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[Display omitted] • A green synthesis of Quercetin from tea leaves. • Upon β-CD complexation improves water solubility and bioavailability of Quercetin. • Binding of substrate into CD cavity in the order per-6-ABCD > Mono-6-ABCD > γ-CD > β-CD > α-CD. • Proposed model strongly supports 1:1 Host-Guest complexation of Quercetin-β-CD. We prepared a naturally occurring flavanoid namely quercetin from tea leaves and analyzed by Absorption, Emission, FT-IR, 1H, 13C nmr spectra and ESI-MS analysis. The inclusion behavior of quercetin in cyclodextrins like α-, β-, γ-, per-6-ABCD and mono-6-ABCD cavities were supported such as UV–vis., Emission, FT-IR and ICD spectra and energy minimization studies. From the absorption and emission results, the type of complexes formed were found to depend on stoichiometry of Host:Guest. FT-IR data of CD complexes of quercetin supported inclusion complex formation of the substrate with α-, β- and γ-CDs. The inclusion of host–guest complexation of quercetin with α-, β-, γ-CDs, per-6-ABCD and mono-6-ABCDs provides very valuable information about the CD:quercetin complexes, the study also shows that β-CD complexation improves water solubility, chemical stability and bioavailability of quercetin. Besides, phase solubility studies also supported the formation of 1:1 drug-CD soluble complexes. All these spectral results provide insight into the binding behavior of substrate into CD cavity in the order per-6-ABCD > Mono-6-ABCD > γ-CD > β-CD > α-CD. The proposed model also finds strong support from the fact with excess CD this exciton coupling disappears indicates the formation of only 1:1 complex. [ABSTRACT FROM AUTHOR]

Raman spectroscopy represents an advanced process analytical technology to monitor and control chemical and biochemical processes. This study presents an autoencoder-based methodology that simulates Raman spectra from process variables and predicts the concentrations of different chemicals. The methodology accurately predicts concentrations from the spectra, even considering the temperature influences, and can work as an anomaly detector in process monitoring. The proposed methodology has significant implications for the optimization of industrial processes, improving process efficiency, reducing waste, and minimizing costs. It can also be extended to other industrial processes and imaging spectroscopy techniques, making it a valuable tool for process monitoring. This study highlights the effectiveness of autoencoders in simulating spectra and quantitative analysis, contributing significantly to the field of process monitoring. It has the potential to revolutionize industrial process monitoring and optimization, leading to substantial improvements in productivity and sustainability. [Display omitted] • Raman spectroscopy is a cutting-edge PAT for (bio)chemical process monitoring. • A method is introduced for simulating Raman spectra from process variables. • The method accurately predicts chemical concentrations with temperature variations. • The method can serve as an effective anomaly detector during process monitoring. [ABSTRACT FROM AUTHOR]

Detecting bearing faults helps ensure the healthy operation of machinery and prevents serious accidents. However, fault diagnosis method based on deep learning relies on the correlation between the extracted vibration signal features. It does not consider the causal relationship between fault, noise, and vibration waveform changes, resulting in lower bearing fault diagnosis accuracy under realistic working conditions. This study proposes a graph neural network (GNN) method based on the Granger causality test for bearing fault detection called GCT-GNN to address this issue. The proposed method first performs feature transformation on the original signals to extract time-domain and frequency-domain features, forming a feature matrix. Then, spectral analysis is conducted on both faulty signals with noise and healthy signals to calculate the lag order between them. Subsequently, the Granger causality test is employed to quantify the impact of faults and noise on signal changes, and the quantified results are used to calculate weights, constructing an adjacency matrix. The completed adjacency matrix and feature matrix are input into the GNN for feature mapping, last classifying the bearing fault data. In this paper, five models, Deep residual shrinkage Network (DRSN), GNN, Support Vector Machines(SVM), Random Forests (RF), and Convolutional Neural Network(CNN) were selected, and comparative experiments were carried out on two public data sets. The results show that, compared with other models, GCT-GNN has better anti-noise ability and is better than other models in various fault diagnoses. • The effect of noise on vibration signal is quantified by Granger causality test. • The lag order was calculated by using spectrum analysis method. • The method of calculating weight by causality is proposed to construct causality graph. • Construct a graph neural network using causal graphs. [ABSTRACT FROM AUTHOR]

Multi-signal calibrations have been recently exploited in molecular spectrochemical analysis alternatively to traditional calibration methods, improving analytical frequency and accuracy. The application of these strategies is simple and minimizes efficiently matrix effects by analyzing two calibration solutions comprising sample plus standard (S1), and sample plus blank (S2). The plot of the signals obtained with S1 and S2 at multiple settings (e.g. different wavelengths) yield a slope that can be related to the analyte concentration in the sample. Similarly, transient signals could also be related to the analyte concentration exploiting a similar strategy. Thus, in this work, two multi-signal approaches developed in flow-based systems are proposed, based on the responses at multiple wavelengths (online multi-energy calibration, OMEC), and on the dispersion profile of the samples, herein denominated multi-dispersion calibration (MDC). The calibrations were carried out with sample solutions after 2-fold dilution with a standard solution and with water. The feasibility of OMEC and MDC were demonstrated using KMnO 4 solutions (without chemical reactions) under continuous and pulsed flow regimes. The applicability of this strategy was also demonstrated by the spectrophotometric determination of urea in milk and pet potty spray in a multi-pumping flow system, based on the color change of bromothymol blue after catalyzed hydrolysis by urease from jack beans (Canavalia ensiformis). MDC and OMEC were compared with external calibrations (EC) and classical standard addition. The limits of detection for urea were estimated at 13 mg L−1, 16 mg L−1, and 10 mg L−1 using MDC, MEC and EC, respectively. Recoveries from 93 to 101%, and the agreement of sample analyzes with the reference procedure demonstrated the good accuracy achieved by the proposed methods. Therefore, it was demonstrated the feasibility of MDC and OMEC for analytical purposes in a simple and efficient way with the advantages of flow-based manifolds. [Display omitted] • Multi-signal calibrations in flow analysis using the diluted sample with the blank and with a standard solution. • Calibration based on the dispersion profile of the sample zone by overlapping transient signals. • Online multi-energy calibration exploiting the simultaneous acquisition of transient signals at multiple wavelenghts. • Fast and simple procedures with appropriateness to overcome some matrix effects. [ABSTRACT FROM AUTHOR]

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal–phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50–500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques. [Display omitted] • A novel L-MPNs strategy was developed to facilitate labeling and separation of nanoplastics. • Formation of L-MPNs@NPs was validated by microscopic and spectroscopic measurements. • SERS approach allows detection of various sizes (50–500 nm) and types of nanoplastics with a LOD of 0.1 ppm. • Nanoplastics can be successfully detected into real environmental water systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • EPO combined with wavelength selection is an effective way to correct moisture in NIRS. • EPO combined with wavelength selection were more superior than using EPO alone. • Comparing to GA, Cars, PSO_CMW algorithm, EPO-siPLS has superior performance. The detection of maize starch content is of great significance for maize processing industry and near-infrared spectroscopy (NIRS) is an ideal rapid detection technology. However, the interference of moisture in maize is a bottleneck problem that affects the accuracy of NIRS quantitative analysis. In this study, we proposed methods based on external parameter orthogonalization (EPO) combined with wavelength selection algorithms to bring more accurate analytical results. Two groups of maize starch samples with different moisture content distributions were investigated to compare the predictive performance of NIRS models. The results showed that the model built using EPO combined with the synergy interval partial least squares (EPO-siPLS) algorithm exhibited the superior prediction accuracy, whose RMSEP/RMSEP ck is improved by 9.7 % compared with that of siPLS model, 25.3 % compared with that of EPO-PLS, and 45.8 % compared with that of the PLS model. This study provides a more accurate and robust new method for rapid detection of maize starch and offers new insights for its application. [ABSTRACT FROM AUTHOR]

[Display omitted] • Bisphenol A and its electron-withdrawing derivatives selected for research in biological applications. • Classical biomacromolecule human serum albumin used as biological model. • The affinity effects of bisphenol A derivatives were predicted by multiple methods. • The effect of electron cloud regulation on the bonding strength was analyzed by electron-withdrawing groups. • Providing a new methodology for biosafety studies of bisphenol A derivatives. Bisphenol A (BPA) is an environmental hormone with substantial physiological toxicity to the human body. Three electron-withdrawing derivatives of BPA are synthesized in this study to reduce its toxicity. The interaction mechanism between BPA and its three derivatives with human serum albumin (HSA) is investigated using molecular docking, electrochemistry, circular dichroism spectrum analysis, and fluorescence spectroscopy. Temperature-dependent tests and time-resolved fluorescence spectra reveal that all four compounds dynamically quench the internal fluorescence of HSA. Based on molecular docking and site competition outcomes, four compounds are primarily bound to site I's active pocket. Thermodynamic parameters indicate that the compounds' interaction with HSA is spontaneous, and introducing weak electron-withdrawing groups changes the action force. Circular dichroism and synchronous fluorescence measurements suggest four compounds impact HSA's structure. The substituents' electron attraction capacity determines their impact. Electrochemical studies examine the effect of electron-absorbing groups on the BPA and HSA binding capacity. Pharmacokinetics showed that nitro-substituted BPA may be a potential superior substitute for BPA. These results indicate crucial practical value, providing theoretical support for future research. [ABSTRACT FROM AUTHOR]

[Display omitted] • The optimum thickness of Sb 2 S 3 is 350 nm and for Sb 2 Se 3 is 760 nm. • The optimum metrics of tandem solar cell are: J sc = 16.32 mA/cm2, V oc = 1.48 V, FF = 60.7 %, PCE = 14.66 %. • The optimum acceptor density and bulk defect density in Sb 2 S 3 and Sb 2 Se 3 are: N A = 8.9 × 1015 cm−3 and B DD = 7.21 × 10−15 cm−3. • The optimized radiative recombination rate in Sb 2 S 3 and Sb 2 Se 3 layers are 0.73 × 10−10 cm3/s and 6.5 × 10−11 cm3/s, respectively. A device simulation presented for a tandem solar cell of Sb 2 S 3 and Sb 2 Se 3 as top (E g = 1.7 eV) and bottom (E g = 1.2 eV) absorber layers. We examined the device characteristics, radiative recombination, and optimum thickness of this tandem cell using filtered spectrum analysis and current-matching techniques in COMSOL. An open-circuit voltage of 1.58 V, current density of 15.50 mA/cm−2, fill factor of 56.90 %, and a remarkable efficiency of 14 %. The optimum thickness of Sb 2 S 3 is 350 nm and for Sb 2 Se 3 is 760 nm. Promising characteristics obtained with a J sc = 16.32 mA/cm2, V oc = 1.48 V, FF = 60.7 %, and an overall power conversion efficiency of 14.66 %. The optimum acceptor and bulk defect density have been calculated to be N A = 8.9 × 1015 cm−3 and B DD = 7.21 × 10−15 cm−3. The optimized values of radiative recombination rate in Sb 2 S 3 and Sb 2 Se 3 are 0.73 × 10−10 cm3/s and 6.5 × 10−11 cm3/s, respectively. [ABSTRACT FROM AUTHOR]

Developing efficient and stable blue-emitting phosphors has always been crucial for advancing full-spectrum WLED technology. In this study, the germanates K 2 MGeO 5 (M = Zr, Hf) were chosen as the host to develop novel NUV-excited blue-emitting phosphors. The crystal structure, electronic structure, and luminescence properties of K 2 MGeO 5 :Bi3+ were comprehensively investigated using X-ray powder diffraction, Rietveld refinement, photoluminescent spectra analysis, and density functional theory calculations. By integrating experimental data with semi-empirical formula calculations, the excitation and emission sources were elucidated. Furthermore, the influence of Bi3+'s local coordination environment on its luminescence performance and the concentration quenching mechanism in K 2 MGeO 5 :Bi3+ were thoroughly examined. A full-spectrum WLED was fabricated by synergistically combining K 2 ZrGeO 5 :Bi3+, commercially available green and red phosphors with a 365 nm LED chip. It is anticipated that this study could provide insights for the advancement of blue phosphors excited by near-ultraviolet light. • K 2 MGeO 5 :Bi3+ phosphors demonstrate excitation in the near-ultraviolet range and emits blue light. • A combined experimental and theoretical approach was utilized to elucidate the origin of excitation and emission. • A full-spectrum WLED was successfully achieved by utilizing K 2 ZrGeO 5 :Bi3+ as the blue component. [ABSTRACT FROM AUTHOR]

In this paper, we present the use of deep neural networks to estimate physical parameters from complex optical emission spectra of the D β /H β transition. Specifically, we focus on estimating the radio frequency electric field vector of the lower hybrid wave and isotope ratio within the scrape-off-layer plasma of the WEST tokamak. Fitting the spectral data using a traditional non-linear least squares analysis requires many free parameters and is computationally expensive, rendering the data unusable for real-time control. By implementing relatively small neural networks, the physical parameters can be directly extracted from the spectral data with reasonable accuracy in a few milliseconds. The deep neural network prediction can serve as input for a reduced model using least-squares fitting or for real-time control. We show that deep neural networks can be an effective tool for analyzing complex multicomponent spectra, providing a speedup of more than 1 0 5 times compared to least residual analysis, with an accuracy of 0.5% for the isotope ratio, and 0.09 kV/cm and 0.38 kV/cm for the RF radial and poloidal electric field respectively. • Deep Neural Network as surrogate model for multicomponent complex spectra analysis. • Principal component analysis applied to neural network dimensionality reduction on experimental spectra. • Estimation of the spectra parameters with high throughput. [ABSTRACT FROM AUTHOR]

One of the main challenges in solar tower renewable technologies is measurement of solar radiation attenuation at the plants at surface level. This paper describes an improved version of the optical spectrum analysis method for measuring solar radiation attenuation in real time at solar tower plants, as presented in a previous work. The new hardware design and calibration process are explained in detail. This new system has a resolution of 0.25 nm in the VIS range and a precision of 0.5% in real time, improving over the state of the art for the measurement of spectral atmospheric attenuation. These specifications allow the assessment of the contribution of different attenuation factors at surface level, such as absorbance peaks (Na, H, H 2 O) or scattering and the search for correlation with different weather conditions. They also enable experimental validation of atmospheric extinction simulation methods and their parameters. This work also includes the results of a 6 month-long campaign of solar weighted atmospheric extinction measurements at Atlantica's operating central receiver solar plant PS10 at Sanlúcar la Mayor (Seville, Spain). Fluctuations in the daily averaged transmittance greater than 10% are observed, which shows the importance of monitoring this parameter during the operation of solar plants. [ABSTRACT FROM AUTHOR]

• The structure of glass can be locally modified via platinum sphere migration. • Platinum nanoparticles were precipitated in the trajectories at low migration speeds. • The fictive temperature of glass increases with the migration velocity. In this study, metal spheres in glass were manipulated via heating using continuous-wave laser illumination. Metals are doped into the trajectory and selective compositional changes in the glass are observed. Meanwhile, the glass structure is modified via rapid heating and quenching. The structure of silica glass modified via platinum sphere migration was examined. Results of electron probe microanalysis confirm the presence of platinum in all trajectories, regardless of its low reactivity with silica glass. Elemental analysis reveals the precipitation of platinum nanoparticles in the trajectories at low migration speeds. Raman and infrared spectrum analyses reveal an increase in the fictive temperature, which increases with the migration velocity. Further, the etching rate increases with the sphere velocity. This study demonstrates that the structure of glass can be locally modified via platinum sphere migration, which depends on the sphere migration velocity. [ABSTRACT FROM AUTHOR]

Cr-doped monoclinic β-Ga 2 O 3 –7%In 2 O 3 single crystals were grown by the floating zone technique with radiation heating. The dark green color of the as-grown crystals transforms to light green upon crystals annealing in an oxygen atmosphere. Excitation spectra reveal characteristic Cr3+ bands in the visible spectral region and complex features in the UV region. Comparisons between as-grown and annealed crystals show variations in chromium excitation bands. UV or visible light irradiation induces intense Cr3+ luminescence in the red spectrum. The R 2 line diminishes at low temperatures, and the R 1 line dominates, exhibiting a blue shift compared to gallium oxide. Raman spectroscopy identifies phonon frequencies, revealing distinct modes associated with crystal lattice vibrations. The fine structure in the luminescence spectrum is attributed to vibronic transitions involving R lines and specific phonon modes. The R 1 line in β-Ga 2 O 3 –7%In 2 O 3 single crystals has a larger FWHM than in β-Ga 2 O 3. Decomposition of R 1 -line reveals inhomogeneous broadening, with Gaussian fits indicating several types of Cr3+ centers, attributed to the octahedrally-coordinated Ga- and In positions, as well as is sensitive to oxygen non-stoichiometry. Photoluminescence decay kinetics measured at 695 nm (R 1 (Ga)-line) have a single-exponential decay at lower temperatures with a lifetime of 2.8 ms at 4.5 K. Temperature dependence of lifetime for the studied crystals is consistent with the previously studied β-Ga 2 O 3 :Cr and confirms an application potential of the material for low-temperature non-contact luminescence thermometry and light sources in deep red or near-IR spectral region. • Cr-doped β-Ga 2 O 3 –7%In 2 O 3 crystals grown by the floating zone technique have been characterized. • The temperature dependences of the photoluminescence spectra of Cr3+ ions were studied. • R 2 line diminishes at low temps and R 1 line dominates, exhibiting blue shift compared to pure β-Ga 2 O 3. • Luminescence spectrum analysis reveals several types of Cr3+ centres. • Photoluminescence decay study at 695 nm suggests potential for low-temperature thermometry. [ABSTRACT FROM AUTHOR]

[Display omitted] • Both polyphenol oxidase and β-glucosidase were involved in VBP formation. • Vaccinoside played as a unique bifunctional precursor to form VBPs. • 15 Amino acids helped to give VBPs (λmax 581–590 nm) of different hues. • Two synthesis pathways were proposed to interpret formation of VBPs. Since Tang dynasty in China, the fresh leaves of Vaccinium bracteatum (VBL) have been applied as natural pigment to produce black rice. However, detailed information on its biosynthetic mechanism still remained unclear. Following rice dyeing capacity assay, vaccinoside, one of iridoid glycosides, was identified as the key active compound. Increased methodical research demonstrated vaccinoside as a distinct bifunctional precursor, which could be catalyzed by polyphenol oxidase or β-glucosidase independently, followed by reaction with 15 amino acids to give blue pigments (VBPs; λmax 581–590 nm) of different hues. Two synthetic pathways of VBPs were proposed, using multiple techniques such as HPLC, HPSEC, UV–Vis spectrum and colorimeter as analysis tools. Black rice was interpreted to be prepared by cooking, using vaccinoside, intrinsic enzymes from fresh VBL and rice protein in combination. These findings promote the understanding of VBP formation mechanisms and provide an efficient method of producing novel Vaccinium blue pigments. [ABSTRACT FROM AUTHOR]

Methods to objectively assess fruit and vegetable (FV) intake in young children are needed in order to support rigorous assessments of policies and interventions. Noninvasive skin carotenoid concentration measurements may provide a rapid assessment of toddler carotenoid and carotenoid-rich FV intake. The aim of this study was to evaluate the relationship between pressure-mediated reflection spectroscopy-measured skin carotenoid score (SCS) with proxy-reported carotenoid and FV intake in racially and ethnically diverse US toddlers. This study was a secondary analysis of data obtained from a randomized controlled 10-week study of the effect of an interactive healthy playgroup intervention vs classroom parent education on the diet and physical activity of toddlers. This study collected skin carotenoid and 1-week dietary intake using a 31-item semi-quantitative food frequency questionnaire analyzed by the Nutrient Data System for Research nutrient database. The current study determined dietary predictors of toddler SCS. Participants were racially and ethnically diverse US toddlers (12 to 36 months) and adult guardian dyads (n = 50) recruited from the community in Houston, TX from fall 2018 to spring 2019. At baseline and 10 to 12 weeks after baseline, SCS was measured by means of pressure-mediated reflection spectroscopy (Veggie Meter, Longevity Link Corporation), guardians reported toddler diet using a food frequency questionnaire, and carotenoid intake was estimated from the food frequency questionnaire responses using a nutrient database. The relationship between toddler SCS and intake of total and individual carotenoid species and FV servings was tested using generalized linear mixed models, controlling for body mass index-for-age percentiles, group assignment, and age. SCS was positively and significantly predicted by estimated intakes of total carotenoids (P =.002), β-carotene (P ≤.001), and lutein and zeaxanthin (P =.003). Reported intakes of α-carotene, β-cryptoxanthin, and lycopene were not predictors of SCS. SCS was predicted by estimated total FV intake (P =.047) and vegetable intake (P =.006), but not fruit intake (P =.580). These results showed that reported dietary carotenoid intake is a significant predictor of SCS in an ethnically and racially diverse population of US toddlers. Toddler skin carotenoid measurement holds promise as a rapid, objective, noninvasive biomarker of dietary carotenoid intake. [ABSTRACT FROM AUTHOR]

We have developed a new position-sensitive optical fiber radiation sensor that achieves single-end readout and high dose rate application. The sensor determines the incident position of radiation on the optical fiber by using the wavelength dependence of light attenuation within the fiber. Through analysis of the wavelength spectrum output from the fiber end, the incident position of radiation on the optical fiber can be inversely estimated via spectrum unfolding. Using this optical fiber sensor, we measured the radiation distribution inside the Fukushima Daiichi Nuclear Power Station (FDNPS). The actual trend of the incident position of radiation was successfully reproduced in a high dose rate area, with the maximum dose rate exceeding 100 mSv/h. This validates the effectiveness of our new position-sensitive optical fiber radiation sensor. [ABSTRACT FROM AUTHOR]

A chirp cyclostationary (CCS) process is a nonstationary stochastic process, whose statistics have been defined and utilized in radar and communication signal processing. However, spectrum analysis of CCS signals, which provides a spectral view to characterize a signal, has not been performed. Classical spectrum analysis is based on the Fourier transform, which is not suitable for CCS signals because of the multiplicative chirp signals in a CCS model. In this study, we propose a generalized spectral representation of chirp cyclostationary signals associated with a linear canonical transform. The proposed representation shows that a CCS signal can be represented by a linear combination of a series of jointly stationary and equal-bandwidth processes, which bridge the nonstationary and stationary processes. Furthermore, the relationships between the second-order statistics of the CCS process and its stationary representations are introduced. Finally, based on the above observations, a linear time-varying Wiener filter was designed for CCS signal denoising and time-varying channel estimation. Finally, the relationships between the nonstationarity of the input and output and time-varying properties of the systems are discussed, which are helpful for determining the nonstationarity of the outputs or the time-varying property of a system. • A generalized spectral decomposition of chirp cyclostationary processes is proposed. • The CCS process is proven as a linear combination of joint stationary processes. • Statistics of the CCS process are linked with those of the stationary components. • A linear chirp periodically time-varying chirp cyclic Wiener filter is designed. [ABSTRACT FROM AUTHOR]

Melodinus axillaris W.T.Wang has been widely used as an important medicine in China. In the folk of China, its whole plant has been used for fractures, rheumatic heart disease, testitis, hernia, abdominal pain, and dyspepsia, etc. Despite its extensive use, there is a shortage of literature investigating the specific bioactive compounds and underlying mechanisms responsible for their anti-inflammatory effects. This knowledge gap serves as the primary impetus for conducting this study, which aims to shed light on the previously unexplored therapeutic potential of M. axillaris. This study aims to investigate the material basis and potential mechanism of anti-inflammatory activity of M. axillaris. Compounds were isolated from the 95% ethanol extract of M. axillaris using a systematic phytochemical method. The structures were established by extensive spectroscopic analysis, including 1D and 2D NMR, HR-ESI-MS, ECD calculation, and DP4+ analysis. The anti-inflammatory activities of ethanol extract and compounds from M. axillaris were tested by an inflammation model of LPS-stimulated RAW264.7 cells in vitro. Western blot analysis was employed to evaluate the expressions of COX-2, iNOS, and NF-κB signaling pathways, aiming to elucidate the underlying mechanisms. Eleven undescribed monoterpenoid indole alkaloids (MIAs), axillines A−K (1 – 11), along with thirteen known analogs were isolated from M. axillaris. Compound 1 was the first representative of vincadine alkaloid with unprecedented 6/5/9/6/6 skeletons. Compounds 1 – 11 and ethanol extract showed significant anti-inflammatory effects in vitro. Among them, compound 2 had the best activity of inhibiting NO release (IC 50 = 3.7 ± 0.9 μM). Additionally, subsequent Western blot analysis revealed that 2 could significantly inhibit the up-regulation of NF-κB signaling pathways, iNOS, and COX-2 in LPS-stimulated RAW264.7 cells, thereby demonstrating its anti-inflammatory activity. This study provides support for the traditional use of M. axillaris in terms of its anti-inflammatory properties and highlights the potential of MIAs as promising candidates for further development as anti-inflammatory drugs. [Display omitted] • Eleven undescribed monoterpenoid indole alkaloids (MIAs) were isolated from M. axillaris. • Compound 1 was the first representative of vincadine alkaloid with 6/5/9/6/6 skeletons. • These MIAs were isolated exhibited significant anti-inflammation activity. • Compound 2 inhibited inflammation by NF-κB signaling pathway. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel Alk-MXenes based composite was successfully fabricated. • Au(III)/Cr(VI) could be efficient reduced to Au(0)/Cr(III) by Fe(II) and S(-II) • Increase in pH and salinity hindered Au(III)/Cr(VI) adsorption-reduction. • The Fe 3 S 4 and Alk-Nb 2 CT x exhibited synergistic effects for Au(III)/Cr(VI) removal. Herein, Fe 3 S 4 particles were introduced into an alkalized-Nb 2 CT x MXenes to construct Fe 3 S 4 @Alk-Nb 2 CT x composite for simultaneous reduction-immobilization of Au(III)/Cr(VI) from water aqueous. Spectrum analysis revealed that the –OH groups on the Alk-Nb 2 CT x surface assisted improving the dispersion and stability of Fe 3 S 4 , resulting in a favorable morphology and structure. The synthesized composites exhibited superior adsorptive property with a maximum adsorption values for Au(III) (2544.3 mg/g) and Cr(VI) (204.8 mg/g). Meanwhile, the removal of targeted pollutants on Fe 3 S 4 @Alk-Nb 2 CT x followed Pseudo-second order kinetics model and showed a good fit with the Langmuir isotherm model, indicating the nature of monolayer chemisorption. Besides, high adsorption selectivity of Fe 3 S 4 @Alk-Nb 2 CT x was still observed in the presence of interference ions, and it could be separated conveniently from solution by a magnet. More importantly, the model-fitting and characterization results manifested that high-density Fe, S and O groups were the main active factors in the as-prepared adsorbents, while the electrostatic attraction, complexation, redox and precipitation dominated the adsorption process. Hence, Fe 3 S 4 @Alk-Nb 2 CT x was a promising candidate employed for in situ environmental pollution incidents, especially competent for the reduction and removal of Au(III)/Cr(VI). [ABSTRACT FROM AUTHOR]

• The structure of frequency-shifted delay loop is introduced to generate the multi-frequency probe pulse train. • The amount of data computation is reduced by adopting the piecewise aggregation approximate (PAA) method. • The first study to achieve fading recognition based on support vector machine (SVM). In order to suppress the interference fading of phase-sensitive optical time domain reflectometer (Φ-OTDR), a multi-frequency detection method based on frequency-shifted delay loop (FSDL) is proposed. A probe pulse train with up to five consistent frequency components are generated by periodic frequency-shifted, amplification, delay and filtering processing in FSDL. The piecewise aggregate approximation (PAA) is introduced to compress the amount of operational data. Wavelet energy spectrum analysis and support vector machine (SVM) are used to extract features and realize the fading classification. With the help of fading label making and restoration, the multi-frequency signals are intelligently aggregated using rotated-vector-sum (RVS). Experimental results show that PAA has applicability in data compression of beat signals. After 5-layer wavelet energy spectrum analysis, the fading binary classification accuracy can reach 96.77 %, and the fading signals identified after segmentation can be restored to the original data. The fading probability based on SVM output labels can be reduced to 1.89 %. The SVM-based classification output labels aggregation shows that the vibration positioning signal-to-noise ratio (SNR) can be increased to 13.52 dB, the phase demodulation curve is smoother, and the demodulation SNR can be up to 17.63 dB. Finally, the R-Square of 0.997 for the amplitude of demodulated vibration signal in repeatability experiment verifies the validity of this effective scheme for fading recognition and suppression. [ABSTRACT FROM AUTHOR]

[Display omitted] • Design a novel automatic detection system for cobalt ions. • Propose an effective spectral preprocessing algorithm. • Apply five full wavelength modeling methods on the system. Cobalt ion is an impurity that has a negative effect in zinc hydrometallurgy, resulting in lower zinc yield and quality. Currently, the zinc hydrometallurgy industry typically uses manual sampling followed by manual sample preparation, and single-wavelength spectral analysis to detect cobalt ions in zinc solution, which is inefficient and lacks accuracy. Therefore, a new automatic detection system for cobalt ions concentration is developed. The system effectively overcomes challenges of pipeline blockage and corrosion by innovatively implementing negative pressure extraction, volume quantification, and split pipeline structure. Compared with manual detection, the system has higher detection repeatability and efficiency, specifically reducing reagent consumption by 70 %, and improving the detection speed by 8 times. In addition, to solve the spectral drift and noise problems, a spectral preprocessing algorithm by forced contraction of long-wavelength region spectra and Gaussian filtering is proposed. This algorithm not only improves the local linearity and regression accuracy of the spectrum, but also improves the detection repeatability of the system. Finally, five full-wavelength modeling methods are applied to the system. The best root mean square error for low concentration (0.1 to 1 mg/L) and high concentration (1 to 20 mg/L) cobalt zinc solution is only 0.0027 mg/L and 0.071 mg/L, respectively. [ABSTRACT FROM AUTHOR]

This paper establishes the concept of the multi-degree-of-freedom (MDOF) response spectrum as a means for the rapid determination of the peak response of a building structure. The MDOF response spectrum is constructed using the peak response results derived by linear modal analyses, it is specific per type of structure and it retains the usual representation characteristics of its single-degree-of-freedom (SDOF) counterpart, i.e., the horizontal axis displays the fundamental period of the MDOF structure, whereas in the vertical axis the peak seismic response quantity of interest (acceleration, velocity, displacement) is provided. Elastic and inelastic versions of the MDOF spectrum are developed with the aid of modal damping ratios. Especially, for the inelastic version of the MDOF spectrum, deformation-dependent equivalent modal damping ratios that account for predetermined inelastic seismic performance levels are utilized. Being defined directly for MDOF structures, the MDOF response spectrum renders the modal response spectrum analysis, i.e., the peak response determination using the first few significant modes of vibration from the standard SDOF spectra in conjunction with the application of a modal combination rule, redundant. • The concept of the MDOF response spectrum is established. • The MDOF response spectrum is constructed using the peak response results derived by linear modal analyses. • The MDOF response spectrum is specific per type of structure and can be defined for elastic and inelastic structures. • The MDOF response spectrum renders the application of modal response spectrum analysis redundant. [ABSTRACT FROM AUTHOR]

The effectiveness of the conventional friction pendulum isolator (FPI) is limited in complex geographical environments and unpredictable earthquake events due to its complex frictional properties and the requirement for a unified setup target. With a view to addressing the aforementioned issues, in conjunction with an adaptive variable friction pendulum isolator (AVFPI), a simple and practical mechanical model is proposed. After applying the mechanical model with a friction-dependent influence model, an improved response spectrum analysis procedure (IRS) is proposed for variable friction pendulum isolation systems. Notably, the proposed procedure allows for the consideration of the effects of variations in velocity, temperature, and pressure on the friction characteristics without the necessity for nonlinear response history analysis (NRHA). The procedure commences with obtaining a numerical model of friction dependency through friction material examinations, then proceeds to verifying the reliability of both the friction dependency and mechanical model through prototype tests of AVFPIs. The following study presents a proposed correction method that depends on random vibration theory to establish a functional relationship between the pseudo-velocity spectrum and the velocity spectrum. Additionally, an association is established between the peak velocity and the generation of frictional heat. Finally, the procedure is evaluated based on the results of an NRHA that takes friction dependence into account through a numerically variable friction pendulum isolation system. The results of the study indicate that the IRS provides a more accurate and secure assessment of the isolator displacement at various temperatures than the response spectrum method, which does not account for the influence of frictional dependency. The failure to consider the influence of friction dependency in high-temperature environments produces an underestimation of isolator slip displacement and a subsequent increase in failure rates. The Polytetrafluoroethylene (PTFE) friction materials that are currently in widespread use exhibit a strong correlation with friction dependence and, as a consequence, cause relatively large displacements at temperatures that are both low and high. The results of this study present an opportunity to expand how response spectrum analysis techniques can be applied to friction pendulum isolation systems. • A simplified mechanical hysteresis model for adaptive variable friction pendulum isolators is proposed. • A new friction material was tested and the velocity, pressure stress and temperature dependence expressions were obtained for the new friction material. • An expression for the friction coefficient of an adaptive variable friction pendulum isolator that takes into account the effects of velocity, pressure stress, and temperature dependence during nonlinear response history analysis is presented. • An improved method for analysing the response spectrum of variable friction pendulum isolation systems is proposed. Notably, the proposed procedure allows the consideration of the effects of velocity, temperature and pressure variations on the friction characteristics without the necessity to proceed to a nonlinear response history analysis (NRHA). • In the improved method of response spectrum analysis of variable friction pendulum isolation system, based on the correction method of stochastic vibration theory, the functional relationship between the pseudo velocity spectrum and the velocity spectrum is established, and a simplified calculation method for calculating frictional heat by peak velocity response is proposed. [ABSTRACT FROM AUTHOR]

• A peridynamic bond fatigue model is proposed based on Walker's law. • The new model reflects the influence of stress ratio on crack growth rate. • The model is validated via crack growth analysis under spectrum loadings. • Fatigue behaviors under different random loadings were reproduced. Engineering structures usually bear cyclic loads with varying amplitude in serving conditions, and thus, fatigue crack propagation analysis, which accounts for spectrum loadings, plays an important role in structural design. This paper presents a novel numerical approach to crack propagation analysis in structures bearing spectrum loadings based on peridynamic (PD) theory. PD model is introduced to deal with the displacement discontinuity across damage and crack. Because the stress ratio has an innegligible influence on crack growth rate in many circumstances, a new PD bond fatigue criterion based on Walker's law is proposed to address this influence. Then, the numerical implementation of discretization and the computational methods applied for solving the PD fatigue model are introduced. The model is verified by comparing the numerical crack propagation with the corresponding analytical solution for a bi-axial loaded fatigue case and validated by compact tensile experiments under random loadings. The results demonstrated the accuracy of the proposed PD fatigue model for structural crack propagation analysis under spectrum loadings. Furthermore, a numerical example of fatigue crack growth in a two-phase material with irregular interfaces is simulated by using the new model to demonstrate the model's feasibility. [ABSTRACT FROM AUTHOR]

Photonic Crystals (PhCs) are materials with a periodic arrangement of dielectric or metallic components that can manipulate the flow of photons. Conventional techniques for computing the spectrum response of these artificial structures are time-consuming, laborious, and susceptible to human errors. This paper presents a novel approach incorporating Machine Learning (ML) in forming PhC-based periodic structures. The structures are designed from the Two-Dimensional (2D) PhCs having air holes in a dielectric material. These crystalline structures work on the Guided Mode Resonance (GMR) principle and find their use in numerous applications, including optical filters in Near Infrared Range (NIR). However, the conventional methods for analyzing the output spectra of PhCs need to be revised due to the complexities in designing compound optical filters. Therefore, an automated process employing ML is required. As a result, in our work, we form 2D crystalline structures using the Finite-Difference Time Domain (FDTD) method and predict various spectral responses of PhCs via ML-based linear regression. The proposed mathematical models provide efficient results and considerably less simulation efforts and time compared to the traditional manual methods. • Photonic Crystals (PhCs) utilize dielectric/metallic elements to control photon behavior, vital for NIR optical filters. • Traditional PhC spectrum analysis methods are often slow and prone to errors, complicating optical filter design. • This study introduces a novel 2D PhC design method combining Machine Learning and FDTD, enhancing efficiency. • Innovations include: dielectric use in PhCs, ML-driven design, automation, resonant mode mathematical modeling, and accuracy validation. • Utilizes Guided Mode Resonance for accurate PhC spectrum response prediction, essential for optimal performance. • ML-based linear regression significantly enhances spectrum prediction efficiency, reducing simulation efforts and time. [ABSTRACT FROM AUTHOR]

Due to technological advancements, wind energy has emerged as a prominent renewable power source. However, the intermittent nature of wind poses challenges in accurately predicting wind speeds, affecting the operation of electric systems. With the Brazilian electricity market transition to hourly electricity pricing, there is a growing need for forecasting tools to enhance wind farm operation and maintenance schedules. To address this issue, this research explores the performance of forecasting models enhanced with a decomposition stage to mitigate wind speed forecast errors. The study considers two decomposition techniques: singular spectral analysis in the time domain and variational mode decomposition in the frequency domain, combined in a hybrid structure incorporating multi-stage decomposition and time series prediction. The study focuses on hourly forecasting horizons of 24, 48, and 72 steps ahead. The autoregressive recurrent neural network achieved a MAPE of 10.92% utilizing decomposition for the 72-hour forecast from January to December 2015, this represents a 51.16% improvement compared to the original structure. The outcomes of all the assessed models employing decomposition demonstrate a decrease in error in comparison to those without decomposition, thereby confirming the potential of hybrid architectures. Forecasting approaches can contribute to improved wind farm operation planning and maintenance scheduling. • Singular spectral analysis combined with variational mode decomposition. • Time and frequency domains for feature extraction in a hybrid structure. • Multi-stage decomposition to mitigate wind speed forecast errors. [ABSTRACT FROM AUTHOR]

• This study showed the first experimental NMPC implementation in a roller compactor. • The bimodal size distribution of granules can be controlled using NMPC. • Bimodal Weibull distribution can be used to describe the granule size distribution. • A novel NIR spectra analysis approach was used to measure ribbon solid fraction. • A hybrid model is developed to integrate roll compaction and ribbon milling processes. This study focuses on the development of a hybrid model to integrate roll compaction and ribbon milling operations to design and control a continuous dry granulation process. The proposed hybrid model has three features: (1) it compensates for underestimated roll gap measurements with knurled rolls, (2) it represents the bimodal size distribution of granules using five fitting parameters of the bimodal Weibull distribution instead of only using specific size percentiles, and (3) it considers the impact of rotor-screen gaps on granules. Furthermore, the hybrid model facilitates the implementation of nonlinear model predictive control in a roller compactor Alexanderwerk WP120. Compared to widely applied open-loop operations in the pharmaceutical industry, nonlinear model predictive control demonstrates better performance, indicated by lower integral absolute errors in controlling mass throughput and ribbon solid fraction, in which real-time measurements can be obtained using a near-infrared sensor and a novel spectra selection approach. [ABSTRACT FROM AUTHOR]

[Display omitted] • α-Amylase exhibited variances release patterns on different aroma compounds. • Umami perception significantly decreased along with the addition amount of α-amylase. • Static quenching with spontaneous interaction was the main quenching mechanism. • Hydrogen and hydrophobic bonding interactions were the dominant. • Eight key amino acid residues in α-amylase interacted with the flavor compounds. The effects of α-amylase on of flavor perception were investigated via spectrum analysis, electronic tongue, on-line mass spectrometry, and molecular docking. Aroma release results showed that α-amylase exhibited variable release patterns of different aroma compounds. Electronic tongue analysis showed that the perception of bitterness, sweetness, sour, and saltiness was subtly increased and that of umami was significantly increased (p < 0.01) along with the increasing enzyme activity of α-amylase. Ultraviolet absorption and fluorescence spectroscopy analyses showed that static quenching occurred between α-amylase and eight flavor compounds and their interaction effects were spontaneous. One binding pocket was confirmed between the α-amylase and flavor compounds, and molecular docking simulation results showed that the hydrogen, electrostatic, and hydrophobic bonds were the main force interactions. The TYP82, TRP83, LEU173, HIS80, HIS122, ASP297, ASP206, and ARG344 were the key α-amylase amino acid residues that interacted with the eight flavor compounds. [ABSTRACT FROM AUTHOR]

An undescribed trichodenone derivative (1), two new diketopiperazines (3 and 4) along with a bisabolane analog (2) were isolated from Trichoderma hamatum b-3. The structures of the new findings were established through comprehensive analyses of spectral evidences in HRESIMS, 1D and 2D NMR, Marfey's analysis as well as comparisons of ECD. The absolute configuration of 2 was unambiguously confirmed by NMR, ECD calculation and Mo 2 (AcO) 4 induced circular dichroism. Compounds 1 – 4 were tested for their fungicidal effects against eight crop pathogenic fungi, among which 1 showed 51% inhibition against Sclerotinia sclerotiorum at a concentration of 50 μg/mL. [Display omitted] • Three previously undescribed compounds were isolated form Trichoderma hamatum b-3. • The absolute configurations of all the isolated compounds were elucidated. • 1 showed 51% inhibition against Sclerotinia sclerotiorum at a concentration of 50 μg/mL. [ABSTRACT FROM AUTHOR]

Diabetes mellitus stands as a metabolic ailment marked by heightened blood glucose levels due to inadequate insulin secretion. The primary aims of this investigative inquiry encompassed the isolation of phytochemical components from the bark of Kopsia teoi , followed by the assessment of their α-amylase inhibition. The phytochemical composition of the K. teoi culminated in the discovery of a pair of new indole alkaloids; which are 16- epi -deacetylakuammiline N (4)-methylene chloride (akuammiline) (1), and N (1)-methoxycarbonyl-11-methoxy-12-hydroxy-Δ14–17-kopsinine (aspidofractinine) (2), together with five known compounds i.e. kopsiloscine G (aspidofractinine) (3), akuammidine (sarpagine) (4), leuconolam (aspidosperma) (5), N -methoxycarbonyl-12-methoxy-Δ16, 17-kopsinine (aspidofractinine) (6), and kopsininate (aspidofractinine) (7). All compounds were determined via spectroscopic analyses. The in vitro evaluation against α-amylase showed good inhibitory activities for compounds 5 – 7 with the inhibitory concentration (IC 50) values of 21.7 ± 1.2, 34.1 ± 0.1, and 30.0 ± 0.8 μM, respectively compared with the reference acarbose (IC 50 = 34.4 ± 0.1 μM). The molecular docking outputs underscored the binding interactions of compounds 5 – 7 ranging from −8.1 to −8.8 kcal/mol with the binding sites of α-amylase. Consequently, the outcomes highlighted the anti-hyperglycemic attributes of isolates from K. teoi. [Display omitted] [ABSTRACT FROM AUTHOR]

Five new sesquiterpenoids, dictamtrinorguaianols E and F (1–2), and dictameudesmnosides F, G, and H (3–5), along with seven known sesquiterpenoids (6–12) were isolated from Dictamnus dasycarpus Turcz. The structures of all new compounds were characterized by spectroscopic methods, including UV, IR, HR-ESI-MS, and 1D and 2D NMR. The In-vitro anti-proliferative activities of all the compounds against two human cancer cell lines (SW982 and A549) were evaluated by CCK-8 assay. Compounds 1 and 4 showed medium anti-proliferative activity against SW982 cells, with IC 50 values of 3.49 ± 0.10 and 6.42 ± 1.23 μM, respectively. Additionally, compounds 2 , 7 , and 8 exhibited medium anti-proliferative activity against A549 cells, with IC50 values ranging from 0.80 ± 0.05 to 6.60 ± 0.46 μM. [Display omitted] [ABSTRACT FROM AUTHOR]

Phytochemical study on the roots of a medicinal plant Ferula communis L. (Apiaceae) resulted in the isolation of 20 sesquiterpenes including 12 previously undescribed compounds, dauferulins A–L (1 − 12). The detailed spectroscopic analysis revealed 1 – 12 to be daucane-type sesquiterpenes with a p -methoxybenzoyloxy group at C-6. The absolute configurations of 1 – 12 were deduced by analysis of the ECD spectra. Dauferulins A–L (1 – 12), known sesquiterpenes (13 − 20), and analogues (14a – 14l) derived from 6- O - p -methoxybenzoyl-10α-angeloyloxy-jeaschkeanadiol (14) were evaluated for their effects on AMPK phosphorylation in human hepatoma HepG2 cells as well as inhibitory activities against erastin-induced ferroptosis on human hepatoma Hep3B cells and IL-1β production from LPS-treated murine microglial cells. [Display omitted] • The roots of Ferula communis L. were investigated to isolate 20 sesquiterpenes. • Among them, dauferulins A–L were assigned as new daucane-type sesquiterpenes. • Their structures were elucidated by spectroscopic analysis. • Daucane-type sesquiterpenes and their analogues were evaluated for effects on AMPK phosphorylation. • Their anti-ferroptosis anti-neuroinflammatory activities were also assessed. [ABSTRACT FROM AUTHOR]

Nine polyacetylenes, including five new compounds named sadivaethynes E -I (1 – 5), were isolated from the roots of Saposhnikovia divaricata. Structural elucidation of compounds 1 – 5 was established by extensive spectroscopic analysis, quantum chemical calculations and DP4+ probability analysis. Among them, the absolute configuration of compound 1 – 2 , 4 – 5 was unambiguous determined by ECD. Also, all compounds were evaluated for cytotoxicity against two human cancer cell lines (A549, HEPG2) in vitro, compound 9 showed moderate inhibitory effect with an IC 50 value of 11.66 μM against HEPG2. [Display omitted] • Five undescribed compounds were isolated from the roots of Saposhnikovia divaricata. • The structures were characterized chemically by NMR, quantum chemical calculations and CD data analysis. • Compound 9 showed moderate inhibitory effect with an IC 50 value of 11.66 μM against HEPG2. [ABSTRACT FROM AUTHOR]

The concept of multi-target-directed ligands offers fresh perspectives for the creation of brand-new Alzheimer's disease medications. To explore their potential as multi-targeted anti-Alzheimer's drugs, eighteen new bakuchiol derivatives were designed, synthesized, and evaluated. The structures of the new compounds were elucidated by IR, NMR, and HRMS. Eighteen compounds were assayed for acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) in vitro using Ellman's method. It was shown that most of the compounds inhibited AChE and BuChE to varying degrees, but the inhibitory effect on AChE was relatively strong, with fourteen compounds showing inhibition of >50% at the concentration of 200 μM. Among them, compound 3g (IC 50 = 32.07 ± 2.00 μM) and compound 3n (IC 50 = 34.78 ± 0.34 μM) showed potent AChE inhibitory activities. Molecular docking studies and molecular dynamics simulation showed that compound 3g interacts with key amino acids at the catalytically active site (CAS) and peripheral anionic site (PAS) of acetylcholinesterase and binds stably to acetylcholinesterase. On the other hand, compounds 3n and 3q significantly reduced the pro-inflammatory cytokines TNF-α and IL-6 released from LPS-induced RAW 264.7 macrophages. Compound 3n possessed both anti-acetylcholinesterase activity and anti-inflammatory properties. Therefore, an in-depth study of compound 3n is expected to be a multi-targeted anti-AD drug. [Display omitted] • Design and synthesis of 18 bakuchiol derivatives. • The new compounds were evaluated for cholinesterase inhibitory activity and anti-inflammatory activity. • Compound 3n has anti-acetylcholinesterase activity and anti-inflammatory activity. • Molecular docking and molecular dynamics simulations study of compounds 3g and 3n indicated that it interacted with both CAS and PAS. [ABSTRACT FROM AUTHOR]

Angiotensin I-converting enzyme (ACE) inhibition is currently a common method for the treatment and control of hypertension. In this study, four new (1–4) and one known (5) cycloartane triterpenoids were isolated from the leaves of Swietenia macrophylla by chromatographic techniques and identified by their spectroscopic data and a comprehensive comparison of published data. The triterpenoids were evaluated for their ACE inhibitory potential using in vitro inhibition assays and in silico methods. The inhibition assay and enzyme kinetics results showed that the most active triterpenoid, compound 4 , inhibited ACE in a mixed-type manner with an IC 50 value of 57.7 ± 6.07 μM. Computer simulations revealed that compound 4 reduces the catalytic efficiency of ACE by competitive insertion into the active pocket blocking the substrate, and the binding activity occurs mainly through hydrogen bonds and hydrophobic interactions. The study showed that S. macrophylla can be a source of bioactive material and the ACE inhibitory triterpenoid could be a potential antihypertensive agent. [Display omitted] • Four new cycloartane triterpenoids were isolated from Swietenia macrophylla. • 3β,16β-dihydroxy-29-norcycloartan-24-one (4) inhibited ACE in a mixed-type manner. • Hydrogenation at C-16 and substitution by the carbonyl group at C-24 enhanced the ACE inhibitory activity of the triterpenoids. • Computational simulation analyses showed that hydrogen bonds were the major binding forces. [ABSTRACT FROM AUTHOR]

Phytochemical studies on the leaves and twigs of Hypericum ascyron Linn. led to the isolation of two previously undescribed rearranged polycyclic polyprenylated acylphloroglucinols (PPAP) with a 4,5- seco -3(2H)-furanone skeleton, named hyperascone A and B (1 – 2). Additionally, a known PPAP tomoeone A (3) and two known xanthones 1,3,5 -trihydroxy-6- O -prenylxanthone (4) and 3,7-dihydroxy-1,6-dimethoxyxanthone (5) were also isolated. The structures of the compounds were determined by the analysis of their spectroscopic data including HRMS, NMR and ECD. All of the five isolated compounds exhibited neuroprotective effects against MPP+ and microglia activation induced damage of SH-SY5Y cells. [Display omitted] • Two new rearranged polycyclic polyprenylated acylphloroglucinols (PPAP) were isolated from Hypericum ascyron. • A possible biosynthetic pathway is proposed based on the Bayer-Villiger reaction. • Some of the compounds showed moderate protective effects against MPP+-induced cell damage. [ABSTRACT FROM AUTHOR]

In this research, five new indolequinazoline alkaloids (1 – 5), along with six known indolequinazoline alkaloids (6 – 11) were obtained from the fruits of Tetradium ruticarpum. Their structures were elucidated through comprehensive spectroscopic data of 1D and 2D NMR, HRESIMS and ECD spectra. Additionally, all isolates were assayed for their SIRT1 inhibitory activities in vitro and compounds 2 , 7 , 10 and 11 exhibited activities with IC 50 values ranged from 43.16 to 118.35 μM. Eleven indolequinazoline alkaloids, including five undescribed compounds, were isolated from the fruits of Tetradium ruticarpum and their SIRT1 inhibitory activities were assessed. [Display omitted] [ABSTRACT FROM AUTHOR]

Aster tataricus L.f. is highly valued for its rich reserves of bioactive compounds. Our research focused on the identification of previously unreported compounds found within the ethanol extract of A. tataricus. Through meticulous spectroscopic analyses and computational methods like NMR calculations and ECD, we successfully elucidated the structures of five novel compounds termed tatarisides A-E (1–5), alongside two known compounds (6, 7). The anti-inflammatory assays conducted yielded noteworthy results, particularly in relation to compounds 1 and 5. These compounds exhibited significant potential in inhibiting the release of NO in LPS-induced RAW 264.7 cells, as evidenced by their respective IC 50 values of 17.81 ± 1.25 μM and 13.32 ± 0.84 μM. The discovery of these new compounds adds to the existing knowledge of A. tataricus 's chemical composition and potential applications. [Display omitted] [ABSTRACT FROM AUTHOR]

• Combing GTCH with BMA method to fuse multi-source GRACE datasets. • Obtaining the accurate shallow and deep GWS estimations in the NCP. • Using HSA method to quantify the contribution of human and natural factors. The North China Plain (NCP) is a critical agricultural hub in China, confronting a significant issue of groundwater depletion. However, different terrestrial water storage (TWS) change products from the Gravity Recovery and Climate Experiment (GRACE) satellites differ considerably in estimating groundwater depletion rates in the NCP. It is urgent to optimize these different products to obtain an elevated understanding of regional groundwater storage (GWS) changes. The generalized three-cornered hat (GTCH) method is used to quantify uncertainties of different GRACE products, and this prior information is integrated with the Bayesian model averaging (BMA) method to fuse GRACE products. Results demonstrate that the GTCH + BMA method can generate uniform GWS products with heightened precision, enhanced coherence, and diminished uncertainty in the NCP. After that, the shallow and deep GWS are meticulously differentiated based on the high-coverage in-situ data, and the shallow GWS (2005.1–2016.8) (-13.7 ± 4.6 mm/yr) declined faster than deep GWS (-6.05 ± 3.9 mm/yr) in the NCP. To further explore the primary factors driving these changes, the latest Hankel Spectrum Analysis (HSA) method combined with ridge regression simulation is employed to decouple the change components of human and natural factors in the shallow and deep GWS. The first attempt to give the contribution of human and natural factors to shallow GWS is 77.18 %/22.82 %, and to deep GWS is 87.59 %/12.41 %. [ABSTRACT FROM AUTHOR]

• Birefringent wedge-based Fourier transform (FT) spectrometer for low-light measurement. • Optimized optical path and data acquisition for the uniqueness of FT spectroscopy. • Comprehensive FT Raman spectrum analysis and noise characterization. • High efficiency and accuracy advantages originating directly from the FT spectrometer system. • A stable, compact, low-cost, and customizable design with potential usage in photoelectric devices, ultrafast optics, and algorithmic data analysis. The development of the Fourier transform (FT) Raman spectrometer is limited by its inherent mechanism that FT Raman are generally less sensitive than grating-based ones in the visible and near-infrared range. However, the FT Raman spectroscopy technique has been applied to other scenarios where sensitivity is not the limiting factor. Here, a new development of the birefringent wedge-based FT spectrometer technique is reported, and the system's efficiency is demonstrated from the Raman spectra of a few common laboratory solvents in the cuvette as a test example. For low-light applications, the birefringent wedge-based system shows reinforced functionality compared to Michelson interferometer-based FT spectrometers in the aspects of 1) advantage due to higher accuracy in wavenumber, especially for locating peak positions; 2) multiplex advantage, which largely improves signal-to-noise ratio (SNR). The proposed setup features a stable, compact, and customizable design and provides an up-to-date reference to the development of FT Raman spectrometers from both scientific and engineering aspects. [ABSTRACT FROM AUTHOR]

Plasmas technology is a simple way to functionalize the surface of multi-wall carbon nanotube MWCNT. Homogenous plasma of Ar–N 2 -H 2 gas mixture was generated in radio frequency RF dielectric barrier Discharge DBD at discharge power of 60 W and total pressure of 500 Pa. The active plasma species was monitored by optical emission spectroscopy OES. While the untreated and treated MWCNTs were investigated with various techniques. The result from OES shows complex spectrum with spectral line/bands related various species such as OH, N 2 , CN, C 2 , H α and Are I, confirming the rich plasma environment, as well as possible active interaction between the MWCNTs and the plasma species. The TEM images of the treated samples revealed the roughness of the CNT outer surface. The X-ray photo electron emission XPS results confirm the presence of nitrogen-based functional groups (C–N C, C–NH O and (C O)–N-(C O)) on the plasma treated MWCNTs. Raman spectrum analysis confirms the functionalization of the treated MWCNTs as the I D / I G ratio increased for the treated sample. The Ar–N 2 -H 2 plasma treatment of MWCNTs undamaged the MWCNTs structure and preserved integrity as observed by XRD result and SEM image. • Effective amino functionalization using Ar–N 2 -H 2 plasma mixture. • The OES of the Ar–N 2 -H 2 plasma mixture displays the presence of OH, N 2 , CN, C 2 , H α and Ar I. • The XPS revealed the presence of C–N C, C–NH O and (C O)–N-(C O) groups on the treated sample. • The plasma treated MWCNTs preserve their structure integrity. [ABSTRACT FROM AUTHOR]

• A pseudotargeted lipidomics method was used for identifying alkylglycerols in foods. • A new Dart package termed FFIMA was developed to facilitate data processing. • Mild acid hydrolysis was employed to assist in analyzing ether phospholipid species. • A total of 156 alkylglycerol-type ether lipids and 35 plasmalogens were identified. Alkylglycerols (1-O-alkyl- sn -glycerols) are microscale but critical lipids in foods. Conventional lipidomics analysis often loses sight of alkylglycerol analysis. In this study, we developed a high coverage pseudotargeted lipidomics method for analyzing alkylglycerols. The developed method integrated the advantages of GC–MS and LC–MS to profile alkylglycerol-type ether lipids comprehensively, with the help of a data processing Dart package termed FFIMA (Feature Fragments Information Matching Algorithm). The developed method exhibited competitive superiority to conventional lipidomics, such as wider coverage and higher accuracy. The validated method was assessed by three aquatic products and three milks. A total of 25 alkylglycerols, 107 diacylglycerol ethers, 21 monoacylglycerol ethers, 28 alkylglycerol-type ether phospholipids, and 35 plasmalogens were identified in the six foods. The results demonstrated that this method offers a comprehensive analysis of a wide spectrum of alkylglycerols. [ABSTRACT FROM AUTHOR]

Traffic prediction is an important topic in intelligent transportation systems (ITSs) that can provide support for many traffic applications. However, accurate traffic prediction is a challenging task, and its difficulties mainly come from the complex spatial and temporal dependencies of traffic network data. Previous studies mainly focused on capturing the spatiotemporal dependencies of traffic data but ignored the temporal frequency features of traffic flows. In this paper, we design a novel multichannel spatial–temporal graph convolution network based on spectrum decomposition (MSDGCN) for traffic prediction. First, we decompose the original traffic flow series into low-frequency, mid-frequency and high-frequency components based on spectrum analysis. Then, based on ChebNet and LSTM, a prediction model with three channels is constructed to capture the low-frequency, mid-frequency and high-frequency features of the traffic flow. Finally, an attention layer is adopted to assign weights for different channels, enabling the model to focus on capturing the main features of the traffic flow. Compared to the state-of-the-art baselines, our model captures the distinct frequency components of the original traffic flow series in a more meticulous manner. Experimental results obtained on six real-world datasets indicate the excellent performance of our model. • We introduced DFT and spectrum analysis into traffic prediction. • An attention mechanism is utilized to reduce the adverse impact of local fluctuations. • A novel multichannel spatial–temporal graph convolution network is constructed. [ABSTRACT FROM AUTHOR]

Pigments with color diversity, hydrophobicity, biocompatibility and photostability are significantly attractive in cosmetic, but it is still a challenge to invent them. To achieve this promising goal, this study demonstrates an unprecedented concept of pigments from assembling zein protein to dye-modified layered double hydroxides (zein/dye-LDHs) by a simple two-step method. Elaborate characterizations including X-ray powder diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, Ultraviolet−visible absorption spectra and thermogravimetric analysis confirm the successful exploration of zein/dye-LDHs biohybrid with the sandwich structure that dye is intercalated into the interlayer space of LDHs by the host-guest interaction between host sheets and guest dye anions, while zein is grafted on dye-LDHs surface via electrostatic interactions and hydrogen bonds. The intercalation into the interlayer region of LDHs and zein grafting remarkably improved the hydrophobicity and photostability of organic dyes and obviously decreased their irritation potential. Further, the diversified color could be easily achieved via adjusting the dosage of pigment and the lipstick formulated with zein/dye-LDHs demonstrated good water resistance, low color migration, natural appearance and high sustainability. These results open a new direction for fabricating pigment with adjustable color hue, good hydrophobicity, high photostability and outstanding biocompatibility, which would inspire more exploration of other biohybrid pigments and applications. [Display omitted] • Zein/dye-LDHs biohybrid with a sandwich structure is first reported in hydrophobic pigment. • Zein/dye-LDHs exhibits enhanced photostability, better hydrophobicity as well as less toxicity compared to organic dyes. • The performance of Zein/dye-LDHs is elucidated by water resistance test, color migration test and sustainability evaluation. • The combination of LDHs intercalation and zein grafting is vital for determining the pigmentary and cosmetic behavior. [ABSTRACT FROM AUTHOR]

• We investigated cortical activity and game performance in first-person shooter (FPS) players in similar to actual gaming environments. • High-skilled FPS players have fast reaction times and high accuracy during tasks. • High-skilled FPS players had a lower delta and theta power spectral density in the frontal and temporal areas. • High cortical activity and accuracy during the task were associated. First-person shooting (FPS) games are among the most famous video games worldwide. However, cortical activities in environments related to real FPS games have not been studied. This study aimed to determine differences in cortical activity between low- and high-skilled FPS game players using 160-channel electroencephalography. Nine high-skilled FPS game players (official ranks: above the top 10%) and eight low-skilled FPS game players (official ranks: lower than the top 20%) were recruited for the experiment. The task was set for five different conditions using the AimLab program, which was used for the FPS game players' training. Additionally, we recorded the brain activity in the resting condition before and after the task, in which the participants closed their eyes and relaxed. The reaction time and accuracy (the number of hit-and-miss targets) were calculated to evaluate the task performance. The results showed that high-skilled FPS game players have fast reaction times and high accuracy during tasks. High-skilled FPS game players had higher cortical activity in the frontal cortex than low-skilled FPS game players during each task. In low-skilled players, cortical activity level and performance level were associated. These results suggest that high cortical activity levels were critical to achieving high performance in FPS games. [ABSTRACT FROM AUTHOR]

According to the theory of traditional Chinese medicine, the main factors related to alcoholic liver disease (ALD) are qi stagnation and blood stasis of the five viscera. Previously, we showed that the bioactive components of Alhagi honey have various pharmacological effects in treating liver diseases, but the influence of Alhagi honey on ALD (and its mechanism of action) is not known. To determine the efficacy of the main active component of Alhagi honey, the polysaccharide AHPN80, in ALD and to explore the potential mechanism of action. AHPN80 was isolated from dried Alhagi honey and identified by transmission electron microscopy, Fourier-transform infrared spectroscopy, and gas chromatography. Venous blood, liver tissue, and colon tissue were collected in a mouse model of alcohol-induced acute liver injury. Histology, staining (Oil Red O, Alcian Blue–Periodic Acid Schiff) and measurement of reactive oxygen species (ROS) levels were used to detect histopathologic and lipid-accumulation changes in the liver and colon. Lipopolysaccharide (LPS) levels and the content of proinflammatory cytokines in serum were measured by enzyme-linked immunosorbent assays. Commercial kits were employed to detect biochemistry parameters in serum and the liver. A terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining kit was used to identify hepatocyte apoptosis. Expression of tight junction-associated proteins in colon tissues and nuclear factor erythroid 2-related factor 2/heme oxygenase-1/toll-like receptor-4/mitogen-activated protein kinase (Nrf2/HO-1/TLR4/MAPK) pathway-related proteins in liver tissues and HepG2 cells were analyzed by immunofluorescence or western blotting. In a mouse model of alcohol-induced acute liver injury, AHPN80 therapy: significantly improved liver parameters (cytochrome P450 2E1, alcohol dehydrogenase, aldehyde dehydrogenase, superoxide dismutase, malondialdehyde, glutathione peroxidase, catalase, total cholesterol, triglycerides, alanine transaminase, aspartate transaminase); reduced serum levels of LPS, interleukin (IL)-1β, IL-6, and tumor necrosis faction-α; increased levels of IL-10 and interferon-gamma. AHPN80 reduced ALD-induced lipid accumulation and ROS production, improved alcohol-induced inflammatory damage to hepatocytes, and inhibited hepatocyte apoptosis. Immunofluorescence staining and western blotting suggested that AHPN80 might eliminate hepatic oxidative stress by activating the Nrf2/HO-1 signaling pathway, repair the intestinal barrier, inhibit the LPS/TLR4/MAPK signaling pathway, and reduce liver inflammation. AHPN80 may activate the Nrf2/HO-1 pathway to eliminate oxidative stress, protect the intestinal barrier, and regulate the TLR4/MAPK pathway to treat ALD in mice. AHPN80 could be a functional food and natural medicine to prevent ALD and its complications. [Display omitted] • AHPN80 could activate the Nrf2/HO-1 pathway, scavenge ROS and eliminate oxidative stress effectively. • AHPN80 protected against intestinal-barrier dysfunction in alcohol-fed mice. • AHPN80 improved alcohol-induced hepatic inflammation via the TLR4/MAPK pathway. • AHPN80 can be a functional food/natural medicine to prevent ALD and its complications. [ABSTRACT FROM AUTHOR]

Panax Notoginseng (PN) can disperse blood stasis, hemostasis, and detumescence analgesic, which can be used for hemoptysis, hematemesis and another traumatic bleeding, and it is known as "A miracle hemostatic medicine". Studies show that the chemical composition of PN is relatively comprehensive, however, its hemostatic active ingredients have not been fully clarified. This study aimed to clarify the hemostatic effective components group (HECG) of PN, provide a foundation for the assessment of PN's quality and its comprehensive development, and for further studies on the pharmacodynamic material basis of other Traditional Chinese Medicines (TCMs). UPLC-MS was used to establish the fingerprint and identify the common peaks in 44 batches of PN extracts (PNE). In addition, the plasma recalcification time and in vitro coagulation time were measured. For spectrum-effect analysis, bivariate correlation analysis (BCA) and partial least squares regression analysis (PLSR) were used to screen the hemostasis candidate active monomers of PN. The monomers were prepared by combining several preparative chromatography techniques. The efficacy was verified by plasma recalcification time, in vitro coagulation time, and a rat model of gastric hemorrhage. A total of 30 common peaks and hemostatic efficacy indexes of 44 batches of PNE were obtained. A total of 18 components were positively correlated with the comprehensive coagulation index by two statistical methods. Six and eleven monomers were obtained respectively by chromatographic preparation and procurement, and one monomer was eliminated due to preparation difficulty and other reasons. Seven active monomers with direct hemostatic effect and one active monomer with synergistic hemostatic effect were screened through plasma recalcification time, and their combinations were used as candidate HECG for hemostatic effect verification. The results of in vitro experiments showed that plasma recalcification time and in vitro coagulation time were significantly reduced (P < 0.05) in the HECG group, compared to the PNE group. The results of in vivo experiment also indicated that the hemostatic effect of HECG was comparable to that of PNE and PN powder. The composition and efficacy of the HECG of PN were screened and verified using the spectral correlation method and in vivo and in vitro efficacy verification; the HECG included Dencichine, Ginsenoside Rg 1 , Ginsenoside Rd, Ginsenoside Rh 1 , Ginsenoside F 1 , Notoginsenoside R 1 , Notoginsenoside Ft 1 and Notoginsenoside Fe. These results laid a foundation for the quality evaluation of PN and provided a reference for the basic research of pharmacodynamic material basis of other TCMs. [Display omitted] • Clarify the hemostatic effective components group of Panax Notoginseng (PN). • Provide a foundation for the assessment of PN's quality and its comprehensive development.. • The selection of gastric hemorrhage model combines the meridian tropism theory and the clinical application of PN.. [ABSTRACT FROM AUTHOR]

Wood texture is pivotal in maximizing the value of trees and timber resources. Consequently, digital modeling and simulation of wood texture have become essential in wood science and industry. Therefore, researching simulation modeling techniques for digital wood texture has significant implications for advancing wood science and industry. This paper introduces a novel approach to modeling and simulating wood texture, focusing on the perspective of deep learning. The proposed method explored the viability of utilizing the StyleGAN model to generate digital wood texture. Fréchet Inception Distance(FID), visual Turing tests, and 1/f fluctuation spectrum analysis were used to evaluate the effectiveness of the digital wood texture models. Additionally, various control techniques were discussed for generating digital wood texture using StyleGAN models. The experimental results strongly indicated that the StyleGAN model exhibits robust capabilities in generating digital wood texture, as evidenced by an FID index of 13. Moreover, the visual Turing tests revealed that professional identification was similar to random guessing, while the fluctuation spectrum analysis demonstrated pixel distribution frequencies similar to those observed in real wood textures. Furthermore, in terms of controlling the simulation of digital wood texture, the StyleGAN model demonstrated remarkable abilities surpassing any previous models based on physical modeling. By fine-tuning truncation parameters and employing network layer mixing techniques, the model could generate the wood texture of various tree species, demonstrating outstanding generalization capabilities. • A new StyleGAN-based simulation method for wood texture is proposed. • Multiple quantitative assessment tools were used to evaluate the simulation results. • Our method simulates wood textures of all tree species with strong generalization. • Wood texture simulation aids wood science and industry in various applications. [ABSTRACT FROM AUTHOR]

Aspercitrininone A (1), a novel polyketide featuring an unprecedented tetracyclic 6/6/6/5 spiral skeleton, was obtained from the rice fermentation cultures of the fungus Aspergillus cristatus together with five known compounds (2 – 6). Their structures were determined by HRESIMS data, 1D and 2D NMR spectroscopic analysis, and electronic circular dichroism (ECD) calculations. Aspercitrininone A was revealed as a new type of C/D cycle spiral structure and an unusual addition product of o-quinoid form citrinin with 2-methylterrefuranone. Compounds 1 , 4 , and 5 exhibited potent antibacterial activities with minimal inhibitory concentration (MIC) values from 13.2 to 67.3 μg/mL against four strains of human pathogenic bacteria in vitro. [Display omitted] • A novel polyketide aspercitrininone A was isolated from rice cultures of Aspergillus cristatus. • Aspercitrininone A possessed an unprecedented tetracyclic 6/6/6/5 spiral skeleton. • It could be formed by o-quinoid form citrinin with 2-methylterrefuranone through Michael addition reaction. • Aspercitrininone A exhibited antibacterial activities. [ABSTRACT FROM AUTHOR]

Four previously unreported diterpenoids including three ent -atisanes (1–3) and one ent -abietane (4), along with one known linear triterpenoid (5) and five known diterpenoids including four myrsinanes (6–9), and one abietane (10) have been isolated from the roots of Euphorbia spinidens Bornm. ex Prokh. The structures were determined on the basis of extensive spectroscopic analyses including HR-ESI-MS, 1D and 2D NMR and comparison of the data with those reported in the literature. Antimicrobial potential of isolated compounds were also evaluated. Guionianol B (10) showed good antibacterial activity against Staphylococcus aureus and Bacillus subtilis with MIC value of 6.25 μg/mL. [Display omitted] [ABSTRACT FROM AUTHOR]