Decay Parameters Research Articles

Optoelectronic and photoacoustic waves in rotating excited semiconductor subjected to thermal shock

In this study, the impact of rotation on the transmission of optical acoustic waves, arising from the movement of the optical carrier within an elastic thermal environment, is examined through theoretical analysis. The theoretical framework incorporates the interaction between acoustic waves and thermomechanics to formulate governing equations specific to a semiconductor medium. The fundamental equations of the physical model, influenced by photothermal and thermoelastic principles, are deduced mathematically while considering the presence of rotation. The model studied the medium under a thermal shock wave from thermal stress resulting from light-induced temperature elevation that is not fixed but decaying over time. The mathematical model is solvable using the normal mode method. The model’s numerical solutions provide access to all physical fields within the physical domain, encompassing displacement, temperature, acoustic pressure, mechanical stress, and carrier density diffusion. Utilizing the harmonic wave method, a two-dimensional graphical representation of the rotation parameter with and without the influence of the decay parameter is obtained. The theoretical analysis involves comparison, analysis, and discussion of the effects of these parameters investigated.

An empirical analysis of learning and forgetting mechanisms in repeated evacuations: A panel recursive logit approach

Global efforts to address climate change increasingly focus on risk communication to encourage people's mitigation behaviour. This study investigates how risk communication influences evacuation behaviour, through repeated risk communications and stated preference surveys. In modelling the learning process of infrequent events like disasters, it is necessary to consider decision-making under uncertainty about future situations and the tendency to forget acquired information. We propose a recursive model that captures two decision dynamics relevant to infrequent events: proactive decision-making amid dynamically changing conditions and the learning and forgetting processes between events. The former is modelled using the recursive logit model on a time-expanded network, while the latter is represented by dynamic changes in utility and memory decay parameters. The estimation results indicate that risk communication generally promotes earlier evacuation to safer places. However, effective communication strategies and the duration of their effects differ based on individuals' perceived and actual risks.

Temporal variation of S-wave attenuation during the 2009 L'Aquila, Central Italy, seismic sequence

Summary We investigate temporal and spatial variations of the spectral decay parameter kappa (κ) before and after the April 6, 2009, L'Aquila earthquake (Mw 6.1), in central Italy. We analyzed foreshocks ten days before and aftershocks occurring ten days and six months after this main event. We select earthquakes with magnitudes Mw ≥ 3.2 registered by the seismic network of central Italy within a radius of 20 km from the epicenter of the L'Aquila mainshock and having hypocenter distances of less than 170 km. We separate near-source, along-path and near-site contributions of κ for each group of events and we detected temporal variations of this S-wave attenuation parameter. We find that ten days before the mainshock κ along the path has the lowest values, probably due to high tectonic stress accumulated, in agreement with previous investigations performed with other techniques, then κ increases during the main event and remains constant during the first ten days of aftershocks. The aftershocks that occurred six months after show an increase in the regional attenuation probably due to the tectonic stress released during the main shock and the earlier aftershocks. From the spatial point of view, ten days before the principal event the foreshocks located to the south show an increase in the near-source attenuation towards the northeast, in the direction of the mainshock. These spatial variations of κ may be related to the presence of crustal fluids near the rupture area, as evidenced by other previous studies. The first ten days of aftershocks that concentrate around the main earthquake have high near-source κ, and those located north of the main rupture have lower values. These observations are consistent with previous investigations that show variations of elastic and anisotropic crustal properties during the L'Aquila earthquake sequence due to dilatancy and fluid diffusion processes within the nucleation zone. We conclude that temporal variations of the spectral decay parameter κ provide important clues for the earthquake cycle in central Italy.

A Novel Interpolation Method for Soil Parameters Combining RBF Neural Network and IDW in the Pearl River Delta

Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new interpolation prediction framework that combines Radial Basis Function (RBF) neural networks with Inverse Distance Weighting (IDW), termed the IDW-RBFNN. This framework initially uses the IDW method to apply preliminary weights based on distance to the data points, which are then used as input for the RBF neural network to form a training dataset. Subsequently, the RBF neural network further trains on these data to refine the interpolation results, achieving more precise spatial data interpolation. We compared the interpolation prediction accuracy of the IDW-RBFNN framework with ordinary Kriging (OK) and RBF methods under three different parameter settings. Ultimately, the IDW-RBFNN demonstrated lower error rates in terms of RMSE and MRE compared to direct RBF interpolation methods when adjusting settings based on different power values, even with a fixed number of data samples. As the sample size decreases, the interpolation accuracy of OK and RBF methods is significantly affected, while the error of IDW-RBFNN remains relatively low. Considering both interpolation accuracy and resource limitations, we recommend using the IDW-RBFNN method (p = 2) with at least 60 samples as the minimum sampling density to ensure high interpolation accuracy under resource constraints. Our method overcomes limitations of existing approaches that use fixed steady-state distance decay parameters, providing an effective tool for soil fertility monitoring in delta regions.

Different roads take me home: the nonlinear relationship between distance and flows during China’s Spring Festival

Human mobility modelling has attracted scholarly attention from physics-based methods and social science explanatory approaches. However, there is limited knowledge of the nonlinear relationship of flows and distance in intercity mobility and regional differences in the nonlinear relationship. Focusing on China’s long-distance and large-scale mobility during the Spring Festival, this paper develops a framework to explain the nonlinear relationship. Using the Gradient Boosting Decision Tree (GBDT) model and Tencent Big Data, we find that there are three types of nonlinear relationships, namely plateau (almost zero distance decay parameter), drop (decreasing distance decay parameter) and rebound (increasing distance decay parameter after decreasing). The provincial differences also reveal that the nonlinear relationships depend on the domestic relative location and the intra-provincial urban system. This result shows that the cities in the coastal province enjoy a more inclusive spatial structure, which supports the migration from the periphery of the province. In contrast, the inland cities are concerned with embracing the migrants and settling them down.

Evolution of water wave packets by wind in shallow water

We use the Korteweg–de Vries (KdV) equation, supplemented with several forcing/friction terms, to describe the evolution of wind-driven water wave packets in shallow water. The forcing/friction terms describe wind-wave growth due to critical level instability in the air, wave decay due to laminar friction in the water at the air–water interface, wave stress in the air near the interface induced by a turbulent wind and wave decay due to a turbulent bottom boundary layer. The outcome is a modified KdV–Burgers equation that can be a stable or unstable model depending on the forcing/friction parameters. To analyse the evolution of water wave packets, we adapt the Whitham modulation theory for a slowly varying periodic wave train with an emphasis on the solitary wave train limit. The main outcome is the predicted growth and decay rates due to the forcing/friction terms. Numerical simulations using a Fourier spectral method are performed to validate the theory for various cases of initial wave amplitudes and growth and/or decay parameter ranges. The results from the modulation theory agree well with these simulations. In most cases we examined, many solitary waves are generated, suggesting the formation of a soliton gas.

Forecasting the yield curve: the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macro‐economic factors

In this article, we analyse the forecasting performance of several parametric extensions of the popular Dynamic Nelson–Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We also consider the role of several popular restrictions on the dynamics of the factors. Using a novel dataset of end‐of‐month continuously compounded Treasury yields on US zero‐coupon bonds and frequentist estimation based on the extended Kalman filter, we show that a second decay parameter does not contribute to better forecasts. In concordance with the preferred habitat theory, we also show that the best forecasting model depends on the maturity. For short maturities, the best performance is obtained in a heteroscedastic model with a time‐varying decay parameter. However, for long maturities, neither the time‐varying decay nor the heteroscedasticity plays any role, and the best forecasts are obtained in the basic DNS model with the shape of the yield curve depending on macroeconomic activity. Finally, we find that assuming non‐stationary factors is helpful in forecasting at long horizons.

Analyzing coherent structures in the tropical cyclone boundary layer using large eddy simulations

Turbulence within the tropical cyclone boundary layer plays a crucial role in the exchange of heat, moisture, and momentum between the surface and the atmosphere. This study investigates the characteristics of coherent structures, specifically streaks and rolls, using large eddy simulations. Our results highlight significant differences across the three radius cases, with smaller radius exhibiting more intense and organized turbulence and streak/roll structures. Our analyses reveal that thermodynamic conditions significantly impact the timing of initial streak/roll development but do not affect their intensity in the steady state. Wind structures closer to the tropical cyclone center lead to stronger and more rapidly developing streaks/rolls, indicating their critical role in determining the intensity and formation of these features. Sensitivity tests on the Coriolis parameter (f) and radial decay parameter of tangential wind (n) show minimal impact on the development of streaks/rolls, suggesting these factors are less influential compared to wind and thermodynamic conditions.

Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging.

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients' tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients' colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients' tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

Insights into metabolic heterogeneity of colorectal cancer gained from fluorescence lifetime imaging

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients’ tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients’ colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients’ tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

Near-Ground wind field characteristics of tracking photovoltaic systems based on field measurements

The study conducts field measurements at a tracking photovoltaic power station in Zhongwei City, Ningxia Hui Autonomous Region, investigating near-ground incoming wind characteristics, spatial coherence, and their impact on the flow field of the tracking photovoltaic system. Actual measurements indicate a low dispersion degree in the roughness index of this area, with an average roughness index of α = 0.1228, which is consistent with the characteristics of open land and desert areas. The incoming wind speed profile largely complies with European wind load specifications, with turbulence intensity measured at different heights exceeding other wind load specifications, primarily due to increased sand movement contributing to turbulence in desert areas. Additionally, this study proposes calculation formulas for measured turbulence intensity, integration scale, and gust factor, offering valuable insights into the incoming wind field characteristics in this region. Furthermore, the investigation into spatial coherence and decay parameters revealed the superior performance of the Krenk model in high frequency bands and over long distances. Lastly, the tracking photovoltaic array induces noticeable shading effects, altering flow field characteristics significantly, with a diminished impact on wind flow velocity as the tilt angle of the photovoltaic panel decreases. These studies serve as a valuable reference for gaining a deeper understanding of wind field characteristics, wind load calculation, and the optimal design of tracking photovoltaic systems.

The Impact of Source Time Function Complexity on Stress-Drop Estimates

ABSTRACT Earthquake stress drop—a key parameter for describing the energetics of earthquake rupture—can be estimated in several different, but theoretically equivalent, ways. However, independent estimates for the same earthquakes sometimes differ significantly. We find that earthquake source complexity plays a significant role in why theoretically (for simple rupture models) equivalent methods produce different estimates. We apply time- and frequency-domain methods to estimate stress drops for real earthquakes in the SCARDEC (Seismic source ChAracteristics Retrieved from DEConvolving teleseismic body waves, Vallée and Douet, 2016) source time function (STF) database and analyze how rupture complexity drives stress-drop estimate discrepancies. Specifically, we identify two complexity metrics—Brune relative energy (BRE) and spectral decay—that parameterize an earthquake’s complexity relative to the standard Brune model and strongly correlate with the estimate discrepancies. We find that the observed systematic magnitude–stress-drop trends may reflect underlying changes in STF complexity, not necessarily trends in actual stress drop. Both the decay and BRE parameters vary systematically with magnitude, but whether this magnitude–complexity relationship is real remains unresolved.

Influence of Fractional and Decay Parameters on the SU(1,1) Quantum System Interaction with Three‐Level Atom

AbstractThrough the generalized fractional derivative, it is studied how the decay term and the fractional parameter affect the quantum system, specifically the interaction between the SU(1,1) algebraic system and a three‐level atom. By transforming the differential equations into fractional differential equations, general fractional solutions are obtained. The influence of decay and fractional parameter on phenomena such as revival and collapse, entropy squeezing, purity, and concurrence are investigated. The results demonstrate how both decay and fractal parameter affect periods of collapse and revival. It is worth noting that the decay parameter shortens the collapse periods, while an increase in the fractional parameter leads to longer collapse periods. The decay parameter also reduces the degree of entanglement between the different components of the quantum system, while increasing the fractional parameter enhances the entanglement within the quantum system. Hence, it can be concluded that the fractional parameter plays a crucial role in the observed effects on the studied properties.

The effect of the degree of hydration of aluminium oxide thin films on the afterglow luminescence phenomena

The occurrence of afterglow luminescence in aluminum oxide thin films obtained by non-electrolytic aluminum oxide conversion coating has been proved. The kinetic parameters of luminescence decay and its spectral distribution were determined using the single photon counting method. The obtained samples of hydrated aluminum oxide, supported on metallic aluminum, were subjected to dehydration and dehydroxylation. The process of dehydroxylation led to a significant (by over two orders of magnitude) increase in the efficiency of afterglow luminescence. On the basis of the luminescence decay spectrum, the emitters in the systems studied were identified to be oxygen vacancies in the structure of Al2O3, including F, F2, F+. Moreover, a high probability of involvement of electrons from the conductivity band and F and F+ states photoconversion in determination of the character of afterglow luminescence was indicated. Durations of afterglow luminescence measured for the barrier layers and porous aluminum oxide films, obtained by electrochemical oxidation, were compared. Significant differences were detected between the kinetic parameters of luminescence decay and the character of emission spectra, whose analysis permitted proposing mechanisms of the processes.

Numerical investigation of the reflection of unsteady decelerating incident shock waves

The incident shock attenuation phenomenon in shock tube has received widespread interest because of its inevitable influence on experimental gas properties. However, few studies have investigated the cascading effects of the resulting nonuniformity on shock reflection in shock tunnels before the nozzle. This paper describes a numerical study on the unsteady reflection of a decelerating incident shock driven by a decelerating piston, as a simplification of the complex nonideal factors. The initial decay and uniform parameter distributions are generated based on the non-inertial frame. The results indicate that the existence of the nonuniform area forces the reflected shock wave region to undergo a transition process of attenuation and then stability. The final values of the gas parameters in zone 5 will, therefore, deviate from those given by the traditional relation for an ideal shock tube, which are only dependent on the terminal shock Mach number. This affects the determination of the total temperature T5, which is difficult to measure directly. We discuss the reconstruction of the nonuniform region with the attenuation trajectory of the incident shock wave and find that there is no one-to-one correspondence between this trajectory and the resulting nonuniformity, which introduces additional uncertainties to the predictions. Thus, an analogy method is developed through the multilevel block building algorithm, allowing the total temperature T5 to be determined using the total pressure p5 considering the effect of nonuniformity. Further assessments verify the applicability of this method in cases with multidimensional and viscous interactions.

Extending the Physical Functionality of Bioactive Blends of Astrocaryum Pulp and Kernel Oils from Guyana

Natural lipids with nutritional or therapeutic benefits that also provide desired texture, melting and organoleptic appeal (mouthfeel, skin feel) are difficult to procure for the food and cosmetics industries. Natural Astrocaryum pulp oil (AVP) and kernel fat (AVK) from Guyana were blended without further modification to study the potential of extending the physical functionality of the blends beyond that of crude AVK and AVP. An evaluation of non-lipid components by ESI-MS indicated twenty-four (24) bioactive molecules, mainly carotenoids (90%), polyphenols (9%) and sterols (1%) in AVP, indicating important health and therapeutic benefits. Only trace-to-negligible amounts of these compounds were detected in AVK. The thermal transition phase behavior, solid fat content (SFC), microstructure and textural properties of five AVP/AVL blends were used to construct phase diagrams of the AVK/AVP binary system. Binary phase diagrams constructed from the cooling and heating DSC thermograms of the mixtures and description of the liquidus line indicated a mixing behavior close to ideal with a tendency for order, with no phase separation. Melting onsets, solid fat content and measurements of solid-like texture all predictively increased with increasing AVK content. The descriptive decay parameters obtained for SFC, crystal size, hardness, firmness and spreadability were similar and predictive and indicate the way the binary system structure approaches that of a liquid or a functional solid. The bioactive content of the blends was accurately calculated; the work provides a blueprint for the blending of AVP and AVK to deliver targeted bioactive content, stability, spreadability, texture, melting profile, organoleptic appeal and solid content. SFCs at 20 °C ranged from 9.1% to 39.1%, melting onset from −17.5 °C to 27.8 °C, hardness from 0.1 N to 3.5 N and spreadability from 3.3 N·s to 147.1 N·s; indicating a useful dynamic range of physical properties suitable for bioactive oils to bioactive butters.

Double-layer optimal scheduling method for solar photovoltaic thermal system based on event-triggered MPC considering battery performance degradation

Solar photovoltaic thermal system (SPTS) can fully tap solar energy resources to realize thermal and electric supply for users simultaneously, but the volatility and uncertainty of renewable energy and load cause the imbalance of energy supply. This paper proposes a multi-time scale optimal scheduling method for SPTS based on event-triggered model predictive control (ET-MPC) considering battery performance deterioration. Firstly, SPTS is divided into day-ahead and day-in optimization layers from different time scales. Day-ahead scheduling takes the minimization economic cost as the optimization function to obtain pre-scheduling plan, and day-in scheduling adapts rolling optimization scheme based on model predictive control (MPC) to reduce power fluctuations and achieve optimal scheduling adjustment. Moreover, the battery performance decay parameter is introduced into the MPC model and embedded into the optimization problem to prolong the cyclic life deterioration, and an event-triggered mechanism is introduced into MPC to improve the computational efficiency and reduce the communication frequency. Finally, the results show that the proposed double-layer scheduling method improves 4.15 %, 66 % and 13.39 % respectively regarding cost, power fluctuation and battery maintenance, and improve the calculation efficiency of 48.89 % compared with standard MPC method, which indicates that the proposed method has good economy, stability and execution efficiency.

Steady-state flow under surface recharge through unconfined aquifer with depth-decaying hydraulic conductivity: Analytical results

This paper presents some analytical results related to groundwater flow through an unconfined horizontal aquifer induced by areal recharge on the top and a decaying hydraulic conductivity. Under steady-state conditions, and in the context of Boussinesq equation, exact analytical solutions describing drainage into one or two penetrating channels at the aquifer boundaries have been derived in closed forms. The analytical expressions have been used to investigate the existence of water divide inside the unconfined aquifer. Based on the derived analytical solutions, a closed-form analytical formula is developed for calculating groundwater transit time within Dupuit-type flow system. The analytical transit time expression is simply expressed in terms of common mathematical functions. Analytical results are verified against a numerical model and show excellent agreements. The analytical transit time is validated against a numerical one obtained from a two-dimensional model representing a rectangular unconfined aquifer. Based on the explicit closed-form solution, a fully analytical inverse problem to estimate the decay parameter is proposed using a least-square objective function. The solution of the inverse problem simply corresponds to the solution of a nonlinear algebraic equation obtained from the definition of the objective function and the form of the analytical solution.

Decay of RNA and infectious SARS-CoV-2 and murine hepatitis virus in wastewater

Wastewater-based epidemiology (WBE) has been an important tool for population surveillance during the COVID-19 pandemic and continues to play a key role in monitoring SARS-CoV-2 infection levels following reductions in national clinical testing schemes. Studies measuring decay profiles of SARS-CoV-2 in wastewater have underscored the value of WBE, however investigations have been hampered by high biosafety requirements for SARS-CoV-2 infection studies. Therefore, surrogate viruses with lower biosafety standards have been used for SARS-CoV-2 decay studies, such as murine hepatitis virus (MHV), but few studies have directly compared decay rates of both viruses. We compared the persistence of SARS-CoV-2 and MHV in wastewater, using 50 % tissue culture infectious dose (TCID50) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays to assess infectious virus titre and viral gene markers, respectively. Infectious SARS-CoV-2 and MHV indicate similar endpoints, however observed early decay characteristics differed, with infectious SARS-CoV-2 decaying more rapidly than MHV. We find that MHV is an appropriate infectious virus surrogate for viable SARS-CoV-2, however inconsistencies exist in viral RNA decay parameters, indicating MHV may not be a suitable nucleic acid surrogate across certain temperature regimes. This study highlights the importance of sample preparation and the potential for decay rate overestimation in wastewater surveillance for SARS-CoV-2 and other pathogens.

Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images.

Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R 2 >0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.