Exponential Components Research Articles

Ultrafast carrier dynamics and transient nonlinear absorption in chalcogenide perovskite BaZrS3

The unique combination of excellent semiconducting properties in halide perovskites and the high stability and nontoxicity of oxide perovskites has led to a recent surge in interest in chalcogenide perovskite BaZrS3 for optoelectronic applications. However, to realize its potential in future device technologies, a comprehensive understanding of photoexcited carrier dynamics and transient optical response is imperative, yet it remains largely unexplored for BaZrS3. In this work, employing transient absorption spectroscopy, we have revealed that photoexcited carriers in epitaxial BaZrS3 nanofilms exhibit two exponential decay components relating to optical phonon cooling and interband recombinations. Meanwhile, our investigation unveils an intriguing transient nonlinear absorption phenomenon in BaZrS3, characterized by the ultrafast switching of the pump-induced transparency (i.e., the saturable absorption) to the absorption enhancement within a timescale commensurate with the measurement resolution (hundreds of femtosecond). This study provides crucial dynamic insights essential for leveraging chalcogenide perovskites, such as BaZrS3, in the development of advanced optoelectronic devices.

Bond-slip model of corroded plain round bars in low-strength concrete under cyclic and monotonic loading

The effect of corrosion on the overall behavior of beam-type bond-slip samples constructed from low-strength concrete and plain round bars was examined in this study. First, a set of nominally identical specimens underwent testing under both monotonic and cyclic loading, and subsequently, the bond-slip interaction was assessed for each individual sample. The observed failure mode for plain round bars was direct pullout without concrete splitting apart, characterized by the loss of cohesion between the rebar and the adjacent concrete surface. Then, an analytical relationship was established by fitting a curve to the average experimental data using the method of least squares. Corrosion-degradation in the bond stress was considered by incorporating an exponential component into the equation of the reference bond-slip curve (i.e., null corrosion). Besides, the degradation in bond strength was predicted as a function of corrosion level, which is in the form of an exponential curve. The maximum surface crack width, an easily quantified variable on-site, was correlated with the bond strength of corroded bars. The regression analysis successfully established the optimal relationship between the maximum surface crack width and the corrosion level in an exponential form as well. Notably, the majority of the data in all cases fell within the 95% confidence interval.

A room-temperature ultrafast carrier dynamical study and thickness-dependent investigation of WTe2 thin films on a flexible PET substrate

In the current era of increasing demand for optoelectronic-based devices with ultra-rapid response, it is important to understand the processes associated with the relaxation dynamics of hot carriers and transient electrical properties of WTe2 material under photoexcitation of charge carriers. In this work, using femtosecond laser pump–probe spectroscopy at room temperature we performed the transient absorption measurement on sputtered deposited WTe2 thin films having four different thicknesses to study dynamics associated with the relaxation of their hot carriers. The relaxation dynamics of photoexcited charge carriers undergo three exponential decay components associated with electron–phonon thermalization in the conduction band and phonon-assisted electron–hole recombination between the electron and hole pocket. The thickness-dependent investigation of WTe2 thin films reveals that the electron–hole recombination process is more prominent in thicker films than in thinner films, supporting previously published theoretical and experimental conclusions. The Ultrafast study of WTe2 thin films suggests that it is a suitable material for future ultrafast optoelectronic-based device applications.

Stochastic ordering results on extreme order statistics from dependent samples with Archimedean copula

This paper considers parallel and series systems with heterogeneous components having dependent exponential lifetimes. The underlying dependence is assumed to be Archimedean and the component lifetimes are supposed to be connected according to an Archimedean copula. Sufficient conditions are found to dominate a parallel system with heterogenous exponential components, with respect to the dispersive order, by another parallel system with homogenous exponential components where the dependence structure between lifetimes of components is the same. We also compare two series systems (and two parallel systems) with general one-parameter dependent components and with respect to the usual stochastic ordering. Examples are given to illustrate the theoretical findings.

Energy dependence of x‐ray beam size produced by polycapillary x‐ray optics

AbstractIn this work, we studied the x‐ray energy dependence of x‐ray beam diameter focused by polycapillary optics. A quantitative beam diameter–energy relation enables more accurate estimation of the element‐specific interrogation area of a sample using the compositional maps produced by a micro‐XRF system. This improves upon our ability to visualize individual beam‐diameter sized mineral grains and in turn directly benefits Planetary Instrument for X‐ray Lithochemistry (PIXL) analyses of martian soil in addition to benefitting other micro‐focused x‐ray fluorescence (XRF) systems. The spatial distribution of an array of characteristic XRF emission lines was measured by sampling via a knife‐edge approach with small motor stepping of the beam across target edges. Data taken as part of this effort, from the Planetary Flight Model (PFM), were limited to only seven beam energies corresponding to the elements Ni, Cu, Se, Ta, Au, Ti and Ba. Hence, we conducted additional analysis using JPL's lab‐based breadboard (LBB) micro‐XRF system, a system that emulates PIXL's functionality where we measured beam diameter corresponding to 18 elements: Na, Mg, Al, Si, Cl, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Ge, Se, Sr and Mo. The experimental results were also compared with Monte Carlo simulations. The beam diameter (y)–energy (x) relation that we obtained for LBB was y = 185.79 exp(−0.078x) whose exponential component was then used to get a more accurate relation for the PFM even with the limited data set: y = 227.53 exp(−0.078x). The difference in the two coefficients for the PFM and LBB stems mainly from the difference in the polycapillary optic design, and this work establishes x‐ray beam diameter versus energy relation quantitatively for both the systems.

Stochastic comparison of parallel systems with heterogeneous dependent exponential components

Let X=(X1,…,Xn) and Y=(Y1,…,Yn) be two random vectors with common Archimedean copula with generator function ϕ, where, for i=1,…,n, Xi is an exponential random variable with hazard rate λi and Yi is an exponential random variable with hazard rate λ. In this paper we prove that under some sufficient conditions on the function ϕ, the largest order statistic corresponding to X is larger than that of Y according to the dispersive ordering and hazard rate ordering. The new results generalized the results in Dykstra et al. (1997) and Khaledi and Kochar (2000). We show that the new results can be applied to some well known Archimedean copulas.

Size‐Dependent Optical Properties and Exciton Self‐Trapping Emission in Carbon Quantum Dots

AbstractCarbon quantum dots (CQDs), synthesized through controlled microplasma treatment of orange juice, exhibit unique luminescent characteristics. The impact of synthesis time on particle size was investigated. Deconvoluted emission spectra displayed broad bands, peaking at an excitation wavelength of 350 nm for CQD sizes of 2.06, 2.4, and 3.09 nm, indicating multiple fluorescence peaks. This suggests a mixture of CQDs with different excitation energies on their surfaces. Luminescence kinetics unveiled three exponential decay components with time constants of 2.73, 4.61, and 3.27 ns, indicating multiple luminescent centers. Emission behavior affected by excitation wavelengths ranging from 350 to 490 nm suggests that quantum transition probabilities are influenced by impurities or defects. These findings emphasize the size‐dependent optical properties and exciton self‐trapping (EST) emission of CQDs. The calculation of the Huang‐Rhys factor S values underscores the profound influence of carrier‐phonon coupling and the Huang‐Rhys factor on the emergence of ESTs within CQDs. Understanding these interactions is crucial for fully utilizing the capabilities of CQDs in applications spanning optoelectronics, sensors, bioimaging, and various technological fields.

A Secure Certificate-Based Data Integrity Auditing Protocol with Cloud Service Providers

With the surge in cloud storage popularity, more individuals are choosing to store large amounts of data on remote cloud service providers (CSPs) to save local storage resources. However, users’ primary worries revolve around maintaining data integrity and authenticity. Consequently, several cloud auditing methods have emerged to address these concerns. Many of these approaches rely on traditional public-key cryptography systems or are grounded in identity-based cryptography systems or certificateless cryptography systems. However, they are vulnerable to the increased costs linked with certificate management, key escrow, or the significant expenses of establishing a secure channel, respectively. To counter these limitations, Li et al. introduced a certificate-based cloud auditing protocol (LZ22), notable for its minimal tag generation overhead. Nonetheless, this protocol exhibits certain security vulnerabilities. In this paper, we devise a counterfeiting technique that allows the CSP to produce a counterfeit data block with an identical tag to the original one. Our counterfeiting method boasts a 100% success rate ∀ data block and operates with exceptional efficiency. The counterfeiting process for a single block of 10 kB, 50 kB, and 100 kB takes a maximum of 0.08 s, 0.51 s, and 1.04 s, respectively. By substituting the exponential component of homomorphic verifiable tags (HVTs) with non-public random elements, we formulate a secure certificate-based cloud auditing protocol. In comparison to the LZ22 protocol, the average tag generation overhead of our proposed protocol is reduced by 6.80%, 13.78%, and 8.66% for data sizes of 10 kB, 50 kB, and 100 kB, respectively. However, the auditing overhead of our proposed protocol shows an increase. The average overhead rises by 3.05%, 0.17%, and 0.45% over the LZ22 protocol’s overhead for data sizes of 10 kB, 50 kB, and 100 kB, correspondingly.

A hyperelastic strain energy function for isotropic rubberlike materials

A three parameter novel hyperelastic strain energy function is introduced in this paper for soft and rubber-like materials. The function integrates a non-separable exponential component with a single term Ogden-type polynomial-like function, resulting in an exponential-polynomial based strain energy function. This helps in capturing both small and large deformation (stretch) behaviours of hyperelastic materials. The structure of the model is simple and validated against several experimental datasets including rubbers, hydrogel, and soft tissues. The model is reported to capture key material behaviors, including strain stiffening and various deformation paths. Through comparative studies with well-known models like the Ogden (six parameters) and Yeoh (three parameters), the model’s effectiveness is established. Furthermore, the model successfully addresses pressure-inflation instability in thin spherical balloons. It’s applicability extends to biological materials, as evidenced by its effectiveness in characterizing porcine brain tissue and a monkey’s bladder.

Crop yield prediction using effective deep learning and dimensionality reduction approaches for Indian regional crops

Crop yield prediction (CYP) at the field level is crucial in quantitative and economic assessment for creating agricultural commodities plans for import-export strategies and enhancing farmer incomes. Crop breeding has always required a significant amount of time and money. CYP is developed to forecast higher crop production. This paper proposes an efficient deep learning (DL) and dimensionality reduction (DR) approaches for CYP for Indian regional crops. This paper comprised ‘3′ phases: preprocessing, DR, and classification. Initially, the agricultural data of the south Indian region are collected from the dataset. Then preprocessing is applied to the collected dataset by performing data cleaning and normalization. After that, the DR is performed using squared exponential kernel-based principal component analysis (SEKPCA). Finally, CYP is based on a weight-tuned deep convolutional neural network (WTDCNN), which predicts the high crop yield profit. The simulation outcomes shows that the proposed method attains superior performance for CYP compared to exiting schemes with an improved accuracy of 98.96 %. The novelty of the proposed approach lies in the combination of DL, DR, and WTDCNN techniques for accurate crop yield prediction, specifically tailored for Indian regional crops.

Orderings of extremes among dependent extended Weibull random variables

Abstract In this work, we consider two sets of dependent variables $\{X_{1},\ldots,X_{n}\}$ and $\{Y_{1},\ldots,Y_{n}\}$ , where $X_{i}\sim EW(\alpha_{i},\lambda_{i},k_{i})$ and $Y_{i}\sim EW(\beta_{i},\mu_{i},l_{i})$ , for $i=1,\ldots, n$ , which are coupled by Archimedean copulas having different generators. We then establish different inequalities between two extremes, namely, $X_{1:n}$ and $Y_{1:n}$ and $X_{n:n}$ and $Y_{n:n}$ , in terms of the usual stochastic, star, Lorenz, hazard rate, reversed hazard rate and dispersive orders. Several examples and counterexamples are presented for illustrating all the results established here. Some of the results here extend the existing results of [5] (Barmalzan, G., Ayat, S.M., Balakrishnan, N., & Roozegar, R. (2020). Stochastic comparisons of series and parallel systems with dependent heterogeneous extended exponential components under Archimedean copula. Journal of Computational and Applied Mathematics380: Article No. 112965).

Diminished differentiation of rewards in individuals at clinical high-risk for psychosis.

Reward processing is impaired in people with schizophrenia, which may begin in the clinical high-risk (CHR) for psychosis period. The Monetary Incentive Delay (MID) task has been important in understanding the neural correlates of reward processing deficits in various psychiatric disorders. Previous research has found that CHR individuals have an imprecise mental representation of rewards, which leads to a diminished differentiation between rewards, though this has not been observed behaviorally. A total of 19 CHR individuals and 20 controls were given a novel variant of the MID task, designed to examine how modulating reward context may impact responses to reward cues, a process often referred to as "adaptive coding." Both groups appeared to update their behavior in response to the rewards available in this adaptive task. However, when compared to controls who showed a more graded decrease in response time to increasing reward contexts, CHR individuals appeared to have a sharp decrease in response time in the low reward context that is nearly stable across higher reward contexts. This is largely driven by the exponential component of the response time distribution, which is often interpreted to be more cognitively or effortfully influenced. Response times are related to negative symptoms, but not positive symptoms, disorganized symptoms, or estimated intelligence. Although an adaptive coding effect was not observed, these results provide novel insight into the reward processing mechanisms and volitional processes in the CHR population, as this was the first study to observe the diminished differentiation of rewards behaviorally.

BUDDI-MaNGA

The many unique properties of galaxies are shaped by physical processes that affect different components of the galaxy – such as their bulges and discs – in different ways, and they leave characteristic imprints on the light and spectra of these components. Disentangling these spectra reveals vital clues that can be traced back in time to understand how galaxies, and their components, form and evolve throughout their lifetimes. With BUDDI, we have decomposed the integral field unit (IFU) datacubes in SDSS-MaNGA DR17 into Sérsic bulge and exponential disc components and extracted clean bulge and disc spectra. BUDDI-MaNGA is the first large statistical sample of such decomposed spectra of 1452 galaxies covering morphologies from ellipticals to late-type spirals. We derive stellar masses of the individual components with spectral energy distribution (SED) fitting using BAGPIPES and estimate their mean mass-weighted stellar metallicities and stellar ages using PPXF. With this information, we reconstruct the mass assembly histories of the bulges and discs of 968 spiral galaxies (Sa-Sm types). Our results show a clear downsizing effect especially for the bulges, with more massive components assembling earlier and faster than the less massive ones. Additionally, we compare the stellar populations of the bulges and discs in these galaxies, and find that a majority of the bulges host more metal-rich and older stars than their disc counterparts. Nevertheless, we also find a non-negligible fraction of the spiral galaxy population in our sample contains bulges that are younger and more metal-enhanced than their discs. We interpret these results, taking into account how their formation histories and current stellar populations depend on stellar mass and morphology.

Examining Cesarean Section Rates in Ghana’s 10 Regions Over a Decade a Comprehensive National Investigation

This study examines cesarean section (C‐section) deliveries in Ghana from 2008 to 2017 in 10 regions, distinguishing between scheduled and emergency procedures. Scheduled C‐sections target specific maternal conditions, such as advanced age, multiparity, and medical history, while emergency C‐sections address acute fetal distress, preeclampsia, bleeding, and other urgent situations. The analysis reveals various regional patterns, with the Brong‐Ahafo Region showing a potential deceleration after 2017 and the Upper West Region indicating a possible acceleration. The high number of C‐sections in Greater Accra and Ashanti may be related to population density and health facilities. The study proposes empirical models, including linear, quadratic, and exponential components, emphasizing quasilinearity. The exponential model suggests transient and permanent phases of cesarean frequency, with the latter dominated by quasilinearity. Optimal parameter values are determined, which highlights the stability of the model. However, caution is advised when projecting too far into the future due to the inevitable slowing of observed trends. The findings offer insights for healthcare planning, resource allocation, and policymaking, emphasizing the need for region‐specific approaches and ongoing monitoring of cesarean dynamics to inform nuanced interventions.

A Novel Crop Yield Prediction Using Deep Learning and Dimensionality Reduction

Crop yield prediction (CYP) at the field level is crucial in quantitative and economic assessment for creating agricultural commodities plans for import-export strategies and enhancing farmer incomes. Crop breeding has always required a significant amount of time and money. CYP is developed to forecast higher crop production. This paper proposes an efficient deep learning (DL) and dimensionality reduction (DR) approaches for CYP for Indian regional crops. This paper comprised ‘3’ phases: preprocessing, DR, and classification. Initially, the agricultural data of the south Indian region are collected from the dataset. Then preprocessing is applied to the collected dataset by performing data cleaning and normalization. After that, the DR is performed using squared exponential kernel-based principal component analysis (SEKPCA). Finally, CYP is based on a weight-tuned deep convolutional neural network (WTDCNN), which predicts the high crop yield profit. The simulation outcomes shows that the proposed method attains superior performance for CYP compared to exiting schemes with an improved accuracy of 98.96%.

Prominently enhanced luminescence from a continuous monolayer of transition metal dichalcogenide on all-dielectric metasurfaces

Abstract 2D materials such as transition metal dichalcogenides (TMDCs) are a new class of atomic-layer materials possessing optical and electric properties that significantly depend on the number of layers. Electronic transitions can be manipulated in artificial resonant electromagnetic (EM) fields using metasurfaces and other designed nanostructures. Here, we demonstrate prominently resonant enhancement in the photoluminescence (PL) of atomic monolayer, WS2, doped with a small quantity of Mo. The excitonic PL showed a strong enhancement effect on a higher-order magnetic resonance of all-dielectric metasurfaces consisting of periodic arrays of Si nanopellets. The PL intensity witnessed a 300-fold enhancement compared to the reference PL intensity on a flat silicon dioxide (SiO2) layer, which suggests a drastic change in the dynamics of photoexcited states. Confocal PL microscopy and the analysis revealed that the single photons were coherently emitted from the TMDC monolayer on the metasurface. Furthermore, examining the PL lifetime in the ps and ns timescales clarified two exponential components at the prominent exciton PL: a short-time component decaying in 22 ps and a long-time component lasting over 10 ns. Therefore, we can infer that the radiative components were significantly activated in the TMDC monolayer on the metasurfaces in comparison to the reference monolayer on a flat SiO2 layer.

Robust Variable Selection with Exponential Squared Loss for the Spatial Error Model

With the widespread application of spatial data in fields like econometrics and geographic information science, the methods to enhance the robustness of spatial econometric model estimation and variable selection have become a central focus of research. In the context of the spatial error model (SEM), this paper introduces a variable selection method based on exponential square loss and the adaptive lasso penalty. Due to the non-convex and non-differentiable nature of this proposed method, convex programming is not applicable for its solution. We develop a block coordinate descent algorithm, decompose the exponential square component into the difference of two convex functions, and utilize the CCCP algorithm in combination with parabolic interpolation for optimizing problem-solving. Numerical simulations demonstrate that neglecting the spatial effects of error terms can lead to reduced accuracy in selecting zero coefficients in SEM. The proposed method demonstrates robustness even when noise is present in the observed values and when the spatial weights matrix is inaccurate. Finally, we apply the model to the Boston housing dataset.

Galactic Diffuse γ-Ray Emission from GeV to PeV Energies in Light of Up-to-date Cosmic-Ray Measurements

Diffuse γ-ray emission between 10 and 1000 TeV from the Galactic plane was recently measured by the Large High Altitude Air Shower Observatory (LHAASO). These observations will help tremendously in constraining the propagation and interaction of cosmic rays in the Milky Way. Additionally, new measurements of cosmic-ray spectra reach a very high precision of up to 100 TeV energies, revealing multiple spectral structures of various species. In this work, based on up-to-date measurements of local cosmic-ray spectra and a simplified propagation setup, we confront a model prediction of diffuse γ-ray emission with measurements of diffuse γ-rays. To better constrain the low-energy part of the model, we analyze the 14.6 yr of Fermi Large Area Telescope (Fermi-LAT) data to extract the Galactic diffuse emission between 1 and 500 GeV from the same sky regions of LHAASO, after subtracting the contribution from known sources and the isotropic diffuse γ-ray background. The joint Fermi-LAT and LHAASO spectra thus cover a very wide energy range from 1 GeV to 1 PeV with small gaps from 0.5 to 10 TeV. Compared with the prediction, we find that clear excesses between several GeV and ∼60 TeV of the diffuse emission exist. Possible reasons to explain the excesses may include unresolved sources or more complicated propagation models. We illustrate that an exponential cutoff power-law component with an index of −2.40 and a cutoff energy of ∼30 TeV is able to account for such excesses.

Flow recession behavior of preferential subsurface flow patterns with minimum energy dissipation

Abstract. Understanding the properties of preferential flow patterns is a major challenge in subsurface hydrology. Most of the theoretical approaches in this field stem from research on karst aquifers, where two or three distinct flow components with different timescales are typically considered. This study is based on a different concept: a continuous spatial variation in transmissivity and storativity over several orders of magnitude is assumed. The distribution and spatial pattern of these properties are derived from the concept of minimum energy dissipation. While the numerical simulation of such systems is challenging, it is found that a restriction to a dendritic flow pattern, similar to rivers at the surface, works well. It is also shown that spectral theory is useful for investigating the fundamental properties of such aquifers. As a main result, the long-term recession of the spring draining the aquifer during periods of drought becomes slower for large catchments. However, the dependence of the respective recession coefficient on catchment size is much weaker than for homogeneous aquifers. Concerning the short-term behavior after an instantaneous recharge event, strong deviations from the exponential recession of a linear reservoir are observed. In particular, it takes a considerable time span until the spring discharge reaches its peak. The order of magnitude of this rise time is one-seventh of the characteristic time of the aquifer. Despite the strong deviations from the linear reservoir at short time spans, the exponential component typically contributes more than 80 % to the total discharge. This fraction is much higher than expected for karst aquifers and even exceeds the fraction predicted for homogeneous aquifers.

Deep K-band surface brightness photometry of dE galaxies

Context. Dwarf elliptical galaxies (dEs) are the most abundant in the Universe. Research into these objects in connection with late-type dwarf galaxies is important for evaluating theories of dwarf galaxy formation and evolution. Aims. Our past studies (2000-2010) suggested a possible evolutionary link between early- and late-type dwarf galaxies. These results are based on deep near-infrared (NIR) surface photometry data of dwarf irregulars (dIs), blue compact dwarfs (BCDs), and a small sample of Virgo dEs. As a continuation of those works, in 2017 we embarked on a study of dEs using the same surface photometry methods, with the aim being to compare early- and late-type dwarfs based on homogeneous datasets. Methods. We selected 74 dEs from two different environments for which we obtained deep images. Isophotal analysis was performed on the images to obtain surface brightness profiles. The two sampled environments were the Local Volume and Virgo cluster, which provide the possibility to compare isolated evolution against evolution in crowded environments. To compare dwarf datasets homogeneously, we used the NIR Ks band which is known to be a better gauge of galaxy mass, with reduced extinction compared to visible bands. Results. In this first paper, we derive apparent physical parameters for 72 dEs from deep NIR imaging and provide preliminary fitting results of their surface brightness profiles. Two targets were undetected in the Ks images, indicating possible misclassification. Physical parameters of 16 dEs are measured for the first time and the parameters of the remaining 56 dEs are compared with the literature. We obtain a mean difference between the measured physical parameters and the results from prior studies of about 0.2″ for the galaxy center coordinates, ≈20″ for the semi-major axis, ≈0.4 mag for the total apparent magnitude, ≈0.11 for the ellipticity, and ≈14° for the position angle. We find well-fitting surface brightness profiles for the dEs using the hyperbolic secant (sech) model combined with an exponential component. Alternatively, we find good agreement with observations for a sech plus a de Vaucouleurs law.