent years, the authors have extended the traditional interval method into the time dimension to develop a new mathematical tool called the "interval process model" for quantifying time-varying or dynamic uncertainties. This model employs upper and lower bounds instead of precise probability distributions to quantify uncertainty in a parameter at any given time point. It is anticipated to complement the conventional stochastic process model in the coming years owing to its relatively low dependence on experimental samples and ease of understanding for engineers. Building on our previous work, this paper proposes a spectrum analysis method to describe the frequency domain characteristics of an interval process, further strengthening the theoretical foundation of the interval process model and enhancing its applicability for complex engineering problems. In this approach, we first define the zero midpoint function interval process and its auto/cross-power spectral density (PSD) functions. We also deduce the relationship between the auto-PSD function and the auto-covariance function of the stationary zero midpoint function interval process. Next, the auto/cross-PSD function matrices of a general interval process are defined, followed by the introduction of the concepts of PSD function matrix and cross-PSD function matrix for interval process vectors. The spectrum analysis method is then applied to random vibration problems, leading to the creation of a spectrum-analysis-based interval vibration analysis method that determines the PSD function for the system displacement response under stationary interval process excitations. Finally, the effectiveness of the formulated spectrum-analysis-based interval vibration analysis approach is verified through two numerical examples. [ABSTRACT FROM AUTHOR]

Background: Diffusion kurtosis imaging is an advanced magnetic resonance imaging technique that reveals additional information on the microstructure and micro-dynamics of different brain masses without the need for contrast agents. The aim of this study was to provide a comprehensive analysis of the role of MRI diffusion kurtosis and to compare it with magnetic resonance spectroscopy (MRS) and dynamic susceptibility contrast perfusion (DSC) in characterizing different brain masses, including gliomas, recurrent tumors, radiation necrosis, abscesses, and infarctions. Sixty-six patients with intracranial brain masses were enrolled in this prospective study. All patients were examined by conventional MRI sequences, DSC perfusion, MRS, and diffusion kurtosis imaging, with implemented b values which were 200, 500, 1000, 1500 and 2000s/mm2. Results: Mean kurtosis (MK) was higher (P < 0.001) in recurrent brain tumors than in radiation-induced necrosis; the optimal MK cutoff value for differentiation between them was 642 with 91.3% sensitivity and 85.7% specificity. Mean kurtosis was also higher (P < 0.001) in high-grade gliomas than in low-grade gliomas; the optimal MK cutoff value for differentiation between them was 639 with 91.6% sensitivity and 85.71% specificity. There was a good level of agreement between ADC and MD within the studied cases, with a correlation coefficient r = 0.815. MK had more sensitivity and specificity in differentiation between high- and low-grade gliomas, as well as RIN and tumoral recurrence, than MRS and DSC. Conclusions: Diffusion kurtosis imaging stands as an integral, noninvasive, and noncontrast tool for the characterization of various brain masses. It augments the capabilities of traditional and advanced MRI techniques, providing a deeper understanding of the microstructural changes in brain tissues. [ABSTRACT FROM AUTHOR]

The sleeping stage classification plays an important role in the medical science because it helps the diagnosis of the mental health diseases. The conventional approach for performing the sleeping stage classification is based on the electroencephalograms (EEGs). However, it is worth noting that the EEGs reflect the brain activities. Nevertheless, the brain activities are very complicated even though the subjects are sleeping. Hence, performing the sleeping stage classification via the EEGs may yield the low classification accuracy. On the other hand, the electrooculograms (EOGs) are the voltages between the front eyes and the back eyes which are related to the eye ball movement. As it can directly reflect the various sleeping stages, it can achieve a higher classification accuracy. Therefore, this paper employs the two channel EOGs for performing the sleeping stage classification. The major contribution of this paper is to 1) employ the singular spectrum analysis (SSA) to exploit the latent intrinsic high dimensional dynamics of the one dimensional EOGs for performing the sleeping stage classification, 2) employ the approximate entropy as the features for performing the sleeping stage classification, and 3) assign the same features of different SSA components of different channels of the epochs of the EOGs into the same group and perform the principal component analysis (PCA) on each group of the feature vectors so that the properties of each type of the features are preserved. The results show that our proposed method yields the five sleeping stage classification accuracy at 93.73% and the sensitivity of the stage one non-rapid eye movement (S1) at 78.44%, which achieves the significant improvements compared to the existing methods. Therefore, our proposed method could be used to reduce the workload of the medical officers. [ABSTRACT FROM AUTHOR]

This study analyzes coupled atmosphere–ocean variability in the South Atlantic Ocean. To do so, we characterize the spatio-temporal variability of annual mean sea-surface temperature (SST) and sea-level pressure (SLP) using Multichannel Singular Spectrum Analysis (M-SSA). We applied M-SSA to ERA5 reanalysis data (1959–2022) of South Atlantic SST and SLP, both individually and jointly, and identified a nonlinear trend, as well as two climate oscillations. The leading oscillation, with a period of 13 years, consists of a basin-wide southwest–northeast dipole and is observed both in the individual variables and in the coupled analysis. This mode is reminiscent of the already known South Atlantic Dipole, and it is probably related to the Pacific Decadal Oscillation and to El Niño–Southern Oscillation in the Pacific Ocean. The second oscillation has a 5-year period and also displays a dipolar structure. The main difference between the spatial structure of the decadal, 13-year, and the interannual, 5-year mode is that, in the first one, the SST cold tongue region in the southeast Atlantic's Cape Basin is included in the pole closer to the equator. Together, these two oscillatory modes, along with the trend, capture almost 40% of the total interannual variability of the SST and SLP fields, and of their co-variability. These results provide further insights into the spatio-temporal evolution of SST and SLP variability in the South Atlantic, in particular as it relates to the South Atlantic Dipole and its predictability. [ABSTRACT FROM AUTHOR]

Background: Hyperspectral imaging (HSI), combined with machine learning, can help to identify characteristic tissue signatures enabling automatic tissue recognition during surgery. This study aims to develop the first HSI-based automatic abdominal tissue recognition with human data in a prospective bi-center setting. Methods: Data were collected from patients undergoing elective open abdominal surgery at two international tertiary referral hospitals from September 2020 to June 2021. HS images were captured at various time points throughout the surgical procedure. Resulting RGB images were annotated with 13 distinct organ labels. Convolutional Neural Networks (CNNs) were employed for the analysis, with both external and internal validation settings utilized. Results: A total of 169 patients were included, 73 (43.2%) from Strasbourg and 96 (56.8%) from Verona. The internal validation within centers combined patients from both centers into a single cohort, randomly allocated to the training (127 patients, 75.1%, 585 images) and test sets (42 patients, 24.9%, 181 images). This validation setting showed the best performance. The highest true positive rate was achieved for the skin (100%) and the liver (97%). Misclassifications included tissues with a similar embryological origin (omentum and mesentery: 32%) or with overlaying boundaries (liver and hepatic ligament: 22%). The median DICE score for ten tissue classes exceeded 80%. Conclusion: To improve automatic surgical scene segmentation and to drive clinical translation, multicenter accurate HSI datasets are essential, but further work is needed to quantify the clinical value of HSI. HSI might be included in a new omics science, namely surgical optomics, which uses light to extract quantifiable tissue features during surgery. [ABSTRACT FROM AUTHOR]

Stainless steel is a notably beneficial product and is widely used in many applications. Controlling the quality of steel products by determining their trace elemental content is essential. The content of trace elements such as Cr in steel protects the alloy from corrosion and enhances its lifetime, especially in the case of steel embedded in concrete structures. This article presents a quantitative analysis of the trace element Cr in steel samples using advanced laser-induced breakdown spectroscopy (LIBS) with an Nd:YAG laser at wavelengths of 355 and 1064 nm. The LIBS emission intensity of Cr at a laser wavelength of 355 nm was improved compared to that at 1064 nm. Notably, the calibration curves exhibit a zero intercept using the LIBS technique at the third harmonic (355 nm) and fundamental (1064 nm) wavelengths generated by the Nd:YAG laser. The detection limits for Cr in steel were determined as 21 and 36 parts per million using the laser wavelengths of 355 and 1064 nm, respectively. This study demonstrated that the wavelength of 355 nm is significantly more suitable for the quantitative analysis of stainless steel than 1064 nm in laser-induced spectroscopy. [ABSTRACT FROM AUTHOR]

The viable but non-culturable (VBNC) state is considered a survival strategy employed by bacteria to endure stressful conditions, allowing them to stay alive. Bacteria in this state remain unnoticed in live cell counts as they cannot proliferate in standard culture media. VBNC cells pose a significant health risk because they retain their virulence and can revive when conditions normalize. Hence, it is crucial to develop fast, reliable, and cost-effective methods to detect bacteria in the VBNC state, particularly in the context of public health, food safety, and microbial control assessments. This research examined the biomolecular changes in Escherichia coli W3110 induced into the VBNC state in artificial seawater under three different stress conditions (temperature, metal, and antibiotic). Initially, confirmation of VBNC cells under various stresses was done using fluorescence microscopy and plate counts. Subsequently, lipid peroxidation was assessed through the TBARS assay, revealing a notable increase in peroxidation end-products in VBNC cells compared to controls. ATR-FTIR spectroscopy and chemomometrics were employed to analyze biomolecular changes, uncovering significant spectral differences in RNA, protein, and nucleic acid concentrations in VBNC cells compared to controls. Notably, RNA levels increased, while protein and nucleic acid amounts decreased. ROC analyses identified the 995 cm− 1 RNA band as a consistent marker across all studied stress conditions, suggesting its potential as a robust biomarker for detecting cells induced into the VBNC state under various stressors. [ABSTRACT FROM AUTHOR]

This study addresses the possibility of using rank distributions of leukocyte formula and dielectric indicators of blood cell suspensions as invariant characteristics for express monitoring of pathological processes in the organism. Experiments were performed in laboratory mice with Ehrlich ascites carcinoma. [ABSTRACT FROM AUTHOR]

Mutations in isocitrate dehydrogenase (IDH) genes have important prognostic signifi cance for patients with glial neoplasms of the brain. Proton MR spectroscopy provides non-invasive determination of the metabolic properties of tumor tissue at the preoperative stage. The aim of the present work was to investigate the feasibility of determining isocitrate dehydrogenase (IDH) mutation status using magnetic resonance spectroscopy (MRS) to detect the presence of 2-hydroxyglutarate (2HG), the metabolic product of the enzyme IDH. We examined 33 patients with glial brain tumors with different degrees of malignancy (grades 2–4), with subsequent identifi cation of IDH mutations. IDH mutations found by proton MRS were confi rmed immunohistochemically in 20 cases. In 13 cases, the 2HG peak was not detected on the MR spectrum and analysis of IDH did not reveal mutations. The use of proton MRS has demonstrated that this method has high sensitivity in predicting the mutation status of glial brain tumors, which makes this method an important tool in preoperative diagnosis. [ABSTRACT FROM AUTHOR]

The effect of niobium ion implantation on the surface and scratch properties of a WC-5wt.%Ni cold sprayed coating was investigated with accelerating energies of 60 and 170 keV and fluences of 5 × 1016 and 8 × 1016 ions cm−2, respectively. High-resolution Rutherford backscattering spectroscopy spectra revealed that Ni-Nb and WC-Nb amorphous layers had likely formed. Using ion implantation parameters of 60 keV with a fluence of 8 × 1016 ions cm-2 (coating 608-NB), higher Nb peak intensities were found. Oxide formation in the form of NbO, NbO2, and Nb2O5 was detected with high-resolution x-ray photoelectron spectroscopy spectra analyses on the 608-NB coating, in conjunction with the intermetallic, thereby having the best coating properties: higher hardness, low roughness, and scratch properties compared to the other ion-doped samples. The failure mechanisms of all the coatings were found to be similar, showing angular cracks, cone cracking, and primary delamination. [ABSTRACT FROM AUTHOR]

In this paper, the structures and properties of (HF)nH2O (n = 1–9) clusters are studied by the combination of genetic algorithm (GA) and density functional theory(GDF) method. The structures are optimized at B3LYP/6–311++G(d,p) level. The refined energies are computed at CCSD(t)/aug-cc-pVDZ level. Infrared spectrum analysis, charge analysis, orbital analysis, and stability analysis are performed on the most stable configurations of each size. Lower-lying structures are obtained for (HF)nH2O (n = 5,6) clusters. (HF)7H2O cluster has special ability based on stability analysis. NCI analysis is conducted on the global optimal structure of all size clusters, and it is found that there are obvious hydrogen bonds in the clusters. Hydrogen bonding is an important factor in stabilizing (HF)nH2O (n = 1–9) composite clusters. The studied clusters can be divided into two categories: non-ionic clusters (HF)nH2O (n = 1–5) and ionic clusters (n = 6–9). [ABSTRACT FROM AUTHOR]

Background: Accurate volume status assessment and dry weight achievement are the most challenging goals for a nephrologist. We aimed to evaluate the role of ultrasonographic parameters including lung ultrasound and inferior vena cava (IVC) measurements as practical methods of volume status assessment in children on hemodialysis by comparing them with established techniques, such as clinical evaluation and bioimpedance spectroscopy. Methods: A prospective cross-sectional study compared pre- and post-dialysis volume status using bioimpedance spectroscopy (BIS) parameters and clinical data with ultrasonographic lung B-lines and IVC parameters in children on regular hemodialysis. Results: A total 60 children (mean age 9.4 ± 2.8 years) were enrolled. Twenty patients (33.3%) were clinically overloaded to varying degrees (17 patients had mild to moderate signs of fluid overload and 3 patients had moderate to severe signs of fluid overload). All other patients (66.7%) were clinically euvolemic. Sonographic parameters were significantly lower post-dialysis than pre-dialysis, including lung B-line count and IVC diameter. IVC collapsibility index mean was significantly higher post-dialysis than pre-dialysis. There was a significant correlation between the lung B-line count, IVC parameters, and BIS-measured overhydration both before and after hemodialysis. Nine patients had ≥ 8 B-lines post-dialysis, only three of them were hypertensive. Conclusions: Clinical criteria alone are not specific for determining accurate fluid status in pediatric hemodialysis patients. Lung B-line score, IVC parameters, and BIS may be complementary to each other and to clinical data. Lung B-lines outperform IVC measurements and BIS in subclinical volume overload detection in pediatric hemodialysis patients. [ABSTRACT FROM AUTHOR]

Laser spectroscopy is a very precise tool in determining atomic structure data. However, in the case of complex spectra, when the individual components of the spectra cannot be separated, precise analysis is hindered by the appearing saturation effect. Sometimes this effect is so large that the spectrum simulation does not provide precise results. In the present work, we present the analysis of the Zeeman spectra of seven praseodymium lines in the range of 566–652 nm, which were recorded using the LIF technique in the presence of the saturation effect. To analyze these spectra, we used a specially dedicated computer program, which allowed for very accurate matching of the simulated spectrum to the recorded experimental shape. As a result of the conducted research, we determined 14 Lande factor values, 3 of which are new. [ABSTRACT FROM AUTHOR]

A set of colour tuning K2Ba(MoO4)2: Dy3+/Eu3+ (KBM: Dy3+/Eu3+) phosphors were fabricated by solid-state method. The phase purity of as-prepared materials was validated by XRD and DRS analyses. The KBM: 0.03Dy3+ sample exhibits two major luminescence lines at 481 and 572 nm when excited by 351 nm light, corresponding to Dy3+ ions' typical transitions of 4F9/2 → 6HJ (J = 15/2, 13/2). By introducing Eu3+ ions into KBM: 0.03Dy3+ phosphor, the ET from Dy3+ to Eu3+ ions arises, leading to colour tuning from green via yellowish green to pink with changing Eu3+ ions' concentration, along with the lowest CCT of KBM: 0.03Dy3+/0.03Eu3+ sample. It can be verified by PLE and PL spectra analysis combined with the decay times of KBM: 0.03Dy3+/yEu3+ samples. The energy transfer mechanism is also expounded. Meanwhile, the emission intensities at 423 K still maintain 72.8% for Dy3+ ions and 91.2% for Eu3+ ions relative to 303 K of the KBM: 0.03Dy3+/0.03Eu3+ sample, displaying its brilliant thermal stability. All these results connote that KBM: Dy3+/Eu3+ phosphors are prospected to be used for the near-UV excited white light-emitting diodes. [ABSTRACT FROM AUTHOR]

We extend the law and economics analysis of spectrum management by considering the economic case for Indigenous and tribal spectrum sovereignty. We use case studies from the United States, Guatemala, Canada, and New Zealand to show that these movements seek a polycentric system of spectrum management that contrasts with the prevailing monocentric systems of spectrum management in which national governments have the primary authority over spectrum governance. Theories of polycentricity and federalism offer insight into the efficiency of Indigenous and tribal spectrum sovereignty as well as polycentric spectrum sovereignty more generally. [ABSTRACT FROM AUTHOR]

Seismic images are essential for understanding the subsurface geological structure and resource distribution. However, the accuracy and certainty of geological analysis using seismic images are limited by the resolution and signal-to-noise ratio. Simultaneously improving resolution and suppressing random noise with traditional methods can be quite challenging. This research proposes a new approach called SeisGAN which leverages a generative adversarial network to address the challenge at hand. Due to the lack of high-resolution noiseless and low-resolution noisy seismic data, stochastic parameter control is employed to simulate a vast range of diverse, paired seismic data for SeisGAN training. The results on the synthetic dataset demonstrate that the proposed method is effective in enhancing the resolution and suppressing the random noise in the original images. Spectrum analysis shows that the proposed method increases the bandwidth of the original data, primarily at high frequencies. Ablation experiments reveal that, under similar conditions, SeisGAN outperforms traditional convolutional neural networks. Incorporating the VGG loss in the generator loss function improves the model's ability to recover high-frequency details. The application of the technique on two publicly available field seismic datasets indicates SeisGAN's excellent generalizability, despite being trained only on synthetic seismic data. Compared with bicubic interpolation and traditional noise suppression and resolution enhancement methods, SeisGAN is capable of effectively suppressing the random noise and enhancing the dominant frequency of field seismic data, making it easier to identify adjacent thin layers and fault features, even for small-scale faults. The zoomed images are clearer and easier to interpret. Furthermore, an example of automatic machine fault identification demonstrates the significant contribution of the SeisGAN-enhanced image to accurate fault recognition. [ABSTRACT FROM AUTHOR]

The study of the rapid detection method of cucumber chlorophyll content and hardness can lay the foundation for the rapid detection of cucumber quality. A Raman Spectroscopy coupled with Competitive Adaptive Reweighted Sampling (CARS) and Support Vector Machines (SVM) method was reported to detect chlorophyll content and hardness of cucumber under different storage time. Mapping images of chlorophyll content and hardness were constructed based on Raman wavenumbers within the range of 1500–1550 cm− 1and1300-1350 cm− 1, respectively. Distribution and changes of the chlorophyll content and hardness were demonstrated by mapping images. 35 and 33 characteristic wavenumbers for chlorophyll content and hardness of cucumber were extracted by CARS, respectively. The full spectral wavenumbers, characteristic wavenumbers of mapping image and characteristic wavenumbers extracted by CARS were compared, and 4 kind of kernel functions were analyzed. For the chlorophyll and hardness, support vector machine (SVM) model constructed based on the CARS characteristic wavenumbers and RBF kernel function had achieved good prediction result, The R2 of training set and the testing set was both over 0.9. The results showed that Raman spectroscopy technology combined with the CARS-SVM algorithm can achieve a rapid detection of chlorophyll content and hardness in cucumber. [ABSTRACT FROM AUTHOR]

A method is proposed for separately determining the concentrations of "light" and "heavy" electrons in n-GaSb. It is based on the analysis of reflection spectra in the far infrared region, taking into account the plasmon-phonon coupling. Calibration curves have been calculated that allow one to determine the concentrations of "light" and "heavy" electrons in GaSb using the frequency of high-energy coupled plasmon-phonon mode. For a series of n-GaSb samples the reflection spectra were measured and the concentrations of "light" and "heavy" electrons were determined at room temperature. Electrophysical Van der Paw measurements have been performed on the same samples at room temperature. By comparing the optical and Hall data, the ratios of the mobilities of "light" and "heavy" electrons (parameter b) were determined. This method of determining the value of the parameter b is used for the first time. [ABSTRACT FROM AUTHOR]

Purpose: Higher dietary intake or higher circulating levels of the trace element boron have been associated with beneficial effects on human health. However, the relationship between plasma boron levels and survival in the general population is not known. Therefore, we aimed to assess the association between plasma boron concentrations and all-cause mortality in a population-based cohort from northern Germany (n = 863 individuals; median age 62.3 years, 42.8% women). Methods: Plasma boron concentrations (median 31.9 µg/L [22.9; 43.5]) were measured by inductively coupled plasma-mass spectrometry. Cox proportional hazards regression models adjusted for relevant confounders were used to associate plasma boron concentrations with all-cause mortality. Results: After a median follow-up time of 11 years, n = 99 individuals had died. In the overall sample, plasma boron concentrations were associated with all-cause mortality in the crude model (HR: 1.07 [95% CI 1.03–1.11] per 5-unit-increment). However, multivariable adjustment rendered the association non-significant (HR: 1.03 [95% CI 0.99–1.07]). Sex-stratified analyses revealed slightly higher mortality hazards with increasing plasma boron concentrations in women (HR: 1.11 [95% CI 1.03–1.18], pInteraction = 0.034), but not in men (HR: 1.00 [95% CI 0.95–1.06]). Conclusion: We conclude that in a moderate-sized sample from the general population, higher plasma boron concentrations were associated with a higher risk of all-cause mortality in women, but not in men. Due to the low number of events in the female subsample (n = 27), this observation has to be interpreted with caution. [ABSTRACT FROM AUTHOR]

Thiosemicarbazones derived from 3-acetylfuran-2(5H)-ones reacted with diethyl acetylenedicar-boxylate in anhydrous ethanol, as well as with maleic anhydride in chloroform, to produce new derivatives containing furan-2(5H)-one and 4-oxothiazolidine fragments. The synthesized compounds were characterized by NMR spectra and elemental analyses. [ABSTRACT FROM AUTHOR]

We have investigated the formation of optical radiation and refined the set of parameters for the young pre-cataclysmic binary with an sdB-subdwarf V1828 Aql. We have obtained moderate-resolution spectra with the 6-m BTA telescope and multiband light curves with the Zeiss-1000 telescope at the Special Astrophysical Observatory of the Russian Academy of Sciences. The method of model stellar atmospheres with an accurate allowance for the gravitational and radiative interaction of the components has been used to calculate the optical radiation from the system. We have found that, despite the high temperature of the primary component, K, the amplitude of the photometric reflection effects limited by the small sizes of the secondary component does not exceed . The emission features in the HI lines forming on the irradiated part of the surface of the cool star, when added with the absorption lines in the spectrum of the sdB-subdwarfs, weaken them by 10–12 and shift them by km s in a narrow range of phases adjacent to the time of the secondary eclipse. As a result, the distortions of the observed radial velocity curves under the action of reflection effects turn out to be much smaller than the measurement errors and cannot be used to determine the component mass ratio from a model analysis. Therefore, to determine the set of parameters for V1828 Aql, we have used the assumption that the mass of the primary component is close to found previously for a large group of sdB-subdwarfs. Based on our model analysis of the observed spectra and light curves for V1828 Aql, we have estimated the atmospheric parameters of the subdwarf and the fundamental parameters of both components. We have found that using the method of model atmospheres in analyzing the reflection effects reduces the estimate of the radius of the cool star by 20 compared to the calculations in the blackbody approximation. [ABSTRACT FROM AUTHOR]

Krylov complexity has been proposed as a diagnostic of chaos in non-integrable lattice and quantum mechanical systems, and if the system is chaotic, Krylov complexity grows exponentially with time. However, when Krylov complexity is applied to quantum field theories, even in free theory, it grows exponentially with time. This exponential growth in free theory is simply due to continuous momentum in non-compact space and has nothing to do with the mass spectrum of theories. Thus by compactifying space sufficiently, exponential growth of Krylov complexity due to continuous momentum can be avoided. In this paper, we propose that the Krylov complexity of operators such as O = Tr[FμνFμν] can be an order parameter of confinement/deconfinement transitions in large N quantum field theories on such a compactified space. We explicitly give a prescription of the compactification at finite temperature to distinguish the continuity of spectrum due to momentum and mass spectrum. We then calculate the Krylov complexity of N = 4, 0 SU(N) Yang-Mills theories in the large N limit by using holographic analysis of the spectrum and show that the behavior of Krylov complexity reflects the confinement/deconfinement phase transitions through the continuity of mass spectrum. [ABSTRACT FROM AUTHOR]

A simple glass system [Li2O–B2O3–NiO] was prepared via the melt-quenching method. This article attempts to outline the structural-optical relationships of Ni ions-bearing lithium borate glass. XRD confirmed the glassy nature of the samples. The increase in density confirmed the formation of a rigid network constructed by BO 4 units. Infrared spectra analysis confirmed a strong structure conversion from BO 3 to BO 4 units, with observed mitigation in non-bridging oxygen bonds. Optical absorbance spectra were analyzed to extract optical features. Nickel ions were exploited to disclose the surrounding environment in glass. A set of optical transitions of nickel ions in octahedral forms were assigned at 1287, 815, 487 and 425 nm, which are exploited to probe ligand field effects. A decrease in splitting energy values and increased interelectronic repulsion values were obtained. This is owing to the weak intensity of the interaction of Ni ions with surrounding ligands and the localization of d-electrons, respectively. These variations led to a strong enhancement in the ionicity of bonding nature. Furthermore, the brown color of the samples confirmed the occupancy of Ni 2 + in octahedral sites. Moreover, the indirect optical band gap increased due to the harsh reduction in NBO. These findings pave the way toward developing optical materials with the desired optical features. [ABSTRACT FROM AUTHOR]

The High Dam is one of the world's biggest embankments dams. Moreover, the new city of Aswan, which locates on the western side of the Nile River, is one of the cities that was established to overcome the growing population problem. Therefore, the detailed geophysical studies for the active faults are of more importance for assessing the seismic stability for both of them. Indeed, the emergency spillway fault was documented as a normal and inactive fault. While, a moderate earthquake (ML = 4.6) was recorded along this fault in 2010, about 4.5 km away from the Dam. Hence, its activity must be re-evaluated. The seismic activity along the fault and its extension has been studied. The seismicity distributions and the fault plane solution indicate normal faulting with a strike-slip component and shallow focal depth. Moreover, pore pressure and fluid diffusion play an essential role in fault activation process. On the other hand, the magnetic data for the research area was subjected to a detailed analysis. 2D spectrum analysis and 3D Euler deconvolution methods, were used to analyze and interpret the aeromagnetic anomaly data so as to better understand the tectonic framework of the study region. Finally, the integrated geophysical data delineate the trend of the emergency spillway fault which extends NW–SE. This fault could assist in updating the current seismic source model around the High Dam and new Aswan city for evaluating the seismic hazard for both of them. [ABSTRACT FROM AUTHOR]

Purpose: The vibration problem of nonlinear structures is very challenging, especially for random excitations. Methods: This paper investigates the power spectral characteristics of the random vibration response of a structure with a nonlinear energy sink (NES) in the frequency domain. Using the statistical characteristics of system response, an optimized objective function is constructed, and a stochastic optimization method is established to realize the parameter optimization of the NES attachment of the structure under random excitation. The random excitation is modeled as a complex exponential series represented by random variables, and the multi-harmonic balance method (MHBM) is used to analyze the random vibration of the multi-degree-of-freedom (MDOF) coupled nonlinear system. Results: By introducing the alternating frequency time (AFT) approach, the analytical derivation of nonlinear constitutive equations in the frequency domain is avoided, and the iterative calculation of power spectral density (PSD) analysis of random vibration based on the frequency domain is effectively realized. Moreover, the peak shift and multi-peak response of the response PSD of the system coupled with NES are discussed. To solve the nonlinear optimization problem of NES system parameters, an MHBM–GA optimization approach is proposed, which realizes the parameter optimization of the nonlinear coupled system under random excitation. Conclusions: This study provides a new method for the vibration analysis and optimization design of NES under random excitation. [ABSTRACT FROM AUTHOR]

The planned missions to explore the surfaces of the Moon and Mars require high exploration efficiency, thus imposing new demands on the mobility system of planetary rovers. In this paper, a design method for a high-speed planetary rover (HPR) is proposed, and the representative configurations are modeled and simulated. First, the influence of the planetary surface environment on the design of HPRs is analyzed, and the design factors for HPRs are determined by studying a single-wheel suspension. Second, a design methodology for HPRs is proposed. The adaptive suspension mechanisms of a four-wheeled rover are synthesized using the all-wheel-attachment condition and position and orientation characteristics theory, which are expressed in the form of a graph theory for the increase in elastic components and active joints. Finally, a dynamic model is built, and a simulation is carried out for the proposed rover. The validity of the proposed method and rover is verified, thus highlighting their potential application in future planetary exploration. [ABSTRACT FROM AUTHOR]

Based on the Galerkin method with Chebyshev polynomials, we numerically solve the Orr-Sommerfeld problem with high accuracy. We calculate the spectra of the planeparallel Poisseuille and Couette flows, the Blasius flow, and flows with pressure gradient above a flat semi-infinite plate for different values of the wave number and the Reynolds number. [ABSTRACT FROM AUTHOR]

In this paper, we discuss properties of the singular value decomposition (SVD-decomposition) within the framework of the analysis of the numerical rank in ill-posed problems for determining frequency properties of discrete sequences consisting of trigonometric binomials. The properties of the numerical rank of the SVD-decomposition are indicated. We propose an algorithm for determining the frequencies of trigonometric binomials involved in the original function that forms a discrete sequence; this algorithm is based on estimates of the numerical rank. We obtain a stable criterion for estimating the numerical rank based on the arithmetic-mean estimators of the pseudo-null-space of the trajectory matrix. Also, we present the results of numerical experiments that demonstrate the consistency of the arithmetic-mean estimator of the pseudo-zero-space for the analysis of the spectrum of noisy sequences. [ABSTRACT FROM AUTHOR]

The study was aimed at developing a new automatic search technique for specific invariant patterns of movement-related brain potentials reflected in multidimensional electroencephalogram (EEG) signals. An adaptive band-pass filter with bandwidth closely matching the spectrum of the desired EEG pattern at the observed moment was synthesized based on the Singular Spectrum Analysis methodology. The preliminary filtering of the original EEG signals provides the required sensitivity for subsequent searching of time boundaries in patterns. The correctness of the developed method was confirmed with standard machine learning tools through the validation of the adaptive search method carried out on the general set of initial data. It is shown that the synthesized method has provided a reliable automatic search for induced pre-movement EEG patterns and the correct determination of their time boundaries (accuracy up 29% on average and reached maximum values to 100% for some individuals). The developed method expands the existing tools to improve the functionality and reliability of various Brain-computer interfaces for various purposes, including medical applications for paralyzed patients. [ABSTRACT FROM AUTHOR]

Purpose: Diet-related diseases are advancing as the leading cause of death globally. As self-reporting of diet by patients can be associated with errors, stable isotopes of human tissues can be used to diagnose diseases, understand physiology, and detect change in diet. This study investigates the effect of type and amount of food on the nitrogen and carbon concentration (Nconc and Cconc) and isotopic composition (δ15N and δ13C) in human scalp hair and fingernails. Methods: A total of 100 residents participated in the study whereas only 74 individuals provided complete diet history. Sixty-six food items majorly available to them were also collected. The Nconc, Cconc, δ15N and δ13C values of human hair, nails and food items were determined. Results: The Nconc, Cconc, δ15N and δ13C values between plant-sourced and animal-sourced food items, as well as human hair and nail tissue were significantly different (p < 0.05). The δ15N value of human tissues was distinct between lacto-vegetarians and omnivores by 0.9‰. The δ15N and δ13C values of human tissues increased by 0.4–0.5‰ with every 5% increase in the consumption of animal protein. Conclusions: The study helps to demarcate lacto-vegetarians from omnivores, and estimate the percentage of animal protein in diet based on the dual isotope values of human tissues. It also acts as a reference to determine isotopic composition of hair tissue provided the isotope value of nail tissue is known and vice versa. [ABSTRACT FROM AUTHOR]

Background: After esophagectomy, the postoperative rate of anastomotic leakage is up to 30% and is the main driver of postoperative morbidity. Contemporary management includes endoluminal vacuum sponge therapy (EndoVAC) with good success rates. Vacuum therapy improves tissue perfusion in superficial wounds, but this has not been shown for gastric conduits. This study aimed to assess gastric conduit perfusion with EndoVAC in a porcine model for esophagectomy. Material and methods: A porcine model (n = 18) was used with gastric conduit formation and induction of ischemia at the cranial end of the gastric conduit with measurement of tissue perfusion over time. In three experimental groups EndoVAC therapy was then used in the gastric conduit (− 40, − 125, and − 200 mmHg). Changes in tissue perfusion and tissue edema were assessed using hyperspectral imaging. The study was approved by local authorities (Project License G-333/19, G-67/22). Results: Induction of ischemia led to significant reduction of tissue oxygenation from 65.1 ± 2.5% to 44.7 ± 5.5% (p < 0.01). After EndoVAC therapy with − 125 mmHg a significant increase in tissue oxygenation to 61.9 ± 5.5% was seen after 60 min and stayed stable after 120 min (62.9 ± 9.4%, p < 0.01 vs tissue ischemia). A similar improvement was seen with EndoVAC therapy at − 200 mmHg. A nonsignificant increase in oxygenation levels was also seen after therapy with − 40 mmHg, from 46.3 ± 3.4% to 52.5 ± 4.3% and 53.9 ± 8.1% after 60 and 120 min respectively (p > 0.05). An increase in tissue edema was observed after 60 and 120 min of EndoVAC therapy with − 200 mmHg but not with − 40 and − 125 mmHg. Conclusions: EndoVAC therapy with a pressure of − 125 mmHg significantly increased tissue perfusion of ischemic gastric conduit. With better understanding of underlying physiology the optimal use of EndoVAC therapy can be determined including a possible preemptive use for gastric conduits with impaired arterial perfusion or venous congestion. [ABSTRACT FROM AUTHOR]

A principle is proposed for hybrid endoscopes, which combines the advantages of televisual and multispectral methods of image transmission and supports the diagnosis of cancer and other diseases of the internal organs at an early stage of their development. This report describes a study of a method for minimizing information loss in endoscopes of this type by specifically selecting the ratio of spatial and spectral resolutions of the device and methods for its experimental implementation. [ABSTRACT FROM AUTHOR]

Nanocomposites comprising (V2O5)x. (Mn0.4Fe2.6O4)(2−x), where x = [0.2, 0.4, 0.6, 0.8, and 1], were successfully synthesized by milling each single phase of V2O5 and Mn0.4Fe2.6O4 nanostructured samples. We studied the structure and morphology of the prepared samples through X-ray diffraction and scanning electron microscopy. UV–Vis. spectrum analysis was used to study the optical characteristics. As an attempt to improve the optical and nonlinear optical properties of the PVDF blend, the prepared nanocomposites were used as nanofillers for the poly (vinylidene fluoride) (PVDF) polymer. Optical and nonlinear optical properties of the PVDF polymer were tuned using (V2O5)x. (Mn0.4Fe2.6O4)(2−x), where x = [0.2, 0.4, 0.6, 0.8, and 1] nanocomposite. The obtained results showed a tunable spectrum, absorption, refractive index, and dielectric constant at wavelengths ranging from 200 to 800 nm. However, the results showed that the (V2O5)0.6. (Mn0.4Fe2.6O4)1.4, sample was the best for obtaining the lowest transmittance percentage and bandgap energy. The nonlinear optical properties and Kerr effect (quadratic electro-optic effect) showed a significant response, which can be tuned in the range from 200 to 1200 nm of wavelength using the investigated samples. Finally, incorporating (V2O5)x. (Mn0.4Fe2.6O4)(2−x), where x = [0.2, 0.4, 0.6, 0.8, and 1], nanoparticles in the PVDF polymer improved the hydrophilic behavior of the PVDF films. This study suggests a promising nanocomposite material for tunable optoelectronics and useful polymer membranes. [ABSTRACT FROM AUTHOR]

This study attempts to examine the morphological, elemental and physical characteristics of PM10 over the Indian Himalayan Region (IHR) using FTIR and scanning electron microscopy-energy dispersive X-ray (SEM-EDX) analysis. The study aimed at source identification of PM10 by exploring the inorganic ions, organic functional groups, morphology and elemental characteristics. The pollution load of PM10 was estimated as 63 ± 22 μg m−3; 53 ± 16 μg m−3; 67 ± 26 μg m−3 and 55 ± 11 μg m−3 over Mohal-Kullu, Almora, Nainital and Darjeeling, respectively. ATR-FTIR spectrum analysis revealed the existence of inorganic ions (SiO44−, TiO2, SO42−, SO3−, NO3−, NO2−, CO32−, HCO3−, NH4+) and organic functional groups (C–C, C–H, C=C, C≡C, C=O, N-H, C≡N, C=N, O-H, cyclic rings, aromatic compounds and some heterogeneous groups) in PM10 which may arise from geogenic, biogenic and anthropogenic sources. The morphological and elemental characterization was performed by SEM-EDX, inferring for geogenic origin (Al, Na, K, Ca, Mg and Fe) due to the presence of different morphologies (irregular, spherical, cluster, sheet-like solid deposition and columnar). In contrast, particles having biogenic and anthropogenic origins (K, S and Ba) have primarily spherical with few irregular particles at all the study sites. Also, the statistical analysis ANOVA depicts that among all the detected elements, Na, Al, Si, S and K are site-specific in nature as their mean of aw% significantly varied for all the sites. The trajectory analysis revealed that the Uttarakhand, Jammu and Kashmir, the Thar Desert, Himachal Pradesh, Pakistan, Afghanistan, Nepal, Sikkim, the Indo-Gangetic Plain (IGP) and the Bay of Bengal (BoB) contribute to the increased loading of atmospheric pollutants in various locations within the IHR. [ABSTRACT FROM AUTHOR]

The continuous decrease of low-slope cropland resources caused by construction land crowding poses huge threat to regional sustainable development and food security. Slope spectrum analysis of topographic and geomorphic features is considered as a digital terrain analysis method which reflects the macro-topographic features by using micro-topographic factors. However, pieces of studies have extended the concept of slope spectrum in the field of geoscience to construction land to explore its expansion law, while research on the slope trend of cropland from that perspective remains rare. To address the gap, in virtue of spatial analysis and geographically weighted regression (GWR) model, the cropland use change in the Yangtze River Basin (YRB) from 2000 to 2020 was analyzed and the driving factors were explored from the perspective of slope spectrum. Results showed that the slope spectrum curves of cropland area-frequency in the YRB showed a first upward then a downward trend. The change curve of the slope spectrum of cropland in each province (municipality) exhibited various distribution patterns. Quantitative analysis of morphological parameters of cropland slope spectrum revealed that the further down the YRB, the stronger the flattening characteristics, the more obvious the concentration. The province experienced the greatest downhill cropland climbing (CLC) was Shannxi, while province experienced the highest uphill CLC was Zhejiang. The most common cropland use change type in the YRB was horizontal expansion type. The factors affecting average cropland climbing index (ACCI) were quite stable in different periods, while population density (POP) changed from negative to positive during the study period. This research is of practical significance for the rational utilization of cropland at the watershed scale. [ABSTRACT FROM AUTHOR]

Purpose: Identification of fatigue-breathing cracks at an early stage offers critical information about the health of structures, aiding in the prevention of catastrophic failure and saving human lives. Localization of multiple breathing cracks is a highly challenging inverse problem, as all these breathing cracks (more than two) might be in a similar state (either opening or closing state) at any particular time instant or in contrasting states (while some breathing cracks are opening, others in closing state) during vibration. This paper presents a spectral correlation approach for the localization of multiple breathing cracks on beams exploiting the modulation effect on the vibration data with bitone harmonic excitation. Contribution and Method: A new nonlinear damage indicator based on cyclic spectral energy is developed for breathing crack identification in beams. Effects of the varied spatial location of multiple breathing cracks, different crack depths, measurement noise, and limited sensors are studied numerically. The superiority and the uniqueness of the proposed spectral correlation approach are verified by comparing it to other popular breathing crack diagnosis algorithms, including singular spectrum analysis (SSA) and weighting function augmented curvature approach. Results and Conclusion: The results of both numerical and experimental investigations in this paper reveal that the proposed spectral correlation algorithm can effectively localize the multiple breathing cracks with different severities present at various spatial positions in the beam. Studies also indicate that the proposed cyclic spectral energy-based nonlinear damage indicator can effectively localize closely spaced or sparsely spaced (i.e., spatially far apart) cracks in the beam. [ABSTRACT FROM AUTHOR]

The inspection of fabric defects is of great importance, as undetected and uncorrected defects entail poor production quality and expensive compensation. Due to the variety of defect types and sizes, it is a very tedious task to perform inspection manually. There are numerous automated systems in the literature; however, most of them require a training scheme where clean and defective fabric samples are manually fed to the system. Because of the diversity of fabric patterns and defect classes, supervised systems reduce convenience and ease of use in real practice. In this study, we propose an unsupervised, robust fabric defect detection method using spectral domain analysis. The proposed algorithm has a very simple flow and can run without any prior training scheme. First, the algorithm splits the input textile image into smaller patches and computes a generic spectral representation of the fabric pattern. Then, the method detects defective regions by measuring dissimilarities between the spectral representation and all local patches of the input fabric. We also introduce a textile fabric dataset, i.e., Ten Fabrics Dataset, which consists of ten different types of fabrics with 27 of the most common textile defects. According to the extensive set of experiments on two different datasets, the proposed method outperforms the state-of-the-art by achieving up to 94% accuracy. [ABSTRACT FROM AUTHOR]

Due to the complexity and volatility of stock market trading, there are still some issues in the existing prediction methods, including the processing of data noise, inexplicable selection of model parameters, and the lag in predicting price fluctuations. Aiming to better predict daily stock prices and fluctuations caused by high noise non-stationary data in actual trading, we propose a hybrid deep learning framework based on Singular Spectrum Analysis (SSA), multiple feature selection, and Long Short Term Memory (LSTM) network optimized by Particle Swarm Optimization (PSO). Based on Pearson correlation coefficients, we select features highly correlated with the closing price as inputs, and further achieve the noise reduction and optimization of those input sources by applying SSA to decompose the stock price time series into independent component signals. Using the stock price data from China and USA, we compared the prediction performance of our method with several well-known methods, and found that it achieved higher price prediction accuracy during periods of high stock volatility. For example, the R-squared and prediction accuracy of Shanghai Composite Index achieved 0.9998 and 99.01%, while the prediction metrics of S &P 500 reached 0.9883 and 94.26%, respectively. Besides, considering transaction costs, our method also achieved the highest profit in trading tests, even compared to long-term holding strategy. [ABSTRACT FROM AUTHOR]

Background: The bimolecular fluorescence complementation (BiFC) assay is commonly used for investigating protein–protein interactions. While several BiFC detection systems have been developed, there is a limited amount of research focused on using laser scanning confocal microscope (LSCM) techniques to observe protoplasts. Protoplasts are more susceptible to damage and instability compared to their original cell state due to the preparation treatments they undergo, which makes it challenging for researchers to manipulate them during observation under LSCMs. Therefore, it is crucial to utilize microscope techniques properly and efficiently in BiFC assays. Results: When the target fluorescence is weak, the autofluorescence of chloroplast particles in protoplasts can interfere with the detection of BiFC signals localized in the nuclear region. Spectrum analysis revealed that chloroplast autofluorescence can be excited by lasers of various types, with the highest fluorescence signal observed at around 660 nm. Furthermore, our investigation into the impact of different pipette tips on the integrity of protoplast samples indicated that the utilization of cut tips with larger openings can mitigate cell breakage. We presented a workflow of LSCM techniques for investigating protoplast BiFC and discussed the microscopic manipulation involved in sample preparation and image capturing. Conclusion: When the BiFC signals are weak, they may be affected by chloroplast autofluorescence. However, when used properly, the autofluorescence of chloroplasts can serve as an excellent internal marker for effectively distinguishing other signals. In combination with other findings, this study can provide valuable reference for researchers conducting BiFC assays and related studies. [ABSTRACT FROM AUTHOR]

In the present investigation, a high-quality single crystal of BMZC was obtained by slow evaporation and its structural organization was determined by single-crystal X-ray diffraction. The distinct vibrations and functional groups of the crystal have been identified via FTIR spectroscopy. The properties of absorbance and transparency were investigated using UV–Vis spectrum analysis. Photoluminescence studies were conducted to investigate the emission properties of the crystals, with an emphasis on the UV region. The thermal stability of the BMZC was evaluated using TG-DTA analysis to look at its behavior in relation to temperatures. Several vibrational frequencies were used in the dielectric studies to examine the crystal's dielectric characteristics. The Vickers microhardness test was used to assess the crystal's mechanical properties. The Nd:YAG laser (1064 nm) was utilized to determine the laser damaging limit of crystals. Using the Z-scan approach, we simultaneously determine the nonlinear absorption coefficient (β) and nonlinear refractive index (n2) for both open and closed aperture configurations, respectively. [ABSTRACT FROM AUTHOR]

The characteristic time scales of the response of the globally averaged climate model with the carbon cycle to external forcing with analysis of the spectrum of the linearized evolution operator of the corresponding dynamic system are evaluated. The model exhibits response time scales of about 4–6 years (related to the carbon dynamics in vegetation) and in the range of 20–100 years (related to the carbon dynamics in nonhumified soil reservoirs). When taking into account the effect of humification, the model reveals the time scale of the response, which is on the order of several millennia. For a closed carbon cycle, the time scale is 102 years, which characterizes the joint variations in the atmospheric and oceanic reservoirs. The proposed approach is highly universal and can be used for a wide range of tasks. [ABSTRACT FROM AUTHOR]

Streamflow predictions play a crucial role in the planning and management of water structures. However, accurately predicting streamflow data, which exhibits nonlinear and nonstationary characteristics, is a challenging problem. In this study, a novel approach was proposed for the prediction of both overall and peak streamflows, aiming to achieve high performance. The data used included precipitation and streamflow time series, as well as lagged data from the empirical mode decomposition (EMD), variational mode decomposition (VMD), and circulant spectrum analysis (ciSSA) subbands. The minimum redundancy maximum relevance (MRMR) method was employed for feature selection from these datasets. The selected features were used to develop daily streamflow prediction models using Gaussian process regression (GPR), ensemble (boosting and bagging), support vector regression (SVR), and artificial neural network (ANN) methods. The performance of the developed MRMR-, EMD-MRMR-, VMD-MRMR-, and ciSSA-MRMR-machine learning models was evaluated using mean squared error (MSE), mean absolute error (MAE), correlation coefficient (R), and determination coefficient (R2) metrics. Additionally, the Bland-Altman plots and the Kruskal–Wallis test were used to determine the statistical significance of the results. According to the results, the ciSSA-MRMR-machine learning models achieved higher performance compared to the other models (R2 value of 0.956, an MSE of 0.0001, and an MAE of 0.0049 for overall streamflow prediction). For peak streamflow prediction, the ciSSA-MRMR-ANN model yielded an R2 value of 0.956, an MSE of 0.0002, and an MAE of 0.0217. It was observed that the proposed method significantly improved the prediction of not only overall streamflow but also peak streamflow values. [ABSTRACT FROM AUTHOR]

Multidimensional NMR spectra are the basis for studying proteins by NMR spectroscopy and crucial for the development and evaluation of methods for biomolecular NMR data analysis. Nevertheless, in contrast to derived data such as chemical shift assignments in the BMRB and protein structures in the PDB databases, this primary data is in general not publicly archived. To change this unsatisfactory situation, we present a standardized set of solution NMR data comprising 1329 2–4-dimensional NMR spectra and associated reference (chemical shift assignments, structures) and derived (peak lists, restraints for structure calculation, etc.) annotations. With the 100-protein NMR spectra dataset that was originally compiled for the development of the ARTINA deep learning-based spectra analysis method, 100 protein structures can be reproduced from their original experimental data. The 100-protein NMR spectra dataset is expected to help the development of computational methods for NMR spectroscopy, in particular machine learning approaches, and enable consistent and objective comparisons of these methods. [ABSTRACT FROM AUTHOR]

A new preconditioned modified conjugate gradient algorithm based on improved gradient operator and preconditioned technology is proposed for moving force identification of bridge structure in this paper. First, the moving load identification problem is converted into the problem of solving large-scale linear equations by the time-domain deconvolution technology and modal superposition method. Then the large-scale linear equations problem is transformed into easily solved equivalent problem by preprocessing. Subsequently, it is transformed into an unconstrained linear optimization problem by constructing the corresponding objective function. Finally, the problem is solved by the proposed conjugate gradient method. The innovation of the proposed method lies in two aspects. First, the proposed conjugate gradient method is proved by mathematical theory. Second, before constructing the objective function, the preconditioned technique is utilized to simplify the original problem. A series of numerical simulations are carried out to verify the stability and effectiveness of the proposed approach under 21 kinds of noise levels and 6 different sensor configurations, and its performances are compared with several conjugate gradient methods. The results show that the proposed method can reduce the iteration number, and also ensure the load identification accuracy, which indicates that the proposed method can improve the speed of identification and effectively reduce the cost. Meanwhile, the identification situation of different load components is studied by the frequency spectrum analysis method. It is found that the proposed method is a stable and a reliable identification method for static and low-frequency components, which provides a new idea for dynamic weighing of low-frequency loads on bridges. [ABSTRACT FROM AUTHOR]