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The preparation of fused silica glass with microstructural patterns has attracted considerable interest, and the process chain of using nano-silica powders mixed with organic polymers to prepare composites for molding, degreasing, and sintering provides a good solution. However, the potential negative effects of organic residues cannot be avoided. In this study, a pattern stencil replication method with silica gel using high-purity quartz fibers as reinforcement is proposed for preparing micropatterned fused silica glass. The microscopic morphology and mechanical properties before and after silica gel drying and the optical properties of fused silica glass obtained by sintering were evaluated via transmission electron microscopy), three-point bending strength test, scanning electron microscopy, X-ray diffraction spectrum analysis, ultraviolet–visible and infrared measurements. The results showed that quartz fiber as a reinforcer could shorten the drying time of the gel and did not degrade the quality of the fused silica glass obtained by sintering. Laser confocal test results showed that microlens arrays were generated by template replication, demonstrating the feasibility of molding fused silica lens arrays with small feature sizes and providing new ideas for the preparation of bulk fused silica glass or micropatterned glass. [ABSTRACT FROM AUTHOR]

The technology of p-type transparent semiconductors is utilized in various fields, and enhancing their performance holds industrial significance. Thus, improving the versatility and efficiency of the p-type transparent conducting oxides (TCO) has become critical for the semiconductor industries and technologies. To be used as hole carrier layes in optoelectronic devices, this study aimed to modify the physical features of nickel oxide (NiO) through a doping approach which may broaden and strengthen the usage of NiO. A cost-effective ultrasonic pyrolysis spray technique was employed for pure and lead (Pb) doped nickel oxide thin film production. The influence of the lead concentration on optical, structural, and morphological traits of the NiO nanostructures was examined via various analyses, including energy-dispersive X-ray spectroscopy (EDAX), scanning electron microscopy (SEM), Photoluminescence, UV–visible spectroscopy, X-Ray Diffraction, and Raman spectroscopy, were utilized to investigate the optical and structural characteristics of these films. In correlation, the X-Ray Diffraction results indicated that the Pb doping induced strain and altered lattice parameters of the grown nanostructures while the cubic phase of NiO maintained. The crystallite size of NiO samples ranged from 31.49 nm to 18.75 nm based on Pb doping concentration which was notably influenced by species and doping content. The UV–vis measurements demonstrated that optical parameters, such as optical band gap, were sensitive to Pb doping ratios. The Raman spectrum analysis confirmed the successful incorporation of Pb ions into NiO. Additionally, the intensity of the PL spectra decreased with increasing Pb content, offering potential applications as window layers in solar cells, smart windows, and other optoelectronic devices. [ABSTRACT FROM AUTHOR]

• 27-day variations of GCR flux according to measurements of AMS-02 and others. • Parameterization of the amplitude-energy spectrum of variations. • Consequences of the force-field model for short-term modulation. This work presents the results of the analysis of 27-day variations in the flux of galactic protons registered by STEREO, SOHO, and AMS-02 in 2015–2016. We calculate variations' amplitude using several different approaches and propose a description of its energy dependence in the range of magnetic rigidity from approximately 0.3 to 100 GV. We also analyse variations of the solar modulation potential, which is the only parameter of force-field model, and consider the possibility of describing the 27-day variations of galactic cosmic rays within the framework of this model. It is shown that rigidity dependence of the 27-day variations amplitude cannot be properly described using this simple approximation. [ABSTRACT FROM AUTHOR]

• Automatic selection of embedding dimension in Singular spectrum analysis is achieved. • Singular spectrum analysis yields the most stable and accurate sea level heights among the methods. • Singular spectrum analysis provides a better concentration of spectral power in the periodogram. In order to obtain reliable GNSS-R derived sea level heights (SLHs), it is crucial to extract accurate reflected signals from signal-to-noise ratio (SNR) data. In this study, Quadratic Fitting, Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), and Singular Spectrum Analysis (SSA) are adopted for extracting the reflected signals from SNR data, which are then analyzed with Lomb Scargle Periodogram (LSP) assisted with tidal harmonic analysis for GNSS-R SLHs. Three continuous GNSS stations including Onsala in Sweden, Friday Harbor in the United States, and Brest in France with tidal ranges of approximately 1 m, 3 m, and 7 m, respectively, were used in the study. The derived SLHs were evaluated against the nearby or co-located tide gauge records. The results reveal that the three proposed algorithms effectively cope with the multi-peaks spectrum problems when using the conventional Quadratic Fitting without a priori reflected height constraint, and SSA can provide the solutions with fewer outliers among the proposed methods with the RMSEs of 6.7 cm, 13.4 cm and 39.6 cm at Onsala, Friday Harbor, and Brest stations, respectively. Without implementing tidal harmonic analysis, SSA is the method capable of acquiring reliable SLHs among the stations, as evidenced by comparing with co-located gauge records, particularly at the Brest station. In summary, SSA not only distinguishes signals across different frequencies, but also orders the signal components according to their eigenvalues, demonstrating the potential to extract the reflected signals from SNR and enhance the stability and accuracy of GNSS-R applications. [ABSTRACT FROM AUTHOR]

• Analysis of geomagnetic field's H time series during quiet geomagnetic condition. • The H time series from high latitude region shows anti-persistent behaviour. • H time series of quiet geomagnetic condition shows multifractal characteristics. • Change in multifractal characteristics with latitude is observed. • The cause of multifractality is identified as long-range correlations. The generation of geomagnetic time series frequently involves intricate spatio-temporal dynamics, wherein nonlinearity and scaling emerge as pivotal mechanisms. The present work investigates the fractal properties of geomagnetic field, and its sources during quiet geomagnetic conditions, by analyzing the horizontal component data of 1 min resolution (H time series) from different latitude regions. Analysis using Auto Correlation Function (ACF), Power spectrum analysis (PSA), Rescaled range analysis (R/S) and Detrended Fluctuation Analysis (DFA) gave indications of the presence of long-range correlations, fractal properties and scaling behaviour of quiet period H time series data. The strong q dependence of generalized Hurst exponent h(q) and scaling exponent Ʈ(q), obtained from the Multifractal Detrended Fluctuation Analysis (MFDFA) method, confirmed the multifractal behaviour of quiet period H time series. The multifractal source analysis of the quiet period H time series with its shuffled and surrogate time series data revealed that, the multifractal characteristics are caused almost entirely by the long-range correlations between small and large fluctuations. The analysis of the latitudinal variations in the multifractal characteristics is also performed as a part of the work, by considering H time series belonging to various latitudes under almost same longitude. The observed decrease in the generalized Hurst exponent values with increase in latitude indicates the change in the multifractal characteristics of the time series with latitude. Also the work revealed that, the H time series from high latitude region shows anti-persistent behaviour, even when the H time series from observatories located at the low and mid latitude regions exhibiting persistent behaviour. The change in the persistence, anti-persistence behaviour can be related to the strength of Earth's magnetic field. [ABSTRACT FROM AUTHOR]

This study successfully synthesized novel phosphors Ca 2 GaTaO 6 : x Dy3+ (CGTO: x Dy3+) and Ca 2 GaTaO 6 :0.06Dy3+, y Sm3+ (CGTO:0.06Dy3+, y Sm3+) using the high temperature solid-phase reaction preparation. The microstructure, optical properties, and energy transfer mechanism of the phosphors were studied through X-ray diffraction (XRD), scanning electron microscope (SEM), photoluminescence (PL) spectra and fluorescence lifetimes. XRD and corresponding refinement results indicate that Dy3+ and Sm3+ ions were effectively doped into the Ca 2 GaTaO 6 (CGTO) lattice. The SEM graphs show that the elements in CGTO:0.06Dy3+, 0.5Sm3+ phosphors are uniformly distributed. PL spectra analysis show the CGTO: x Dy3+ phosphors display two strong emission peaks located at 482 nm for blue emission and 575 nm for yellow emission when excited with 350 nm light. Under uniform conditions, when excited with 365 nm of light, the CGTO:0.06Dy3+, y Sm3+ phosphors emit light that can be tuned with adjustable color coordinates and correlated color temperature (CCT) by incorporating varying proportions of Sm3+ ions. This tunability is achieved through the effective energy migration from Dy3+ to Sm3+ ions within the phosphor material. Furthermore, the emission spectra and weaken lifetimes of the CGTO:0.06Dy3+, y Sm3+ confirm the energy transport between Dy3+ and Sm3+, and the energy transfer efficiency reached to 76 %. At 423 K, the luminescence intensity of CGTO:0.06Dy3+, 0.05Sm3+ phosphor retains 87 % of the intensity observed at 298 K, signifying its excellent thermal durability. Finally, the electroluminescent performance of the CGTO:0.06Dy3+ and CGTO:0.06Dy3+, 0.05Sm3+ phosphors packaged on 365 nm light-emitting diode (LED) chips respectively were studied to investigate the capability applications of the phosphors in white light-emitting diodes (WLEDs) field. The CCT of the packaged LEDs decline from 3396 to 2825 K, indicating CGTO:0.06Dy3+, 0.05Sm3+ phosphor shifts to warmer white light. At a voltage input of 3.4 V and a current of 600 mA, the thermal sensing shows that the WLEDs maintain aptitude for 90 min, showing that the packaged WLEDs can function consistently under elevated temperatures. These studies indicated the phosphors have potential applications in indoor lighting. [ABSTRACT FROM AUTHOR]

Southeastern Turkey perished by the M w 7.8, Kahramanmaras earthquake on February 6, 2023, at 01:17 UT (04:17 LT). The Kahramanmaras-centered event, hit by the break of the East Anatolian Fault Line, is felt in Syria, Egypt, Lebanon, Iraq, and Cyprus on the border of Turkey. Together with Syria, it causes loss of lives and severe damage in 10 cities. This work is dedicated to the people of the region. The study discusses the causality of anomalies by conducting ionospheric anomaly research via the interpolated TEC map obtained from the CODE according to the coordinates of the epicenter of the earthquake (latitude, longitude). The TEC amplitudes are observed by evolving the time-domain TEC map into the frequency-domain with the Fourier transform. The peaks of the amplitudes allow preliminary information for the anomaly days. For the anomaly, the TEC (TECU) boundaries are drawn by the statistical specification. The TEC map outside these boundaries is marked as an anomaly. The causality of abnormalities is tried to be read through the triad of the geomagnetic storm(s) , solar activity , and the earthquake effect. One can find seven anomaly days in the paper. January 30, February 2, 3, 11, 15, 16, and 21 are the anomaly days. The essay probably detects the anomaly before 3 days related to the Southeastern earthquake. • Reads the causality of the earthquake in southeast Turkey (Mw 7.8), through the ionosphere-earth crust relationship. • Notices potential anomalies by presenting the time-domain TEC atlas in the frequency domain with Fourier spectral analysis. • Considering all possible TEC anomaly essentials detect the precursors of the earthquake 3 days before the event day. [ABSTRACT FROM AUTHOR]

Studying the mechanisms of bagasse conversion into syngas is essential to sustain the growing use of biomass in energy economy production. In this work, the precise kinetics of bagasse gasification with various gasification agents was firstly investigated employing in-situ infrared spectra with Coats-Redfern integration, combining qualitative infrared spectroscopy allowed for kinetic analysis, so as to explore how the intermediate species vary in each basic reaction. The results demonstrate that the CO 2 agent reduces the activation energy of nitryl after amino oxidation, making the lignin involved in gasification more easily as well as causing higher gasification efficiency. On the one hand, steam serving as a gasification agent enhances the concentration of hydroxyl groups and produces H 2 -rich syngas. On the other hand, the strong oxidizing hydroxyl group reduces the energy barrier of carbonyl and carboxyl groups in cellulose, which facilitates the gasification process. Furthermore, this study compared the effects of gasification agent (H 2 O or CO 2) on syngas composition, reactor temperature distribution, carbon conversion rate, gasification efficiency, as well as low calorific value, providing essential information for understanding the micro-reaction pathways and pathway regulation during bagasse gasification. • Reducing the activation energy of functional groups are regulated by gasifiers. • The synergistic of gasification agents regulate chemical bond-breaking pathways. • The prospects of producing H 2 from biomass gasification are elucidated. [ABSTRACT FROM AUTHOR]

Pain and inflammation are the most frequent reasons for which people seek medical care. Currently available analgesics against these conditions produce fatal adverse effects. NPK 500 capsules is an alternative herbal analgesic employed to treat dysmenorrhea, peptic ulcer and pain. NPK 500 is produced from Cassia sieberiana. A plant used in traditional medicine to treat pain and inflammation. This study reports the analysis, phytochemical characterization and mechanism of analgesic and anti-inflammatory activities of two NPK 500 capsules, called old and new NPK500 capsules (ONPK500 and NNPK500) respectively. Physicochemical, organoleptic, GC-MS and LC-MS methods were employed to analyze the NPK 500 capsules. Analgesic activity was evaluated using tail immersion, Randall-Selitto and acetic acid induced writing tests. Anti-inflammatory activity was evaluated using carrageenan-induced rat paw inflammation. Additionally, pro-inflammatory mediators such as prostaglandin E2 (PGE2), inducible nitric oxide synthase (iNOS), cyclooxygenase 1 and 2 (COX-2 and COX-1) were quantified in the sera of the rats using Enzyme Linked Immunosorbent Assay (ELISA) kits. Thirteen major compounds were characterized in the NNPK 500 capsules via the GC-MS and LC-MS spectroscopies. Kaempferol was the major compound characterized in addition to physcion, β-sitosterol 3-O-β-D-glucopyranoside, betulinic acid and nine others. Physicochemical and organoleptic indices of the capsules were also derived for its authentication and quality control. Furthermore, NNPK 500 0.5–1.5 mg/kg p.o. produce significant (P < 0.5) analgesic activity (160–197%) higher than that of ONPK500 (109.8%) and Morphine (101%) in the tail immersion test. The analgesic activity of NNPK 500 0.5–1.5 mg/kg p.o. (171.0–258.3%) and ONPK 500 (179.5%) were also significant (P < 0.01) and higher than that of Aspirin (103.00%) in the Randall-Selitto test. Both capsules also demonstrated significant (P < 0.5) analgesic and anti-inflammatory activities in the acetic acid-induced writhing and carrageenan-indued paw edema tests respectively. The two NPK500 capsules also, significantly (P < 0.5) inhibited PGE2 and iNOS but not COX-2 and COX-1 in the carrageenan-indued paw edema test. These results show that NNPK 500 and ONPK 500 capsules possessed potent analgesic and anti-inflammatory activities via inhibition of PGE2 and iNOS as a result of their chemical constituents. NPK500 capsules thus, relief acute pain and inflammation without causing gastrointestinal, renal or hepatic injuries, since they did not inhibit COX-1. [Display omitted] • The major active ingredient identified in NPK500 capsules was kaempferol. • Physcion, β-sitosterol 3-O-β-D-glucopyranoside and betulinic acid were also present. • Analgesic activity of NPK500 was 171.0–258.3% against 103.00% for Aspirin. • NPK500 also produced significant anti-inflammatory activity. • NPK500 capsules inhibited PGE2 and iNOS during inflammation. [ABSTRACT FROM AUTHOR]

Ficus erecta , a traditional Chinese She Ethnomedicine, has been historically utilized to treat various inflammatory conditions such as arthritis, nephritis, and osteoporosis. However, the underlying mechanisms accounting for its anti-inflammatory activity, as well as its active components, largely remain elusive. The purpose of this research was to investigate the chemical constituents of F. erecta that contribute to its anti-inflammatory effects. Coumarins and flavones were obtained from the 95% EtOH extract of F. erecta using virous column chromatography and reversed-phase semipreparative HPLC. The structures of the new compounds were elucidated by extensive analysis of spectroscopic methods, including HRESIMS, 1D and 2D NMR spectra, and CD experiments. Cultured macrophage RAW264.7 cells were utilized for the anti-inflammatory experiments. MTT cell viability assay, Griess reagent method, ELISA, and Western blot experiments were employed to evaluate the anti-inflammatory activity and investigate the related mechanism. Four new (1–4) and eleven previously identified (5–16) coumarins, together with one new (17) and six known flavones (18–23) were isolated from the whole plant of F. erecta. Compounds 7 and 17 significantly reduced nitric oxide (NO) and prostaglandin E2 (PGE 2) production without cytotoxic effects. Furthermore, compounds 7 and 17 reduced the production of proinflammatory cytokines including tumor necrosis factor (TNF)- α , interleukin (IL)-1 β , and IL-6 in a concentration-dependent manner. Western blot analysis indicated that compounds 7 and 17 suppressed the expression of iNOS, COX-2, and p-I κ B α in LPS-stimulated RAW264.7 macrophage cells. The current phytochemical investigations revealed that coumarins and flavones represent the primary chemical constituents of F. erecta. Compounds 7 and 17 exhibit potent anti-inflammatory properties, linked with the inhibition of NF- κ B activation by preventing the degradation of I κ B α phosphorylation. These compounds may serve as promising candidates for treating or preventing certain inflammatory diseases. [Display omitted] • Four new coumarins and one new flavone were isolation from Ficus erecta. • Their structures were elucidated on the basis of spectroscopic analyses. • Twelve selected isolates were evaluated for the in vitro anti-inflammatory activity. • 7 and 17 reduced the production of pro-inflammation mediators and cytokines. • 7 and 17 might exert their anti-inflammatory effects by inhibiting NF- κ B activation. [ABSTRACT FROM AUTHOR]

Accurate baseline correction is a fundamental requirement for extracting meaningful spectral information and enabling precise quantitative analysis using Raman spectroscopy. Although numerous baseline correction techniques have been developed, they often require meticulous parameter adjustments and yield inconsistent results. To address these challenges, we have introduced a novel approach, namely constrained Gaussian radial basis function fitting (CGF). Our method involves solving a curve-fitting problem using Gaussian radial basis functions under specific constraints. To ensure stability and efficiency, we developed a linear programming algorithm for the proposed approach. We evaluated the performance of CGF using simulated Raman spectra and demonstrated its robustness across various scenarios, including changes in data length and noise levels. In contrast to standard methods, which frequently require complicated parameter adjustments and may exhibit varying errors, our approach provides a simple parameter search and consistently achieves low errors. We further assessed CGF using real Raman spectra, leading to enhanced accuracy in the quantitative analysis of the Raman spectra of chemical warfare agents. Our results emphasize the potential of CGF as a valuable tool for Raman spectroscopy data analysis, significantly advancing sophisticated analytical techniques. • We introduce innovative methods for baseline correction. • We also consider the development of a curve fitting problem and an efficient linear programming algorithm. • Empirical results demonstrate our methods' superior accuracy in both simulated and real data. • Our methods demonstrate robustness across various measurement scenarios. [ABSTRACT FROM AUTHOR]

The analysis of in situ single cells in tissue is crucial for the study of tumors. However, simultaneous analysis of multiple biomolecules for single cells by fluorescence immunohistochemistry is challenging. Spontaneous Raman spectroscopy provides biochemical fingerprints of individual cells in a label-free and nondestructive manner, yet it is not well applied to single cells in tissue. Here, we develop an in situ single-cell spontaneous Raman spectroscopy (SRS) system that can localize a single cell in tissue with fluorescence imaging, while obtaining the single-cell Raman spectra for molecular analysis. Our system is verified by measuring the standard polystyrene beads of different sizes. Measurements of in situ single macrophages in clinical cancerous and para-cancerous tissues are then performed. By using discriminant analysis, it is shown that CD68+ macrophages in cancerous and para-cancerous tissues are classified with an accuracy of 98.3 %. The molecular content of single macrophages in tissue is analyzed by using multivariate curve resolution-alternating least squares method. We find that the lipid content of tumor-associated macrophages in cancerous tissues is higher while both the contents of protein and nucleic acid are lower than those in para-cancerous tissues, which is challenging to achieve by conventional immunohistochemistry. Our in situ single-cell SRS system has the capability for the obtaining of molecular information of a localized single cell in tissue, which may find potential applications for clinical cancer diagnosis. • An in situ single-cell spontaneous Raman spectroscopy (SRS) system is developed. • In situ single-cell SRS localizes a single cell in tissue, and obtains its Raman spectra for molecular analysis. • Single CD68+ macrophages in liver cancerous and para-cancerous tissues are classified. • Various molecular substances of single CD68+ macrophages in liver cancerous and para-cancerous tissues are analyzed. [ABSTRACT FROM AUTHOR]

Three new neo -5,10- seco -clerodane diterpenoids (1 – 3), four previously undescribed ethoxy/methoxy acetal analogues (4 – 7), one new etherified labdane diterpenoid (8), and seven known diterpenoids (9 – 15) were isolated from the whole plant of Schnabelia terniflora. Their structures were established on the basis of extensive spectroscopic analysis, single-crystal X-ray diffraction data, calculated electronic circular dichroism (ECD), and Mo 2 (OAc) 4 -induced circular dichroism. Compounds 2 and 3 represent the first examples of neo -5,10- seco -clerodane diterpenoids containing a 1 H -pyrrole-2,5-dione and a pyrrolidine-2,5-dione moiety, respectively. A plausible biosynthetic pathway for 1 – 3 is proposed. All diterpenoids were evaluated for their cytotoxic activity against non-small-cell lung cancer lines (A549 and H460) and gastric cancer lines (HGC27 and AGS). Among them, 2 and 14 showed moderate cytotoxicity against four cell lines. [Display omitted] [ABSTRACT FROM AUTHOR]

The phytochemical investigations on the fruits of Kadsura coccinea led to the isolation of six undescribed dibenzocyclooctadiene lignans named kadcolignans B-G, together with eleven previously described analogues. The structures of these compounds were established by spectroscopic methods including NMR, HRESIMS, and CD experiments. All isolated compounds were evaluated for their hepatoprotective activity by measuring the levels of triglyceride (TG), total cholesterol (TC), and reactive oxygen species (ROS) in FFA-induced HepG2 cells. As a result, compounds 4 , 5 , 9 , 13 , and 15 showed potent inhibitory effects on hepatocyte lipid accumulation at a concentration of 100 μM. Our research not only broadens the understanding on the chemical composition of K. coccinea but also provides experimental and theoretical evidences supporting the fruit's active ingredients in alleviating nonalcoholic fatty liver disease (NAFLD). Six undescribed dibenzocyclooctadiene lignans were isolated from the fruits of Kadsura coccinea. Five dibenzocyclooctadiene lignans showed strong inhibitory effects on hepatocyte lipid accumulation. [Display omitted] [ABSTRACT FROM AUTHOR]

• Theoretical derivations explored SFPR errors in BTT, confirmed by rigorous experiments and simulations. • Simulation and experimentation verified errors from speed fluctuation on blade frequency spectrum analysis. • An actual angle of arrival fitting method is proposed to correct speed fluctuation errors in BTT. • Simulation and experiment results show the proposed method is more accurate and robust than the conventional method. Blade tip timing (BTT) serves as an innovative non-contact technique for measuring blade tip vibration displacement, offering the capability to conduct online measurements of blade vibrations during operation. Despite its potential, the conventional BTT calculation method encounters significant inaccuracies attributable to speed fluctuation per revolution (SFPR), posing challenges for identifying blade vibration parameters accurately. To address this issue, extensive theoretical derivations were undertaken to comprehensively investigate the factors influencing the error magnitude induced by speed fluctuation. In response to the identified challenges, an innovative approach known as the actual angle of arrival fitting BTT method (AAF) was proposed. This method, grounded in a least square approach, aims to reduce errors caused by SFPR and enhance the precision of blade vibration measurement. The correctness of theoretical derivations and the effectiveness of the AAF BTT method were validated through thorough numerical simulations and experimental verifications, providing valuable insights into improving measurement accuracy. Results from these validations underscored the simplicity, efficiency, and enhanced accuracy afforded by the AAF method in measuring blade tip vibrations. By overcoming the limitations of conventional BTT calculation methods, the AAF approach offers a promising avenue for more accurate and reliable blade tip vibration measurements in various operational contexts. [ABSTRACT FROM AUTHOR]

The Polarization Topological Charge (PTC) is a crucial parameter of a Cylindrical Vector Beam (CVB). Defined as the repetition number of polarization state changes along the azimuth axis, its sign indicates the polarization's rotation direction. This paper delves into the effects of polarization mutation within Fractional Vector Beams (FVB) with angular uncertainty on PTC sorting systems. We compare three optical geometric coordinate transformation methods: Log-Polar (LP), Beam-Copying (BC), and Spiral Transformation (ST), focusing on their robustness and suitability. Our findings show that the azimuth angle of polarization mutation markedly influences the PTC sorting system's output, leading to measurable uncertainties. Importantly, these uncertainties are not intrinsic to the FVB, but rather stem from the sorting system itself. Our study concludes that the BC method is optimal for PTC spectra analysis, whereas the ST method with carefully selected parameters is preferable for average PTC analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Cool white light emissive Y 2 Si 2 O 7 :Dy3+ developed via gel-combustion method, having triclinic crystal structure with P-1 space group. • NUV 352 nm excitation produced different emission peaks of Dy3+ ions, analogous to 4F 9/2 →6H 15/2, 13/2 and 11/2 transitions. • Quadrupole-quadrupole interaction responsible for concentration quenching. • Optimum sample maintain luminescence stability 80.4 % upto 423 K temperature with 0.2503 eV of activation energy. We report on development and properties of Dy3+ doped Y 2 Si 2 O 7 (YPS) phosphor, a key development in efficient, sustainable lighting via phosphor converted white light emitting diodes (pc-wLEDs). Using gel-combustion method, we synthesized a series of Y 2-x Si 2 O 7 :xDy3+ (x = 1–8 mol %) phosphors. The prepared samples were characterized for their structure, morphology and elemental composition using X-ray diffraction (XRD), transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDX) respectively. Diffraction exploration verified triclinic structure and phase purity of fabricated samples. TEM image displayed particle agglomeration with nearly spherical structures. Optical parameters were assessed through diffuse reflectance spectrum (DRS) and photoluminescence (PL) spectra analysis. On 352 nm excitation, distinct luminous peaks from Dy3+ ions, analogous to 4F 9/2 →6H M (M = 15/2, 13/2, and 11/2) transitions, were observed. Particularly, intense emission at 571 nm resulted from the 4F 9/2 →6H 13/2. The optimal amount of Dy3+ was determined to be 5 mol %, with concentration quenching attributed to quadrupole–quadrupole interaction. Y 1.95 Si 2 O 7 :5 mol % Dy3+ phosphor possessed activation energy of 0.2503 eV and demonstrates good thermal stability. Thus, these results indicate that the synthesized Y 2 Si 2 O 7 :Dy3+ phosphors are well suited for white light applications. [ABSTRACT FROM AUTHOR]

• An improved multi-channel singular spectrum analysis method is proposed, which is ranked by the standard spectrum of singular value energy. • A dissipated energy function is proposed that can be well used for the determination of the dominant oscillatory section of the grid. Moreover, this energy function can be effectively extended to power systems with power electronic devices. • The area equivalent model can be updated periodically using updated PMU data to accommodate topology changes. The identification of dominant oscillation paths is one of the key aspects in studying the stability of inter-area power grids. This paper proposes an improved multi-channel singular spectrum analysis (MSSA) algorithm combined with dissipative energy to identify dominant oscillation section in power systems. First, an improved MSSA method is introduced, which determines the order using the singular value energy spectrum and can effectively identify inter-area oscillation modes in power systems. Second, an energy function analysis method is proposed, which is well-suited for determining dominant oscillation section in power systems. This method is minimally affected by time-varying and nonlinear factors and allows for the visualization of generator states. Finally, the IEEE 68-bus system is used to construct an equivalent model, demonstrating the method's versatility. Simulation results validate the noise resistance, computational efficiency, and applicability to topology change scenarios of the proposed method. This method can accurately analyze inter-area oscillation modes and help to establish the dominant oscillation section. [ABSTRACT FROM AUTHOR]

Monolayer niobium oxychloride (NbOCl 2), synthesized as reported in Guo et al. (2023), exhibits potential as a quantum light source. Our density functional theory (DFT) study assesses niobium oxyhalide monolayers (NbOX 2 , X = Cl, Br, I), focusing on quantum point defects' impact on electronic behavior. Vacancy-induced magnetism is observed in these monolayers; oxygen and niobium vacancies trigger magnetism, contrasting with non-magnetic halogen vacancies. The energy difference between magnetic and non-magnetic states is contingent on vacancy type and halogen mass, with oxygen vacancies showing an energy increase and niobium vacancies a decrease as halogen mass rises. Doping effects are notable; halogen and oxygen vacancies result in n-type doping, while niobium vacancies lead to p-type. In the NbOI 2 monolayer, the Nb + 1 vacancy is found to be more stable than the neutral vacancy. Conversely, for other charge states and vacancies, the neutral state remains the most stable. Magnetization is significantly enhanced by oxygen and halogen bivacancies, with spin energy difference and magnetization scaling with the halogen's atomic number. The optical spectrum analysis shows that defects can extend absorption into the infrared, with anisotropic optical properties dependent on light polarization direction. These findings highlight the tunability of niobium oxyhalide monolayers for quantum technology applications, emphasizing the role of defects in modulating electronic and optical characteristics. • The electronic and optical properties of both perfect and defective NbOX 2 (X: Cl, Br, I) monolayers are thoroughly investigated using density functional theory. • Oxygen and niobium vacancies are shown to induce local magnetic moments within the monolayer structure. • Analysis indicates that the positively charged niobium state is energetically more favorable than the neutral state in NbOI 2. • The presence of halogen–oxygen bivacancies is found to significantly enhance magnetization in the monolayers. • Vacancies are capable of shifting the optical absorption edge towards the infrared (IR) region, highlighting potential applications in solar cells and optoelectronics. [ABSTRACT FROM AUTHOR]

Luminescence is a powerful tool to analyse various types of defects in a wide range of materials; it is often applied for silica, which is a broadly used material in photonics, microelectronics, nuclear energy industry, optoelectronics and other important technological applications. In this work, a single crystalline (0001) α-SiO 2 (quartz) sample has been investigated by the ionoluminescence (IL) method. In this case, intense emitted light can be observed when a 2 MeV He+ beam reaches the quartz sample. Three emission bands were found at 1.45 eV, 1.76 eV and 2.34 eV, the corresponding defects were identified as an unknown origin, non-bridging oxygen hole centres (NBOHC), and self-trapped excitons (STEs), respectively. The evolution of the defect-related IL peaks was determined as a function of He+ irradiation fluence. To perform accurate data evaluation, the instrumental function of the applied IL set-up (collimator, optical fibers and spectrometer) was determined and taken into account. The importance of methodological issues in the IL measurement (including set-up, sample holder and proper beam settings) was also discussed. The described steps of system calibration and data evaluation are indispensable for IL spectrum analysis leading to a detailed understanding of defect evolution taking place during the ion-beam irradiation process. [ABSTRACT FROM AUTHOR]

Local atomic environment (LAE) representations have enabled a deeper understanding of complex alloy configurations, by enabling machine learning and data science approaches to previously inaccessible tasks. For example, recent developments have used site-centered descriptors to interpret the structurally complex LAEs present in polycrystalline grain boundary (GB) networks and learn the spectrum of grain boundary segregation energies available across many binary alloys. One limitation of many LAE representations is their "site-focus", which limits their ability to capture chemical complexity at the atomic scale. This paper introduces a modified "bond-focused" LAE representation, which is used to assess pair-wise solute interactions in the topologically complex environments of grain boundaries. This approach opens the pathway to learning models, which we develop here to construct a large-scale database of spectral parameters describing grain boundaries in binary alloys. [Display omitted] [ABSTRACT FROM AUTHOR]

The decomposition of multichannel signals into their underlying components is a problem of key interest in many disciplines. It involves the analysis of nonlinear and nonstationary time series and the need to identify the most relevant frequencies of oscillation that characterize the extracted underlying components, disentangling their sources of variation and assessing their relative phase or cyclical position. Many successful multivariate methods for signal extraction identify the frequencies after the decomposition problem has been solved. They may not be able to easily recognize the full information contained in each frequency though. Within the context of Multivariate Singular Spectrum Analysis, this paper develops Multivariate Circulant Singular Spectrum Analysis (MCiSSA), a self-identifying procedure for the frequencies without the need of further processing the data. Seeing MSSA procedures as a generalization of principal component analysis that includes series and their lags, the key for the self-identification of the frequencies is the use of block circulant matrices of second moments, instead of the usual variance–covariance matrix, that allows matching eigenvalues with frequencies. Additionally, MCiSSA performs a double diagonalization of that block circulant matrix that uncovers cross section relations per frequency. We show the performance of MCiSSA through several synthetic examples that include latent signals modulated both in amplitude and frequency. To do so, we compare the Root Mean Squared Error (RMSE) of the adjusted series to the simulated ones across several multivariate alternatives being MCiSSA the best option with RMSE 40% lower than the second best option in the first example and 24% in the second example. Finally, we apply MCiSSA to two real data applications: energy commodity prices and temperatures. The first application shows how MCiSSA helps to understand the main drivers and co-movements of primary energy commodity prices at various frequencies that are key to assess energy policy at different time horizons. We find that prices are dominated by the European gas at all frequencies. More specifically, the volatility of the price of the European gas accounts for almost half of the cyclical variability in the system. The second application shows the growing trend of temperatures in 12 South European cities (on average, trends have increased 1.77 Celsius degrees between 1950 to 2022) and their changing pattern in seasonality. • New MCiSSA is a multichannel signal extraction method for time series based on SVD. • It matches in an automated way singular values with frequencies. • It shows the data sources of variation by frequency & assess their relative position. • It compares favorably with other multichannel techniques in terms of RMSE. • It helps to understand decoupling in energy commodity prices & climate change. [ABSTRACT FROM AUTHOR]

Flexible low dielectric constant (low- k) SiCOH thin films were fabricated onto flexible indium tin oxide coated polyethylene naphthalate (ITO/PEN) substrates using plasma-enhanced chemical vapor deposition (PECVD) of a tetrakis(trimethylsilyloxy)silane (TTMSS) precursor. RF plasma powers of 20 and 60 W were utilized for the deposition. The k -values of the pristine SiCOH films deposited at 20 and 60 W were 2.46 and 2.00, respectively. Both films showed hydrophobic surfaces. An inductively coupled plasma-reactive ion etching (ICP-RIE) process was then performed on the flexible SiCOH thin films using CF 4 , CF 4 + O 2 , and CF 4 + Ar. The surface wettability of the films increased substantially following etching, with many of the etched films being considered hydrophilic. The Fourier transform infrared (FTIR) spectra of the pristine films identified four prominent absorption bands as CH x stretching, Si-CH 3 bending, Si-O-Si stretching, and Si-(CH 3) x stretching vibration modes. After the etching process, the peak area ratios of Si-O-Si stretching mode increased and those of Si-(CH 3) x stretching mode decreased. The X-ray photoelectron spectroscopy (XPS) spectra analysis determined significant concentration of fluorine on the surface of the film following etching. From the high-resolution XPS scan, it was found that the peak intensity of the C1s and Si2p peaks decreased after etching process and the peak center of the F1s peak shifted depending on etching chemistry. The k -values of the films at 20 W were fairly consistent while those of the films at 60 W increased significantly following the etching process. The increase in k -value after etching for the films at 60 W correlated with surface hydrophilicity, increase in the refractive index, and change in the peak area ratios of Si-O-Si and Si-(CH 3) x stretching modes in the FTIR spectra. [Display omitted] • Flexible low- k thin films were synthesized by chemical vapor deposition. • Fluorocarbon-based plasma was adopted for etching of flexible low- k films. • Change in chemical structure of flexible low- k films depended on etching chemistry. • Dielectric constant after etching was related to the surface characteristics. [ABSTRACT FROM AUTHOR]

Spectral intensity drift is a frequent issue in analytical processes, especially in long time excitation scanning for large size metal materials, which can significantly adversely impact the accuracy and stability of analysis results. Spectral intensity drift correction is the process of preprocessing spectral data using mathematical algorithms in order to facilitate the subsequent qualitative and quantitative analysis of spectra, especially in combination with stoichiometric methods. Up to now, spectral intensity drift correction within prolonged excitation has not been reported yet. We propose an intensity drift correction method for element content of large-size samples using the Spark Mapping Analysis for Large Samples (SMALS) technique. By considering the row-by-row and column-by-column mapping modes of the SMALS, this includes curve fitting baseline correction for in-row and in-column correction, as well as total average value correction for inter-row and inter-column correction. The final measurement values are derived by coupling rows with columns. The careful implementation of correction steps can enhance baseline correction performance, effectively reducing measurement errors a drift errors. Application of this method to characterize the cross and longitudinal sections of an oversized steel billet indicates high agreement with composition distribution obtained by micro-beam X-ray fluorescence (μ-XRF). The corrected longitudinal and cross-sectional data also exhibit strong alignment. Comparison of statistical analysis results pre- and post-correction demonstrates significant improvements in the clarity of elements segregation pattern. This intensity drift correction method not only enhances the spectral quality but also improves the accuracy and robustness of quantitative and qualitative spectral analysis. This study contributes to establishing a robust foundation for component characterization of large-size metal materials using the SMALS technique. The novel spectral intensity correction method shows theoretical significance and practical value for large-scale, long-duration excitation scanning analysis. [Display omitted] • The measurement error was eliminated by in-row/in-column, inter-row/inter-column correction and complementary coupling. • The intensity drift correction method significantly improves the accuracy and stability of analysis results of the SMALS. • This work laid a firm foundation of component characterization for large-size metal material using the SMALS. [ABSTRACT FROM AUTHOR]

Herein, six previously undescribed steroids (1–6), were isolated from leaves and twigs of Aphanamixis polystachya (Wall.) R. N. Parker (Meliaceae). Their structures were elucidated by comprehensive spectroscopic analysis, including HRESIMS, 1D and 2D NMR, UV, and IR. Antiviral activity of these compounds were evaluated. Compounds 1–6 showed varying degrees of inhibitory activity against the severe acute respiratory syndrome coronavirus 2 main protease (SARS-CoV-2 Mpro) at 200 μ M. [Display omitted] [ABSTRACT FROM AUTHOR]

Diabetes is a significant global health challenge, affecting circa 540 million adults worldwide. Dioscorea dumetorum , a Nigerian folkloric antidiabetic plant is severely understudied in terms of its bioactive phytochemical constituents. Antidiabetic guided isolation of the tubers and peels of D. dumetorum afforded three phytoecdysteroids bearing a cis -fused A/B ring junction including two new ones: 24-hydroxymuristerone A (1) and 24-hydroxykaladasterone (2), alongside the known muristerone A (3). Additionally, 2,2′,7,7′-tetramethoxy-[1,1′-biphenanthrene]-4,4′,6,6′-tetraol (4), batatasin I (5), and dihydroresveratrol (6) were isolated. Structural elucidation relied on spectroscopic, spectrometric methods, and comparison with existing literature. The ethyl acetate extracts of both the tubers and peels of D. dumetorum exhibited the highest phenolic content, correlating with potent antioxidant activity. Compounds 4 (IC 50 = 0.10 mg/mL) and 6 (IC 50 = 0.22 mg/mL) demonstrated superior inhibitory effects against α-glucosidase compared to acarbose (IC 50 = 0.63 mg/mL). In contrast, compounds 3 , 4 , and 5 showed reduced α-amylase inhibition, with IC 50 values of 2.58, 3.78, and 1.12 mg/mL, respectively, compared to acarbose (IC 50 = 0.42 mg/mL). These observed bioactivities validate the traditional use of D. dumetorum and contribute valuable phytochemical data to the scientific literature of the species. [Display omitted] • Evidence of antidiabetic properties of D. dumetorum is established through a bioactivity-guided fractionation approach. • Two new phytoecdysteroids and the known phytoecdysteroid muristerone A (3) were isolated. • Three known polyphenols were isolated. • Compounds 4 and 6 display higher inhibitory activity against α-glucosidase than the positive control acarbose. • Compounds 4 and 5 display a high antioxidant activity, in the same range as ascorbic acid. [ABSTRACT FROM AUTHOR]

Ligularia fischeri Turcz. is a medicinal plant for the treatment of inflammation in China and Korea. Its chemical components in anti-sepsis activity and the related molecular mechanisms remain unknown yet. In this study, two undescribed eremophilane sesquiterpenoids fischerins A (1) and B (2), together with 8 known sesquiterpenoid derivatives (3 – 10), were isolated from the whole plant of L. fischeri. Their structures were identified by detailed spectroscopic and ECD analyses. 3-Oxo-8-hydroxyeremophila-1,7(11)-dien-12,8-olide (6) showed the most inhibitory effect on NO production in LPS-stimulated RAW 264.7 cells with the IC 50 value of 6.528 μM. Meanwhile, compound 6 also decreased the mRNA expression of pro-inflammatory factors IFN- γ , IL-1 β , IL-6 and TNF- α via downregulating NF-κB signaling pathway in vitro. Furthermore, compound 6 reduced the mortality, murine sepsis score, the serum TNF- α level and organic damage in a mouse model of sepsis. These findings indicated that compound 6 possessed the potent anti-inflammatory activity and had the potential as a promising drug candidate for sepsis therapy. [Display omitted] • Two undescribed eremophilane sesquiterpenoids were isolated from Ligularia fischeri. • Compound 6 showed the anti-inflammatory effect in LPS-induced RAW264.7 cells. • Compound 6 regulated NF-κB pathway in vitro. • Compound 6 showed protective effects against CLP-induced sepsis in vivo. [ABSTRACT FROM AUTHOR]

Three new meroterpenoids (1 – 3) and ten known ones (4 – 13) were obtained from the endophytic fungus Talaromyces primulinus H21 isolated from the plant of Euphorbia sikkimensis. Their structures including their absolute configurations were elucidated by extensive analysis of spectroscopic data such as HR-ESI-MS, 1D/2D NMR, and X-ray diffraction of single crystal together with comparison of experimental ECD with calculated ECD. All compounds were examined for their inhibitory effects on nitric oxide (NO) production induced by lipopolysaccharide (LPS) in RAW264.7 cells, and compounds 3 , 9 , 12 , and 13 exhibited certain inhibition on NO production, with IC 50 values of 27.19, 41.55, 25.23, and 24.71 μM, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

In our continuous work on the isolation of endophytes, the endophytic fungal strain YIMF00209 was obtained from the roots of Gmelina arborea , which is an ethnic medicinal plant mainly distributed in Southeast Asia. The fermentation extracts of the strain exhibited significant antimicrobial activities against Staphylococcus aureus , Fusarium solani , and Escherichia coli. Based on morphological characteristics and phylogenetic analysis, it was identified as Talaromyces muroii. Four new polyketides, talaromurolides A-D (1 – 4), along with 26 known compounds (5 – 30), were isolated from the culture broth of the strain in two different media. Their structures were identified based on HRESIMS, NMR, and CD spectral data. Among them, compounds 2 , 4 – 6 , 19 , 22 , 24 , 27 , 28 , and 30 were isolated from the fermentation broth in CYM medium; compounds 1 , 3 , 7 – 18 , 20 , 21 , 23 , 25 , 26 , and 29 were obtained from the fermentation broth in PDB medium; and compounds 2 , 5 , and 30 were existed in both two media. Compounds 6 – 9 , 12 , 16 , 20 , 21 , 23 , 25 , and 29 were obtained from the genus Talaromyces for the first time. The antimicrobial activities of several compounds were assayed against six pathogens. Compound 1 exhibited inhibitory activities against S. aureus , E. coli , Candida albicans , Salmonella typhimurium , and Botrytis cinerea with MIC value of 64 μg/mL. Compound 25 exhibited antibacterial activity against E. coli with MIC value of 32 μg/mL. [Display omitted] [ABSTRACT FROM AUTHOR]

Four previously undescribed sesquiterpenoids (1–4), including two natural guaiane-type sesquiterpenoids (1 – 2), a rearranged guaiane-type sesquiterpenoid (3), and a norsesquiterpenoid (4), were isolated from the ethanol extract of the aerial parts of Pogostemon cablin (Blanco.) Benth. Their chemical structures were determined based on extensive spectroscopic data analysis, including UV, IR, NMR, HRESIMS, and CD spectroscopy. Compound 1 exhibited a good hypoglycemic activity with glucose uptake of 124.3% and 131.2% in myotubes, respectively, at the concentrations of 20 and 40 μM and showed no cytotoxicity. These findings provide a material basis for further research on P. cablin. Four previously undescribed sesquiterpenoids (1–4), including two natural guaiane-type sesquiterpenoids (1 – 2), a rearranged guaiane-type sesquiterpenoid (3), and a norsesquiterpenoid (4), were isolated from the ethanol extract of the aerial parts of Pogostemon cablin (Blanco.) Benth. Compound 1 exhibited a good hypoglycemic activity at the concentrations of 20 and 40 μM and showed no cytotoxicity. [Display omitted] [ABSTRACT FROM AUTHOR]

Three undescribed phenols, mandshusica C-E (1 – 3) and a new lignan, mandshusica F (5), along with six known compounds (4 , 6 – 10) were isolated from the roots and rhizomes of Clematis terniflora var. manshurica (Rupr.) Ohwi. Their structures were elucidated by extensive spectroscopic analysis as well as NMR and ECD calculations. Moreover, the possible biosynthetic pathways of compounds 1 – 3 were also discussed. All compounds were evaluated for their anti-inflammatory activities in LPS-induced RAW 264.7 cells. Compounds 1 , 3 , 4 significantly reduced the levels of NO and TNF-α, while compounds 2 and 8 significantly inhibited NO production in LPS-induced RAW264.7 cells. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • A deep learning-based model for the automatic removal of scattering in fluorescence spectra has been developed. • Using the DeepLabV3+ model to segment scattering in three-dimensional fluorescence spectra. • Using GLCIC network to repair fluorescent spectrum of scattering areas. • PARAFAC successfully resolved the component spectra after the model removes scattering. Three-dimensional excitation–emission matrix fluorescence spectroscopy is often plagued by scattering effects, mainly Rayleigh and Raman scattering, and thus must be pre-processed for de-scattering before spectral analysis. In this study, a new method based on deep learning was proposed to automaticly remove the scattering from fluorescence spectra. First, the semantic segmentation model Deeplabv3+ was used to realize the segmentation of the scattering region in the original fluorescence spectrum and compared with other segmentation models. The results show that the mean intersection over union (mIoU) of this model is 89.58 % and its Accuracy is 95.40 %, which are better than those of the other models. Then, the Globally and Locally Consistent Image Completion (GLCIC) network was used to repair the spectral energy of the scattering areas. Model effectiveness in scattering removal is evaluated using metrics such as mean absolute error, mean relative error, structural similarity, and peak signal-to-noise ratio. Furthermore, this study employs PARAFAC for component analysis of the spectra after scattering removal by the model, comparing them with actual components, all yielding correlation coefficients greater than 0.99. The results show that compared with the traditional scattering-removal method based on the mathematical model, the proposed method can automatically remove scattering areas in batch samples' fluorescence spectra, without the need for manual parameter setting or other processes. This improves scattering removal efficiency, enhances the simplicity, and speed of fluorescence detection technology. [ABSTRACT FROM AUTHOR]

• A cascaded high-order tunable multi-wavelength random Raman fiber laser covers 1.1–1.5 μm band is demonstrated. • The effectiveness of the few-mode fiber-based filter on the multi-wavelength random Raman lasing stimulation is investigated. • The method of combination of high-nonlinear dispersion-shifted fiber and standard single-mode fiber to enhance the flatness of the multi-wavelength random lasing is proposed and verified. In recent years, multi-wavelength fiber lasers have become one of the research hotspots and have been extensively applied in optical fiber communication systems. However, the presented multi-wavelength fiber lasers mainly operate in the 1.5 μm band. In this paper, a few-mode fiber filter-based cascaded high-order tunable multi-wavelength random Raman fiber laser (MWRRFL) is demonstrated, for the first time, in which a tuning range covers the 1.1–1.5 μm band. In the half-open MWRRFL, a few-mode fiber-based intermodal interferometer filter is inserted in the point reflector as a wavelength selector. The synergetic effect including high Raman gain and Rayleigh backscattering intensity in the hybrid of dispersion-shifted fiber and standard single-mode fiber is employed. It presents the capability for flat multi-wavelength random lasing stimulation. As a result, the wavelength channel number of the 6th-order random lasing is 6, with a maximum power variation of 4.66 dB and good temporal stability. The proposed cascaded tunable MWRRFL could provide a versatile source for optical fiber communication, optical fiber sensing, spectrum analysis, etc. [ABSTRACT FROM AUTHOR]

This paper explores fractional spectra of signals after two types of nonuniform samplings in the presence of timing offset. Both cases of bandlimited and multiband signals in the fractional Fourier domain are considered, based on which we provide conditions for reconstructing the spectrum and devise relevant methods for compensating the bias introduced by timing offset. To obtain these goals, we divide the nonuniformly sampled signal into uniformly sampled sub-sequences and establish the relationship between the discrete-time fractional Fourier transforms (DTFrFTs) of them and the FrFT of the original signal. It indicates that the obtained DTFrFTs consists of periodic replicas of the FrFT for the original signal with each replica being biased by a phase term introduced by timing offset. Based on the matrix form of the relationship, we implement spectral reconstruction of bandlimited signals under certain conditions by performing the inverse of a matrix determined by the phase terms. Different from bandlimited signals, the DTFrFTs of uniformly sampled sub-sequences for multiband signals are studied within disjoint fractional frequency sub-intervals separated by aliasing boundaries. Moreover, inverse of a matrix with fewer columns and rows is utilized to reconstruct the spectrum. Simulations verify the effectiveness of the proposed methods. • The effect of timing offset in multicoset sampling has been studied in terms of FrFT. • New methods for spectrum analysis have been devised in the presence of timing offset. • The proposed methods have low computational complexity and high accuracy. [ABSTRACT FROM AUTHOR]

[Display omitted] • Dy3+, Sm3+ co-activated K 4 Ca(PO 4) 2 phosphors made via Co-precipitation are pure, nano-sized, and suitable for luminescence. • UV excited singly doped ions show peaks transitioned 4F 9/2 →6H 15/2 ,6H 13/2 for Dy3+ and 4G 5/2 →6H 5/2 ,6H 7/2 ,6H 9/2 for Sm3+. • Spectral overlap condition satisfied and Energy transfer occurrence is observed for Dy3+ & Sm3+ ions. • Red deficiency is minimized by substitution of Eu3+ ions as depicted in co-doped emission spectra and CIE. • Applications for warm white emitting nano phosphor may be possible in WLED's, displays and solid-state lightings. Highly luminescent K 4 Ca(PO 4) 2 : RE3+ (RE = Dy3+, Sm3+) materials were synthesized by Co-precipitation method. structural and morphological analysis depicts phase purity and nano structured particles. The study investigated the energy transfer mechanism among dopant ions and examined the impact of concentration on luminescence. Photoluminescence (PL) spectrum analysis revealed that upon near-ultraviolet excitation, K 4 Ca(PO 4) 2 : Dy3+, Sm3+ emission assigned to transitions of different Characteristic peaks observed in region spanning 480 to 650 nm. Furthermore, photometric properties were investigated suggesting synthesized phosphor have application in preparation of white LEDs. [ABSTRACT FROM AUTHOR]

• Hydration damage of conglomerate is jointly controlled by pore and mineralogical factors; • High pore tortuosity directly lead to high hydration damage; • Pores have a greater impact on hydration damage than mineralogical factors. This study endeavors to delve into the microscopic mechanisms of hydration-induced damage in tight conglomerates. Initially, we obtained data on the micro-morphology, elemental composition, and mineral composition of the conglomerate using field emission scanning electron microscopy imaging, EDS energy spectrum analysis, X-ray diffraction mineral experiments, and image fine processing techniques. Subsequently, a conductivity meter was employed to gauge solution conductivity throughout the process, while a high-resolution camera monitored changes in appearance morphology. The hydration samples were then re-examined using field emission scanning electron microscopy imaging and EDS energy spectrum experiments. Our analysis reveals that the extent of hydration-induced damage in the conglomerate samples correlates with their pore and fracture parameter characteristics, as well as their elemental and mineral composition. Notably, samples with higher surface porosity and tortuosity are more susceptible to hydration-induced damage, whereas those with higher circularity, solidity, and degree of orientation of the angle exhibit lower susceptibility. The circumference and aspect ratio display weak positive and negative correlations with the degree of hydration-induced damage in the conglomerate, respectively. However, the detailed mechanism warrants further investigation. Furthermore, samples with elevated montmorillonite content are more prone to hydration-induced damage, whereas those with increased Fe and illite content are less likely to suffer from hydration-induced damage. These findings offer novel insights into the microscopic mechanisms underlying dynamic hydration-induced damage in conglomerate samples and hold significant implications for guiding the efficient development of conglomerate oilfields. [ABSTRACT FROM AUTHOR]

In this paper, we investigate and report the effects of Si4+/Al3+ (SiO 2 /Al 2 O 3) molar concentration ratio on the self-reduction process of Yb3+ to Yb2+ ions and upconversion (UC)-, visible (VIS)- emission spectra, direct optical bandgaps (DOB), indirect optical bandgaps (IOB) of Bin+/Ybm+, Er3+/Bin+, and Er3+/Bin+/Ybm+ (n, m = 3, 2) co-doped SiO 2 –Al 2 O 3 –MgO–TiO 2 (SAMT) magnesium aluminum silicate glasses. The valence states of the bismuth (Bi), and Ytterbium (Yb) elements in the raw materials mixture existing in the SAMT glass were determined using X-ray photoelectron spectroscopy (XPS) spectra analysis. With the increase of Al3+ molar concentration from 16 mol. % up to 20, 24, 28 and 32 mol. % corresponding to the Si4+/Al3+ (SiO 2 /Al 2 O 3) molar concentration ratio of 3.4, 2.5, 1.9, 1.5, and 1.2, the self-reduction process of Yb3+ to Yb2+ ions was enhanced and thus significantly affected the DOB, IOB, the intensities of UC-, VIS- emission spectra of Bin+/Ybm+, Bin+/Er3+, and Bin+/Er3+/Ybm+ (n = 2, 3) co-doped SAMT glasses under excitation of 473 nm, 808 laser diode (LD) and 980 nm LD. In addition, the CIE 1931(x, y) color coordinates for VIS- and UC- emissions spectra of Bin+/Ybm+, Bin+/Er3+ (n = 2, 3) co-doped SAMT under excitation of 473 nm and 808 nm LD are also calculated and determined in the CIE 1931(x, y) chromaticity diagram. • Effect of Si4+/Al3+ ratio on the self-reduction process of Yb3+ to Yb2+ ions were investigated. • XPS results determined existence of Bi3+, Bi2+, Yb3+, and Yb2+ ions in SiO 2 –Al 2 O 3 –MgO–TiO 2 glass. • CIE1931 for VIS, UC emissions of Bin+/Er3+/Ybm + under excitation of 473, 808 nm were determined. [ABSTRACT FROM AUTHOR]

Silicate-Titania (SiTi) glass-ceramics doped with Pr3+ (0.6, 1.6, 2.4 and 3.6 mol%) ions were prepared by sol-gel technique. The materials were characterized by powder XRD, FTIR, TEM, EDX, Optical absorption and Photoluminescence spectroscopy. The identification of non-bridging oxygen (NBO) formation and the removal of OH groups are validated through analysis of the FTIR spectra. Additionally, measurements using XRD and TEM showed that the samples contain nano-sized crystallites. The three phenomenological Judd–Ofelt (J–O) intensity parameters Ω 2 , Ω 4 , and Ω 6 were obtained and used to analyze different radiative characteristics for the fluorescence levels of Pr3+ in the glass ceramic, including radiative lifetime, branching ratio, radiative transition probability and stimulated emission cross-section. Several emissions were observed in the visible region, among which the 1D 2 →3H 4 in the orange-red region is the most intense. All of these reported branching ratios, stimulated emission cross-sections, and visible emission spectra point to the possibility of employing them as red region lasers. The CIE chromaticity coordinates from all of the emission spectra were also assessed to determine if these materials are suitable for orange-red phosphors. According to CIE chromaticity investigations, 1.6 mol% of Pr3+ ion concentration is ideal for SiTiPr glass-ceramic for use as red phosphors and possibly red lasers. • SiO 2 –TiO 2 glass ceramics doped with Pr3+ are synthesized by sol-gel technique. • TiO 2 nanocrystals of size around 10–20 nm are formed. • Judd-Ofelt parameters and radiative parameters are calculated. • Strong emissions in the orange-red region are observed under blue excitation. • Cross-relaxation reduces luminescence at high Pr3+ concentration. [ABSTRACT FROM AUTHOR]

We propose an alternative method for processing infrared thermography (IRT) data based on a thermal 1-layer model. The method is based on the analogy of the Shock Response Spectrum (SRS) analysis for mechanical systems (ISO 18431). A thermal Q-factor, similar to the resonance sharpness (Q-factor) of a mechanical oscillator, is introduced as a parameter for selecting a specific thermal 1-layer model. Two main aspects of this method and corresponding properties have been considered: the strictly model-based treatment of this methodology and an empirical introduction of additional bandpass filters. The method is validated with two practical examples: for a homogeneous polymer sheet with blind holes and an inhomogeneous plate made of carbon fiber reinforced polymer (CFRP) with artificial defects, the capability of defect detection is compared with established methods. The comparison of the results with the commonly used data processing methods of IRT as Pulsed Phase Thermography (PPT) and Modified Differential Absolute Contrast (MDAC) shows equivalent or sometimes improved performance. [ABSTRACT FROM AUTHOR]

Sleep staging plays an important role in the diagnosis and treatment of clinical sleep disorders. The sleep staging standard defines every 30 seconds as a sleep period, which may mean that there exist similar brain activity patterns during the same sleep period. Thus, in this work, we propose a novel time-related synchronization analysis framework named time-related multimodal sleep scoring model (TRMSC) to explore the potential time-related patterns of sleeping. In the proposed TRMSC, the time-related synchronization analysis is first conducted on the single channel electrophysiological signal, i.e., Electroencephalogram (EEG) and Electrooculogram (EOG), to explore the time-related patterns, and the spectral activation features are also extracted by spectrum analysis to obtain the multimodal features. With the extracted multimodal features, the feature fusion and selection strategy is utilized to obtain the optimal feature set and achieve robust sleep staging. To verify the effectiveness of the proposed TRMSC, sleep staging experiments were conducted on the Sleep-EDF dataset, and the experimental results indicate that the proposed TRMSC has achieved better performance than other existing strategies, which proves that the time-related synchronization features can make up for the shortcomings of traditional spectrum-based strategies and achieve a higher classification accuracy. The proposed TRMSC model may be helpful for portable sleep analyzers and provide a new analytical method for clinical sleeping research. • A novel time-related synchronous analysis model is proposed for sleep staging. • The proposed TRMSC model significantly improves the sleep staging performance. • The TRMSC provides an effective solution for sleep staging researches and applications. [ABSTRACT FROM AUTHOR]

The adoption of sensors and other technologies in modern agricultural systems has led to an increase in data availability for the optimization of crop management. Soil moisture (SM) forecasts, which heavily depend on the availability of SM sensor data, have the potential to reveal underlying processes that are not easily identified through day-to-day field management. The SM data's complexity and the temporal and spatial dynamic interrelation with other environmental factors present challenges that make it necessary to implement preprocessing techniques and models capable of adapting to the changing characteristics of the data. Recent studies have suggested that combining data preprocessing techniques, such as input time series (TS) decomposition, with ensemble forecasting models can reduce data complexity, improve forecast accuracy, and provide the model with the necessary robustness against extreme input values. In this study, we assess the efficiency of Singular Spectrum Analysis (SSA) and Ensemble Empirical Mode Decomposition (EEMD) as input TS decomposition techniques to improve the preprocessing and forecasting performance of machine learning (ML) and deep learning (DL) algorithms. The results of this study suggest that the use of EEMD could have an average reduction of 44% in absolute errors while improving the interpretability of the data. In a case study on citrus production in Southeast Florida, we demonstrated that using EEMD as a preprocessing method significantly reduces prediction errors. This reduction could allow a substantial increase in water savings when users implement SM forecasts for irrigation scheduling. • We evaluated SSA and EEMD for ML/DL soil-moisture (SM) forecasting. • EEMD incorporation led to a 44% error reduction compared to no preprocessing. • EEMD effectively isolated nonstructural components in the time series. • EEMD outperformed SSA due to high-frequency variation in SM-TS. • Adding EEMD could lead to significant water savings in citrus irrigation. [ABSTRACT FROM AUTHOR]

• Four hemicyanines with different structures are synthesized and characterized successfully, and the single crystal structure are collected. • Through the single crystal data, the electrostatic potential, HOMO&LUMO and other information are obtained. • The optical properties of hemicyanines are analyzed by combining the calculated results and experiments. Four hemicyanine dyes (1–4) containing indole group and bearing different substituent in phenyl ring were successfully synthesized. In this study, NMR, elemental analysis and single-crystal analysis were employed to confirm the structures of four newly synthesized compounds. Additionally, electrostatic potential calculations were conducted to enhance the dataset of hemicyanines comprehensively. Furthermore, the optical properties of the resulting hemicyanines were evaluated in organic solvents. The elucidation of the single-crystal structure of the material allows for a deeper understanding of the relationship between its intrinsic structure and properties. This systematic investigation represents an essential initial step towards the development of related photoactive agents for light-based diagnostic and therapeutic applications. [Display omitted] [ABSTRACT FROM AUTHOR]

The main problem that arises in the mobility spectrum analysis (MSA) is the appearance of additional spectral lines, which are not related to real physical processes and transport mechanisms. The paper proposes a simple model of systematic errors occurring in magneto-transport measurements and investigates their impact on this adverse phenomenon. The analysis was carried out for typical mobility spectra characteristic of single- and dual-carrier transport. On the basis of numerical experiments, heuristic rules were formulated that can be helpful in distinguishing real spectral lines from false peaks caused by measurement errors. • A simple model of systematic errors in transport measurements has been proposed. • The impact of these errors on the mobility spectra has been investigated. • In the case of two-carrier transport, one additional spectral line always shows up. • Such artificial (ghost) peak has unique properties that allow it to be identified. [ABSTRACT FROM AUTHOR]

The Qiye Shen'an tablet is formulated using total saponins extracted from Notoginseng stems and leaves. At present, the study on its chemical composition remains scarce and the quality control indicators are limited, which seriously hindering the effective quality control and clinical research. Hence, this study aims to comprehensively identify and characterize the Qiye Shen'an tablet while controlling its main component contents. To achieve a comprehensive understanding of this tablet, an ultra-high performance liquid coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) method was employed for its separation and characterization. Through the analysis of 99 batches of Qiye Shen'an tablet produced by 9 enterprises, the characteristic quantitative components were further obtained. A total of 113 compounds were characterized and identified, among which 17 representative compounds were selected, and the ultra-high performance liquid-triple quadrupole tandem mass spectrometry (UPLC-TQS-MS/MS) method was established for further quantitative determination. It has been successfully applied to the content determination of 99 batches of Qiye Shen'an tablet, and a new quality control method is being formed. This study provides a new method for chemical spectrum analysis and determination of labeled compounds of Qiye Shen'an tablet, and lays a solid foundation for further study of potential active ingredients and comprehensive quality evaluation. • The qualitative analysis of Qiye Shen'an tablet was reported for the first time. • A total of 113 compounds of Qiye Shen'an tablet were deduced by UPLC Q-TOF/MS. • Seventeen representative compounds were quantified simultaneously in 38 min. [ABSTRACT FROM AUTHOR]

It can be foreseen that the global demand for natural gas (NG) will show an increase trend in the upcoming decades. Solidified Natural Gas (SNG) having a high energy density provides an alternative solution for the storage and transportation of NG. In this study, our focus lies on investigating the impact of 1,3-dioxane and L-tryptophan on mixed CH 4 /dioxane hydrate formation from multiple perspectives including thermodynamic, Raman spectra, and kinetics. The thermodynamic experimental results confirmed that the mixed CH 4 /dioxane hydrate can form at a moderate conditions and shows high dissociation enthalpies. A thermodynamic model based on van der Waals and Platteeuw model was applied for predicting equilibrium conditions of the Hydrate–Liquid–Vapor system, yielding an average absolute deviation ranging from 1.7% to 3.9%. Raman spectra results re v ealed that there is a two–stage growth mechanism for mixed CH 4 /dioxane hydrates. Kinetic results demonstrated that the system of CH 4 /5.56 mol% dioxane/water shows the highest gas uptake of 91.1 (±0.5) v /v at 287.15 K and 10.0 MPa, compared to other systems. Moreover, the addition of 1000 ppm L-tryptophan can reduce the time to reach 90% uptake (t 90), showing a value of 19.9 (±1.8) minutes. The findings derived from this research are instrumental in developing the SNG technology. [Display omitted] • Methane storage via mixed CH 4 /dioxane hydrates was investigated. • A thermodynamic model for mixed CH 4 /dioxane hydrate was developed. • In-situ Raman spectra analysis of hydrate formation was conducted. • The effects of L-tryptophan on hydrate formation kinetics were studied. • Up to 91.1 v /v of methane uptake is achieved at moderate conditions. [ABSTRACT FROM AUTHOR]

The utilization of near-infrared (NIR) spectroscopy, in conjunction with chemometric techniques, has been widely used in a variety of sectors, including agricultural production and pharmaceutical production. Nevertheless, the laborious and arduous procedure of gathering samples and evaluating their physicochemical properties leads to relatively limited training set sizes for modeling. This problem severely limits the optimization and practical application of NIR spectrum analysis models. The Safer Active Semi-Supervised Sample Augmentation Learning Model (Safer-AS3A) proposed in this paper tries to address the problem by incorporating active learning (AL) and semi-supervised learning (SSL) techniques. Experiments were conducted on two sets of publicly available NIR spectral datasets, and the Safer-AS3A model was compared to other models with similar characteristics. The experimental results indicate that the Safer-AS3A model proposed in our study outperforms comparable models in terms of accuracy and robustness when dealing with scenarios having a limited number of labeled samples. Furthermore, after the training set was expanded with the Safer-AS3A model, the Partial least squares regression (PLSR), Bayesian ridge regression (BRR), and Support vector regression (SVR) models on the Diesel dataset improved their R 2 on the test set by 5.923 %, 3.018 %, and 7.331 %, respectively, compared to the models using only the labeled sample set. On the other hand, the Ridge regression (RR), BRR, and SVR models on the test set on the Shoot dataset improved the R 2 by 4.169 %, 4.449 %, and 11.597 %, respectively. Overall, the Safer-AS3A model can effectively expand the NIR spectral dataset and considerably improve the performance of the NIR spectral analysis model. Using the AL method, the SSL method, and the co-training method together, a novel and effective method is presented for generating high-quality pseudo-labels. This method opens up new avenues for enhancing the efficiency and precision of NIR spectrum analysis. It also provides novel perspectives on sample diversification and prospective applications in other disciplines. [Display omitted] • A deep active learning method is developed to analyze near-infrared spectroscopy data. • The stability principle and voting mechanism are added to the confidence evaluation of pseudo-labeling. • The co-training method effectively alleviates the problem of insufficient labeled spectral samples. [ABSTRACT FROM AUTHOR]

[Display omitted] • Visible near infrared spectroscopy can be used to detect four heavy metals in Jiaozhou Bay, China. • The model established in this study have an RPD of over 1.7. • This study provides an effective reference for ecological environment protection and resource development of the Jiaozhou Bay. As an important component of biogeochemical cycle in coastal ecosystems, sediments are the sink of heavy metals. Therefore, distribution and dynamics of heavy metals in sediments could assess ecological quality and predict ecological risks. In the new era, rapid and green technology are highly needed, especially that could determine multi-parameters simultaneously. Here, we explored a new method to rapidly determine concentrations of heavy metals in sediments by visible and near infrared reflectance spectroscopy (VIRS). We sampled sediments in the Jiaozhou Bay, China, collected their reflectance spectra, and measured concentrations of four heavy metals (As, Cr, Cu, and Zn). Heavy metal models were established and evaluated using substances highly correlated with heavy metals. This study provides an effective reference for rapid analysis of As, Cr, Cu, and Zn simultaneously in sediments, at least in the Jiaozhou Bay, and for ecological environment protection and resource development of the Jiaozhou Bay. [ABSTRACT FROM AUTHOR]

[Display omitted] • A hybrid Transformer network, TMNet, was developed to identify SERS spectra. • Transformer encoder was used to extract precise features of the sequential spectra. • Classification results were generated through features by the multi-layer perceptron. • TMNet excellently identified drugs in hair and urine in different noise scenarios. Surface-enhanced Raman Spectroscopy (SERS) is extensively implemented in drug detection due to its sensitivity and non-destructive nature. Deep learning methods, which are represented by convolutional neural network (CNN), have been widely applied in identifying the spectra from SERS for powerful learning ability. However, the local receptive field of CNN limits the feature extraction of sequential spectra for suppressing the analysis results. In this study, a hybrid Transformer network, TMNet, was developed to identify SERS spectra by integrating the Transformer encoder and the multi-layer perceptron. The Transformer encoder can obtain precise feature representations of sequential spectra with the aid of self-attention, and the multi-layer perceptron efficiently transforms the representations to the final identification results. TMNet performed excellently, with identification accuracies of 99.07% for the spectra of hair containing drugs and 97.12% for those of urine containing drugs. For the spectra with additive white Gaussian, baseline background, and mixed noises, TMNet still exhibited the best performance among all the methods. Overall, the proposed method can accurately identify SERS spectra with outstanding noise resistance and excellent generalization and holds great potential for the analysis of other spectroscopy data. [ABSTRACT FROM AUTHOR]

[Display omitted] • A portable Raman spectroscopy detection system was established. • The spectral data from peanut samples was obtained using this system. • A hybrid strategy for variable selection was proposed. • This study used Raman spectra and hybrid strategy to detect AFB 1 in peanuts. Aflatoxin B 1 (AFB 1), among the identified aflatoxins, exhibits the highest content, possesses the most potent toxicity, and poses the gravest threat. It is commonly found in peanuts and their derivatives. This study employs Raman spectroscopy to monitor the AFB 1 levels in moldy peanuts, providing a reliable theoretical basis for peanut storage management. Firstly, different degrees of moldy peanuts are spectrally characterized using a portable Raman spectrometer. Subsequently, a two-step hybrid strategy for feature selection is proposed, combining backward interval partial least squares (BiPLS) and variable combination population analysis (VCPA), aiming to simplify model complexity and enhance predictive accuracy. Finally, partial least squares (PLS) regression models are constructed based on different feature intervals and wavelength points. The research results reveal that the PLS regression model using the optimized feature intervals and wavelength points exhibits improved predictive capability and generalization performance. Notably, the BiPLS-VCPA-PLS model, established through the two-step optimization, selects nine wavelength variables, achieving a root mean square error of prediction (RMSEP) of 33.3147 μ g ∙ k g - 1 , a correlation coefficient of the prediction set (R P) of 0.9558, and a relative percent deviation (RPD) of 3.4896. These findings demonstrate that the two-step feature optimization method, combining feature interval selection and feature wavelength selection, can more accurately identify optimal variables, thus enhancing detection efficiency and predictive precision. [ABSTRACT FROM AUTHOR]

Identification of components in pesticide mixtures has been a major challenge in spectral analysis. In this paper, we assembled monolayer Ag nanoparticles on Thin-layer chromatography (TLC) plates to prepare TLC-Ag substrates with mixture separation and surface-enhanced Raman scattering (SERS) detection. Spectral scans were performed along the longitudinal direction of the TLC-Ag substrate to generate SERS spectra of all target analytes on the TLC plate. Convolutional neural network classification and spectral angle similarity machine learning algorithms were used to identify pesticide information from the TLC-SERS spectra. It was shown that the proposed automated spectral analysis method successfully classified five categories, including four pesticides (thiram, triadimefon, benzimidazole, thiamethoxam) as well as a blank TLC-Ag data control. The location of each pesticide on the TLC plate was determined by the intersection of the information curves of the two algorithms with 100 % accuracy. Therefore, this method is expected to help regulators understand the residues of mixed pesticides in agricultural products and reduce the potential risk of agricultural products to human health and the environment. [Display omitted] • A simple method for preparation of TLC-Ag substrate with separation and SERS detection. • Machine learning algorithm analyze TLC-SERS spectra to identify pesticides mixtures. • The combination of the two algorithms ensures accuracy of the identification results. • Accurate identification of analytes even the analytes overlap on the TLC path. [ABSTRACT FROM AUTHOR]