Spectral Parameters Research Articles

Temporal and Spectral Characteristics of Persistent Emission and Special Bursts of Magnetar SGR J1935+2154 Based on Insight-HXMT

In October 2022, the magnetar SGR J1935+2154 entered the active outburst state. During the episode, the Insight-HXMT satellite carried out a long observation that lasted for 20 days. More than 300 bursts were detected, and a certain amount of persistent radiation signals were also accumulated. This paper mainly introduces the results of persistent radiation profile folding and period search based on Insight-HXMT data. At the same time, the burst phase distribution characteristics, spectral lag results of burst, the spectral characteristics of zero-lag bursts and the time-resolved spectral evolution characteristics of high-flux bursts are reported. We found that there is no significant delay feature during different energy bands for the bursts of SGR J1935+2154. The observed zero-lag burst does not have a unique spectrum. The time-resolved spectrum of the individual burst has consistent spectral types and spectral parameters at different time periods of the burst. We also find that the burst number phase distribution and the burst photon phase distribution have the same tendency to concentrate in specific regions of the persistent emission profile.

Prediction of the success of electrical cardioversion in patients with atrial fibrillation using parameters obtained by spectral and vectorcardiographic analysis of the ECG

Abstract Introduction Electrical cardioversion (ECV) still presents a treatment option for atrial fibrillation (AF). Despite the great success rate in the acute setting, its long-term success rate is low. The aim of the study was to find predictors of SR maintenance after ECV using spectral and vectorcardiographic (VCG) analysis of the ECG curve. Methods Consecutive patients with AF referred for elective ECV were prospectively enrolled. The digital ECG recording obtained before the ECV was analyzed using spectral and VCG analysis. All patients had Holter monitoring and clinical follow-up three months after cardioversion to assess SR maintenance. Atrial fibrillation activity was analyzed by spectral analysis, determining the dominant frequency (DF), RI (regularity index) and OI (organization index). QRS complexes were analyzed by vectorcardiography and dXmean, dYmean and dZmean (derivation of VCG signals) parameters were determined. Using logistic regression (LR) with backward parameter reduction, separate and combined predictive models of SR maintenance were calculated based on both the analysis from the VCG data and the spectral analysis data. Additional models with a forward selection of clinical variables were also calculated. The efficiency of the models was evaluated on a separate test subset of the data (N=32). Results A total of 80 patients were enrolled (age 70+10 years, 48 (64%) men, CHADSVASc 3.17+1.5, BMI 29.75kg/m2). At the 3-month follow-up, AF recurrence was present in 36 patients (45%). Using only vectorcardiographic parameters, dXmean (OR 3.07, 95 %CI 1.14- 8.63), p=0.001) and dYmean (OR 0.26, 95% CI 0.09-0.72), p <0.001) best predicted the SR maintenance (AUC of 0.72). Using only spectral analysis parameters, the best predictor was DF (OR 3.07, 95%CI 1.14-8.63), p=0.012) with AUC of 0.66. By combining the results of spectral analysis and vectorcardiography, an AUC of 0.78 was achieved. Among the clinical parameters, the most significant predictors were insufficiently controlled arterial hypertension and previous history of stroke. Conclusion Digital analysis of ECG curves using deeper mathematical models provides a better predictive model than classical clinical and echocardiographic models. The combination of spectral analysis of fibrillation atrial activity and vectorocardiographic analysis of QRS complexes revealed more accurate predictive information compared to both analyses alone.

Riemann-Hilbert approach and double-pole solutions for the third-order flow equation of DNLS-type equation with nonzero boundary conditions

In this paper, the Riemann-Hilbert approach is applied to study a third-order flow equation of derivative nonlinear Schrödinger-type equation with nonzero boundary conditions. By utilizing the analytical, symmetric, and asymptotic properties of eigenfunctions, a generalized Riemann-Hilbert problem is formulated for the third-order flow equation of derivative nonlinear Schrödinger-type equation with nonzero boundary conditions. The formulas of N-soliton solutions for cases of single pole and double poles are given. We present some kinds of soliton solutions of these two cases according to different distributions of spectral parameters to study the dynamical behavior of them.

Spectral analysis of heart rate variability in patients with newly diagnosed atrial fibrillation

Spectral analysis of heart rate variability gives an idea of the role of the autonomic nervous system in the regulation of chronotropic heart function and can be used to evaluate the effectiveness of drug therapy. The selection of drug therapy taking into account the individual clinical form of atrial fibrillation, as well as the vegetative status of the patient, will undoubtedly increase the effectiveness of treatment. In this study, spectral parameters were studied in patients with newly diagnosed atrial fibrillation and the effect of the antiarrhythmic drug class III miodarone on these parameters.

Monitoring of Chlorophyll Content of Potato in Northern Shaanxi Based on Different Spectral Parameters.

Leaf chlorophyll content (LCC) is an important physiological index to evaluate the photosynthetic capacity and growth health of crops. In this investigation, the focus was placed on the chlorophyll content per unit of leaf area (LCCA) and the chlorophyll content per unit of fresh weight (LCCW) during the tuber formation phase of potatoes in Northern Shaanxi. Ground-based hyperspectral data were acquired for this purpose to formulate the vegetation index. The correlation coefficient method was used to obtain the "trilateral" parameters with the best correlation between potato LCCA and LCCW, empirical vegetation index, any two-band vegetation index constructed after 0-2 fractional differential transformation (step size 0.5), and the parameters with the highest correlation among the three spectral parameters, which were divided into four combinations as model inputs. The prediction models of potato LCCA and LCCW were constructed using the support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN) algorithms. The results showed that, compared with the "trilateral" parameter and the empirical vegetation index, the spectral index constructed by the hyperspectral reflectance after differential transformation had a stronger correlation with potato LCCA and LCCW. Compared with no treatment, the correlation between spectral index and potato LCC and the prediction accuracy of the model showed a trend of decreasing after initial growth with the increase in differential order. The highest correlation index after 0-2 order differential treatment is DI, and the maximum correlation coefficients are 0.787, 0.798, 0.792, 0.788 and 0.756, respectively. The maximum value of the spectral index correlation coefficient after each order differential treatment corresponds to the red edge or near-infrared band. A comprehensive comparison shows that in the LCCA and LCCW estimation models, the RF model has the highest accuracy when combination 3 is used as the input variable. Therefore, it is more recommended to use the LCCA to estimate the chlorophyll content of crop leaves in the agricultural practices of the potato industry. The results of this study can enhance the scientific understanding and accurate simulation of potato canopy spectral information, provide a theoretical basis for the remote sensing inversion of crop growth, and promote the development of modern precision agriculture.

Crystal growth and spectroscopic properties of Nd3+ -doped SrB4O7 single crystal

Single crystal of Nd3+ -doped SrB4O7 (SBO) has been successfully grown by the Czochralski method. The spectroscopic properties were investigated and spectral parameters were calculated based on the Judd–Ofelt theory. The results suggest that the Nd:SBO crystal may have great potential as laser crystal, and through self-frequency doubling, it is expected to achieve the frequency conversion of the characteristic output of Nd3+ in the near infrared to obtain a visible laser.

Precipitation of oxide dispersion strength steels after long-term annealing at temperature of 475 °C

Oxide dispersion strengthened steels are key alloys used in nuclear installations. Steels with chromium content of up to 10 wt % are suitable due to their advantageous properties and these alloys are used for the construction of technological devices in the primary circuit of nuclear power plants. From other studies, it can be concluded that chromium has anti-corrosive properties due to the formation of a passivation layer, which results in reduced activation of the material by thermal neutrons. Macroscopic properties are determined by their microstructure, and therefore, the description of the microstructure is important. Transmission Mössbauer spectroscopy and atom probe tomography were used to characterise the material. This provides information about the physical and/or chemical environment of the resonant atoms can be obtained. Obtained spectral parameters reach saturation values from which the solubility limit of chromium in iron can be determined. In Cr-rich phase, the solubility limit can be estimated from the value of spectral parameters of the single-line in the spectrum annealed for the longest time. The suggested procedures are subsequently applied to the case studies of stainless steels suitable for the construction of various components of the III+/IVth generation of nuclear reactors (including fast and fusion reactors).

Improving the estimation of rice above-ground biomass based on spatio-temporal UAV imagery and phenological stages.

Unmanned aerial vehicles (UAVs) equipped with visible and multispectral cameras provide reliable and efficient methods for remote crop monitoring and above-ground biomass (AGB) estimation in rice fields. However, existing research predominantly focuses on AGB estimation based on canopy spectral features or by incorporating plant height (PH) as a parameter. Insufficient consideration has been given to the spatial structure and the phenological stages of rice in these studies. In this study, a novel method was introduced by fully considering the three-dimensional growth dynamics of rice, integrating both horizontal (canopy cover, CC) and vertical (PH) aspects of canopy development, and accounting for the growing days of rice. To investigate the synergistic effects of combining spectral, spatial and temporal parameters, both small-scale plot experiments and large-scale field testing were conducted in Jiangsu Province, China from 2021 to 2022. Twenty vegetation indices (VIs) were used as spectral features, PH and CC as spatial parameters, and days after transplanting (DAT) as a temporal parameter. AGB estimation models were built with five regression methods (MSR, ENet, PLSR, RF and SVR), using the derived data from six feature combinations (VIs, PH+CC, PH+CC+DAT, VIs+PH +CC, VIs+DAT, VIs+PH+CC+DAT). The results showed a strong correlation between extracted and ground-measured PH (R2 = 0.89, RMSE=5.08 cm). Furthermore, VIs, PH and CC exhibit strong correlations with AGB during the mid-tillering to flowering stages. The optimal AGB estimation results during the mid-tillering to flowering stages on plot data were from the PLSR model with VIs and DAT as inputs (R 2 = 0.88, RMSE=1111kg/ha, NRMSE=9.76%), and with VIs, PH, CC, and DAT all as inputs (R 2 = 0.88, RMSE=1131 kg/ha, NRMSE=9.94%). For the field sampling data, the ENet model combined with different feature inputs had the best estimation results (%error=0.6%-13.5%), demonstrating excellent practical applicability. Model evaluation and feature importance ranking demonstrated that augmenting VIs with temporal and spatial parameters significantly enhanced the AGB estimation accuracy. In summary, the fusion of spectral and spatio-temporal features enhanced the actual physical significance of the AGB estimation models and showed great potential for accurate rice AGB estimation during the main phenological stages.

Spectral CT in the evaluation of perineural invasion status in rectal cancer.

To investigate whether preoperative spectral CT quantitative parameters can assess perineural invasion (PNI) status in rectal cancer. Sixty-two patients diagnosed with rectal cancer who underwent preoperative spectral CT were retrospectively enrolled and divided into positive and negative PNI groups according to histopathologic results. The CT attenuation value (HU) of virtual monochromatic images (40-70keV), spectral curve slope (K(HU)), effective atomic number (Zeff), and iodine concentration (IC) from spectral CT were compared between these two groups using t test or rank sum test. A nomogram was established by incorporating the independent predictors to assess the overall diagnostic efficacy. The area under the ROC curves (AUCs) were compared using the DeLong test. The preoperative spectral CT parameters (40-70keV attenuation, K(HU), Zeff, and IC) were significantly higher in the PNI-positive group compared to the PNI-negative group (all p < 0.05). The highest predictive efficiency of PNI was observed at 40keV attenuation, with an area under the curve (AUC), sensitivity, specificity, and accuracy of 0.847, 81.8%, 72.5%, and 75.8%, respectively. Binary logistic regression demonstrated that the clinical feature (cN stage) and 40keV attenuation were independent predictors of PNI status. The nomogram incorporating these two predictors (cN stage and 40keV attenuation) exhibited the best evaluation efficacy, with an AUC, sensitivity, specificity, and accuracy of 0.885, 86.4%, 77.5%, and 80.6%. Spectral CT quantitative parameters proved valuable in the preoperative assessment of PNI status in rectal cancer patients. The combination of spectral CT parameters and clinical features could further enhance the diagnostic efficiency.

Dark-soliton asymptotics for a repulsive nonlinear system in a baroclinic flow

In geophysical hydrodynamics, baroclinic instability denotes the process in which the perturbations draw the energy from the mean flow potential power. Researchers focus their attention on the baroclinic instability in the Earth's atmosphere and oceans for the meteorological diagnosis and prediction. Under investigation in this paper is a repulsive nonlinear system modeling the marginally unstable baroclinic wave packets in a baroclinic flow. With respect to the amplitude of the baroclinic wave packet and correction to the mean flow resulting from the self-rectification of the baroclinic wave, we present a Lax pair with the changeable parameters and then derive the N-dark-dark soliton solutions, where N is a positive integer. Asymptotic analysis on the N-dark-dark solitons is processed to obtain the algebraic expressions of the N-dark-dark soliton components. We find that the obtained phase shift of each dark-dark soliton component is relevant with the N − 1 spectral parameters. Furthermore, we take N = 3 as an example and graphically illustrate the 3-dark-dark solitons, which are consistent with our asymptotic-analysis results. Our analysis may provide the explanations of the complex and variable natural mechanisms of the baroclinic instability.

New insight into the hard X-ray emission influenced by the type I bursts observed by Insight-HXMT during the outburst of 4U 1636–536

Context. Thermonuclear bursts, also known as type I X-ray bursts, result from unstable nuclear burning of H/He accreted to the surface of neutron stars, lasting from tens to hundreds of seconds. Thermonuclear bursts have an important impact on accretion environments around the neutron stars, such as their disks and coronas, and are therefore a subject of extensive research. Thermonuclear bursts can be used as probes to gain a deeper understanding of the properties of their disks and coronas. Aims. By analyzing the data from Insight-HXMT and NICER, we can determine the evolution of the significance of the hard shortage in 4U 1636–536 with its spectral state, as well as the evolution of the fraction of deficit with energy. Additionally, we investigate the possible geometry and evolution of the corona in 4U 1636–536 by combining our findings with the results of spectral analysis. Methods. We extracted the light curves from the Insight-HXMT low-energy, medium-energy, and high-energy data and subtracted their pre-burst emission, which allowed us to estimate the significance of the hard shortages during the bursts. By fitting the spectra, the correlation between the persistent spectral parameters and the significance of the hard shortages could be established. The bursts were then grouped according to the spectral state in which they occurred, and the significance of the hard shortages was estimated. These in turn helped to investigate the evolution of the fraction of deficit with energy. Results. We find that during the soft state the significance of possible hard X-ray shortage in bursts is almost zero. However, in the hard state, some bursts exhibit significant shortages (&gt; 3σ), while others do not. We attempt to establish a correlation between the significance of the hard X-ray shortage and the spectral parameters, but the data quality and the limited number of bursts prevent us from finding a strong correlation. For bursts with insignificant shortages in the soft state, the fraction of the deficit remains small. However, in the hard state the fraction of deficit for all bursts increases with energy, regardless of the significance of the shortage of individual bursts. For bursts during the hard state, we investigated the evolution of the fraction of deficit during the bursts by stacking the peaks and decays of the bursts, and find that as the flux of the bursts decreases, the energy corresponding to the maximum of the fraction of deficit becomes progressively higher. Conclusions. We explore the possible geometry and evolution of the corona suggested by the evolution of the fraction of deficit, which is obtained from the spectral and temporal analysis.

Controllable nonautonomous localized waves and dynamics for a quasi-1D Gross-Pitaevskii equation in Bose-Einstein condensations with attractive interaction.

This paper investigates dynamical behaviors and controllability of some nonautonomous localized waves based on the Gross-Pitaevskii equation with attractive interatomic interactions. Our approach is a relation constructed between the Gross-Pitaevskii equation and the standard nonlinear Schrödinger equation through a new self-similarity transformation which is to convert the exact solutions of the latter to the former's. Subsequently, one can obtain the nonautonomous breather solutions and higher-order rogue wave solutions of the Gross-Pitaevskii equation. It has been shown that the nonautonomous localized waves can be controlled by the parameters within the self-similarity transformation, rather than relying solely on the nonlinear intensity, spectral parameters, and external potential. The control mechanism can induce an unusual number of loosely bound higher-order rogue waves. The asymptotic analysis of unusual loosely bound rogue waves shows that their essence is energy transfer among rogue waves. Numerical simulations test the dynamical stability of obtained localized wave solutions, which indicate that modifying the parameters in the self-similarity transformation can improve the stability of unstable localized waves and prolong their lifespan. We numerically confirm that the rogue wave controlled by the self-similarity transformation can be reproduced from a chaotic initial background field, hence anticipating the feasibility of its experimental observation, and propose an experimental method for observing these phenomena in Bose-Einstein condensates. The method presented in this paper can help to induce and observe new stable localized waves in some physical systems.

A phase-resolved Fermi-LAT analysis of the mode-changing pulsar PSR J2021+4026 shows hints of a multipolar magnetosphere

Context. The radio-quiet γ-ray pulsar PSR J2021+4026 is a peculiar Fermi-LAT pulsar showing repeated and quasi-periodic mode changes. Its γ-ray flux shows repeated variations between two states at intervals of ∼3.5 years. These events occur over timescales &lt; 100 days and are correlated with sudden changes in the spin-down rate. Multiwavelength observations also revealed an X-ray phase shift relative to the γ-ray profile for one of the events. PSR J2021+4026 is currently the only known isolated γ-ray pulsar showing significant variability, and thus it has been the object of thorough investigations. Aims. The goal of our work is to study the mode changes of PSR J2021+4026 with improved detail. By accurately characterizing variations in the γ-ray spectrum and pulse profile, we aim to relate the Fermi-LAT observations to theoretical models. We also aim to interpret the mode changes in terms of variations in the structure of a multipolar dissipative magnetosphere. Methods. We continually monitored the rotational evolution and the γ-ray flux of PSR J2021+4026 using more than 13 years of Fermi-LAT data with a binned likelihood approach. We investigated the features of the phase-resolved spectrum and pulse profile, and from these we inferred the macroscopic conductivity, the electric field parallel to the magnetic field, and the curvature radiation cutoff energy. These physical quantities are related to the spin-down rate and the γ-ray flux and therefore are relevant to the theoretical interpretation of the mode changes. We introduced a simple magnetosphere model that combines a dipole field with a strong quadrupole component. We simulated magnetic field configurations to determine the positions of the polar caps for different sets of parameters. Results. We clearly detect the previous mode changes and confirm a more recent mode change that occurred around June 2020. We provide a full set of best-fit parameters for the phase-resolved γ-ray spectrum and the pulse profile obtained in five distinct time intervals. We computed the relative variations in the best-fit parameters, finding typical flux changes between 13% and 20%. Correlations appear between the γ-ray flux and the spectral parameters, as the peak of the spectrum shifts by ∼10% toward lower energies when the flux decreases. The analysis of the pulse profile reveals that the pulsed fraction of the light curve is larger when the flux is low. Finally, the magnetosphere simulations show that some configurations could explain the observed multiwavelength variability. However, self-consistent models are required to reproduce the observed magnitudes of the mode changes.

Quantitative analysis of visually normal EEG reveals spectral power abnormalities in temporal lobe epilepsy

ObjectiveTo compare quantitative spectral parameters of visually-normal EEG between Mesial Temporal Lobe Epilepsy (MTLE) patients and healthy controls (HC). MethodWe enrolled 26 MTLE patients and 26 HC. From each recording we calculated total power of all frequency bands and determined alpha-theta (ATR) and alpha-delta (ADR) power ratios in different brain regions. Group-wise differences between spectral parameters were investigated (p < 0.05). To test for associations between spectral-power and cognitive status, we evaluated correlations between neuropsychological tests and quantitative EEG (qEEG) metrics. ResultsIn all comparisons, ATR and ADR were significantly decreased in MTLE patients compared to HC, particularly over the hemisphere ipsilateral to epileptic activity. A positive correlation was seen in MTLE patients between ATR in ipsilateral temporal lobe, and results of neuropsychological tests of auditory verbal learning (RAVLT and RAVLT-D), short term verbal memory (Digit span backwards), and executive function (Weigl's sorting test). ADR values in the contralateral posterior region correlated positively with RAVLT-D and Digit span backwards tests. DiscussionResults confirmed that the power spectrum of qEEG is shifted towards lower frequencies in MTLE patients compared to HC. ConclusionOf note, our results were found in visually-normal recordings, providing further evidence of the value of qEEG for longitudinal monitoring of MTLE patients over time. Exploratory analysis of associations between qEEG and neuropsychological data suggest this could be useful for investigating effects of antiseizure medications on cognitive integrity in patients.

Nd3+-doped mixed alkaline-earth zinc silico-aluminate glass: Insights on its 1069 nm spectral performance parameters

Nd3+-doped mixed alkaline-earth zinc silico-aluminate glass: Insights on its 1069 nm spectral performance parameters

Overdistention accelerates electrophysiological changes in uterine muscle towards labour in multiple gestations

Background for the researchPremature birth and its associated complications are one of the biggest global health problems, since there is currently no effective screening method in clinical practice to accurately identify the true Preterm Birth (PTB) from the false threatened ones. Despite the high prevalence of PTB in multiple gestation (MG) women which amounted up to 60%, in the literature there is any work about their uterine myoelectric activities in vivo system. Electrohysterography (EHG) has been emerged as an alternative technique for predicting PTB in single gestation (SG) women. PurposeThe aim of this study was to characterize and compare the uterine myoelectrical activity in vivo system of SG and MG women in regular check-ups, to provide the basis for early detection and prevention of preterm labor in MG. Basic proceduresA prospective observational cohort study was conducted on 31 SG and 18 MG women between the 28th and 32th WoG who underwent regular check-ups in the Polytechnic and University Hospital La Fe (Valencia, Spain). The 30-minute bipolar recording was filtered in the 0.1-4 Hz bandwidth and downsampled to 20 Hz. Signal analysis was performed in 120-second moving windows with 50% overlap, after removing artefacts by a double- blind expert process. A set of 8 temporal, spectral and non-linear parameters were calculated: root mean square (RMS), kurtosis of the Hilbert envelope (KHE), median frequency (MDF), H/L ratio, and sample entropy (SampEn) and bubble entropy (BubbEn) calculated in the whole bandwidth (WBW) and the fast wave high (FWH). The 10th, 50th and 90th percentiles of all windows analysed were calculated to obtain representative values of the recordings. For each parameter and percentile, statistically significant differences between the SG and MG groups and their statistical power (SP) were analysed to determine both the existence of an effect and substantive significance, respectively. Main findingsIn comparison to SG, MG EHG exhibited significant higher impulsiveness and higher predictability than SG which was reflected in the KHE (SP10 = 85.2, p10 < 0.001) and entropy measures (SampEn FWH: SP50 = 62.0, p50 = 0.0.016; SP90 = 52.5, p90 = 0.059. BubbEn FWH: SP50 = 75.2, p50 < 0.001; SP90 = 60.3, p90 = 0.002), suggesting an accelerated evolution of uterine electrophysiological condition. In addition, several EHG parameters were found to significantly correlate with foetal weight such as amplitude (RMS: r90 = 0.311, p90 = 0.006), signal impulsiveness (KHE: r10 = 0.311, p10 = 0.006) and entropy measures (SampEn FWH: r50 = −0.317, p50 = 0.005*; r90 = −0.279, p90 = 0.013*. BubbEn FWH: r50 = −0.370, p50 = 0.001*; r90 = −0.313, p90 = 0.005*), suggesting an electromechanical coupling between uterine overdistension and contractile activity in vivo system. Principal conclusionsIn comparison to SG women, MG showed higher impulsiveness and predictability in early third gestational trimester, as reflected in KHE, SampEn and BubbEn, respectively. We found similar cell excitability between SG and MG women far from delivery. In addition, we confirmed the relationship between uterine overdistension and surface myoelectric activity, revealing the electromechanical coupling pathway in uterine smooth muscle. Therefore, contextualized EHG-biomarkers would provide valuable information for early detection of PTB risk, which would allow clinicians better PTB management through personalised therapeutic interventions.

Validation Of An Efficient Non-Hydrostatic Wave Model As A Design Tool For Foreshores In Physical Models

In the design of physical model experiments in coastal engineering, it is common that the construction of a foreshore is necessary to obtain the desired wave conditions at a given location, usually close to a structure being tested. In addition to the commonly used spectral wave parameters to describe the target wave conditions, the wave height distribution and associated parameters (such as Hmax and H2%), wave periods and infra-gravity waves can be important to reproduce properly as well. Wave height distributions are typically important for tests where e.g. wave run-up or wave forces are of interest. Since the construction of foreshores is labour intensive (and thus expensive), it is useful to be able to check a priori whether the target wave conditions are met with a given foreshore design and whether the chosen transition slope does not significantly influence the wave conditions. One way to do this is by using numerical wave models. For a numerical model to be a useful design tool for physical model layouts, the predicted wave transformation (over the foreshore) needs to be sufficiently accurate. One option is to use detailed CFD wave models for this purpose, such as OpenFOAM, which has been shown to accurately reproduce wave transformation (Jacobsen et al., 2015; Jacobsen et al., 2018). CFD models, however, typically feature high computational demand and consequentially computational times in the order of days. This is a significant disadvantage in the context of designing a physical model experiment, for which the layout and configuration is often an iterative process, which would be hampered by overly long computational times. On the other hand, spectral wave models, like SWAN (Booij et al., 1996), are much faster but do not model all the individual waves rendering it unable to model exceedance distributions. As a middle-ground, it seems that the XBeach model (Roelvink et al., 2009) used in its 2-layer non-hydrostatic mode (De Ridder et al., 2021) might present a workable compromise between computational time and accurate representation of the wave transformation. The model has been validated by De Ridder et al. (2021) on bichromatic waves, complex barred beach geometry and a fringing reef for bulk wave parameters and spectral properties. Expanding on earlier validation work, in this work the ability of the XBeach 2-layer non-hydrostatic model (XBeach-nh) to reproduce wave height exceedance distributions over a sloping foreshore is validated using wave flume data, described in Sections 2 and 3. The preliminary results of the validation effort are shown in Section 4.

In-situ observations of cloud microphysics over Arabian Sea during dust transport events

The unique in situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice processes. Cloud base droplet number concentration is about 142 ± 79 cm−3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2% supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion ( ε; the ratio of DSD spectral width ( σ ) to mean radius ( rm )) and liquid water adiabatic fraction (AF) indicates that the entrainment effect has increased relative dispersion significantly (2–3 times larger) in these clouds. Effective radius ( reff ) is found to be proportional to mean volume radius ( rv ) with a proportionality constant ( β ) that varies between 1.0–1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2–50 μ m and the large drizzle drops (or ice hydrometeors) with size range 100–6400 μ m are parameterized using the gamma function distributions useful for large-scale cloud models.

Thermodynamic functions of germane isotopologues AGeH4 (A = 70, 72, 73, 74, 76) calculated from high-resolution IR spectra

Standard thermodynamic functions of germane isotopologues 70GeH4, 72GeH4, 73GeH4, 74GeH4, and 76GeH4 are calculated in “harmonic oscillator – rigid rotator” and “anharmonic oscillator – oscillating non-rigid rotator” approximations and by the direct summation of the experimental energy values. To found the values of thermodynamic functions in the 200–700K temperature range, approximation coefficients are determined by regression analysis. The isotope effect influence on the values of the standard isobaric heat capacity, entropy, enthalpy of heating, and the reduced isobaric-isothermal potential of germane is established. Limiting requirements for the accuracy of determining the spectral parameters for detecting the influence of the isotope effect on the thermodynamic functions and interatomic distances in the germane molecule are formulated.

Identification of complex crude oil categories in ultra-deep petroleum systems based on a new fluorescence analysis method: An example from the southwestern Tabei Uplift, Tarim Basin, China

Ultra-deep crude oils have become one of the most important targets for petroleum exploration. In ultra-deep petroleum systems, differential hydrocarbon generation of various source rocks and multistage oil accumulation and secondary alteration processes led to the coexistence of crude oils with diverse sources and formation mechanisms. How to effectively identify complicated crude oil categories is a difficult issue confronted with ultra-deep petroleum exploration. Because crude oils are generally fluorescent, fluorescence analysis methods exhibit great application potential for classifying ultra-deep crude oils. However, due to the lack of other restrictive parameters, previous methods based on fluorescence color and fluorescence spectra limit the geological application of fluorescence analysis methods in ultra-deep petroleum systems. Based on the combination of fluorescence spectral parameters and fluorescence lifetimes, this study innovatively provides a new fluorescence analysis method for identifying complex crude oil categories in ultra-deep petroleum systems. Moreover, the sources and formation mechanisms of the ultra-deep crude oil can be further identified by combining fluorescence parameters with physical and geochemical parameters. By applying the above method, this study effectively identified three categories of crude oils and revealed their sources and formation mechanisms in the ultra-deep petroleum system of the southwestern Tabei Uplift, Tarim Basin, China. The new fluorescence analysis method may have practical significance for revealing the sources and formation mechanisms of ultra-deep crude oils.