Characteristic Function Research Articles

Examining inter‐regional and intra‐seasonal differences in wintering waterfowl landscape associations among Pacific and Atlantic flyways

The Central Valley of California (CVC) and Mid‐Atlantic (MA) in the U.S. are both critical sites for nationwide food security, and many waterfowl species annually, especially during the winter, providing feeding and roosting locations for a variety of species. Mapping waterfowl distributions, using NEXRAD, may aid in the adaptive management of important waterfowl habitat and allow various government agencies to better understand the interface between wild and domestic birds and commercial agricultural practices. We used 9 years (2014–2023) of data from the US NEXRAD network to model winter waterfowl relative abundance in the CVC and MA as a function of weather, temporal period, environmental conditions, and landcover characteristics using boosted regression tree modelling. We were able to quantify the variability in effect size of 28 different covariates across space and time within two geographic regions which are critical to nationwide waterfowl management and host a high density of nationally important commercial agriculture. In general, weather, geographic (distance to features), and landcover condition (wetness index) predictors had the strongest relative effect on predicting wintering waterfowl relative abundance in both regions, while effects of land cover composition were more regionally and temporally specific. Increased daily mean temperature was a major predictor of increasing relative waterfowl abundance in both regions throughout the winter. Increasing precipitation had differing effects within regions, increasing relative waterfowl abundance in the MA, while decreasing in general within the CVC. Increasing relative waterfowl abundance in the CVC are strongly tied to the flooding of the landscape and rice availability, whereas waterfowl in the MA, where water is less limiting, are generally governed by waste grain availability and emergent wetland on the landscape. Waterfowl relative abundance in the MA was generally higher nearer to the Atlantic coast and lakes, while in the CVC they were higher nearer to lakes. Our findings promote a better understanding of spatial associations of waterfowl to landscape features and may aid in conservation and biosecurity management protocols.

CD69+CD103+CD8+ tissue-resident memory T cells possess stronger anti-tumor activity and predict better prognosis in colorectal cancer

BackgroundColorectal cancer (CRC) is one of the most prevalent cancers worldwide. Despite advancements in therapeutic methodologies, it still causes a high rate of patient mortality. CD8+ tissue-resident memory T (TRM) cells are strategically positioned to mediate effective anti-tumor responses. However, the characteristic surface molecules and functions of CD8+ TRM cells exhibit significant heterogeneity.MethodsThe roles and anti-tumor biological functions of different CD8+ TRM subsets in CRC were determined by clinical CRC samples, bioinformatics analysis, and in vitro experiments including co-culture experiments and transwell migration assays. The signaling pathways that synergistically regulate the differentiation of CD8+ TRM cells were identified by in vitro CD8+ T cell activation and inhibition assays, and the functioning transcription factors were predicted using the UCSC and JASPAR databases.ResultsWe found that different CD8+ TRM subsets existed in CRC tumor tissues, which were identified as CD69−CD103−CD8+ TRM, CD69+CD103−CD8+ TRM (SP CD8+ TRM), and CD69+CD103+CD8+ TRM (DP CD8+ TRM) subsets. Compared with SP CD8+ TRM cells, increased infiltration of DP CD8+ TRM cells predicted better prognosis and played a protective role mainly in tumor invasion and lymph node metastasis of CRC. DP CD8+ TRM cells expressed higher levels of effector molecules and exerted stronger anti-tumor effects in a FAS/FASL pathway-dependent manner. Additionally, DP CD8+ TRM cells secreted higher levels of CXCL13 and recruited B cells into tumor tissues through the CXCL13/CXCR5 signaling axis to form tertiary lymphoid structures, participating in anti-tumor immune responses. Notch and TGF-β signaling pathways synergistically regulate the differentiation of DP CD8+ TRM cells.ConclusionsWe clarified the roles and mechanisms of different CD8+ TRM subsets in CRC and identified that DP CD8+ TRM cells exert stronger anti-tumor effects and predict better prognosis, which provides ideas for developing new clinically available therapeutic targets.

A Three-Parameter Exponential Frechet Distribution: Theory and Application

A novel three-parameter distribution of the Exponential G-family distribution called the Exponential Frechet Distribution has been proposed. Some properties of the model like moment generating function, characteristic function, quantile function, survival function and hazard function were derived. Bayesian and MLE approach was used to estimate the parameter. The Exponential Frechet Distribution flexibility was demonstrated by both simulation and application to remission time of bladder cancer patients. The results revealed that the Exponential Frechet Distribution yielded a better fit in comparison with other extended distribution.

Relay‐assisted D2D communication over novel multicluster two‐wave and multi‐cluster fluctuating two‐ray channels

AbstractA decode and forward relay assisted device‐to‐device (D2D) communications over a novel multicluster two‐wave (MTW) fading is analysed with Terahertz (THz) channel conditions. Co‐channel interference (CCI) over a recently proposed multi‐cluster fluctuating two‐ray (MFTR) fading is also present at relay and receiver. Maximal ratio combining (MRC) and power harvesting based on power splitting are present at relay and receiver. A characteristic function based approach is used here to derive success probability, outage probability and capacity with outage expressions. The expressions depend on THz channel parameters, distances between various nodes in D2D system, power harvesting parameter and fading channel conditions. The system is numerically analysed under various D2D network conditions.

Unwanted or negative treatment reactions in digital psychological interventions for adolescents with chronic pain.

Reports of pain clinical trials evaluating psychological treatments often lack sufficient details on the potential and actual harm resulting from intervention. We aimed to understand how frequent and intense treatment reactions, conceptualized as unwanted symptoms, were in three clinical trials of digital Cognitive Behavioral Therapy (CBT) for adolescents with: (1) chronic primary pain, (2) sickle cell disease, and (3) chronic pancreatitis. We also aimed to understand any differences by demographic and clinical variables. Analyses were conducted with 246 youths (12-18 years old) experiencing chronic pain and one of their caregivers. 66% of the total sample was female. The number, intensity, and type of treatment reactions experienced were assessed post treatment. T-tests and Chi-squared tests were conducted to explore whether certain treatment reactions were more frequent as a function of baseline or clinical characteristics. 9% of participants experienced some negative treatment reaction. The average intensity of those events was very low on a 0-3 scale (M = 0.1, SD = 0.4). There were no differences in the prevalence or intensity as a function of participant's sex, age, race, or baseline pain intensity. However, baseline anxiety [t = -2.4 (244); p < .05] and baseline pain interference [t = -2.2 (223); p < .05] were significantly higher in those who experienced negative treatment reactions. A small number of participants reported experiencing negative treatment reactions, with a low intensity level. Those experiencing negative treatment reactions showed higher baseline anxiety and pain interference. Future research may build from our example to standardize collection of harms data in trials of psychological interventions.

Estimation of the multivariate symmetric stable distribution using the method of moments

. The multivariate symmetric stable distribution is a heavy-tailed elliptically contoured law that has many important applications in signal processing and financial mathematics. The family includes the sub-Gaussian stable distribution as a special case. This work addresses the problem of feasible estimation of the parameters of the multivariate symmetric stable distribution. We present a method based on the application of the method of moments to the empirical characteristic function. Further, we show almost sure convergence of our estimators, discover their limiting distribution, and demonstrate their finite-sample performance.

Identifying the Key Protection Areas of Alpine Marsh Wetlands in the Qinghai Qilian Mountains, China: An Ecosystem Patterns–Characteristics–Functions Combined Method

The alpine marsh wetlands in the Qilian Mountains of Qinghai (QMQ) are under constant threat from the effects of climate change and human activities. Identifying the key ecological protection areas (KEPAs) of marsh wetlands is the prerequisite for formulating protection strategies and executing spatial planning programs. The current study developed a novel method to identify the KEPAs of marsh wetlands by following the ecosystem pattern–characteristics–functions (EPCFs) combined method and the ecological source–ecological corridor–ecological node research paradigm. More specifically, an evaluation system for ecological resistance was constructed by integrating the drivers of EPCFs in the marsh wetlands. Additionally, the marsh wetland degradation disturbances were analyzed through the drivers of EPCFs incorporated with a field survey. The findings indicated the following: (1) The marsh wetlands had a total water yield of approximately 3.96 × 108 m3. The soil conservation rate and habitat quality per unit area were calculated to be 52.92 t·hm−2·a−1 and 0.992, respectively, with higher values observed on the southern bank and lower values on the northern bank of the river in the QMQ. (2) The KEPAs for the marsh wetlands covered a total extent of 996.53 km2 in the QMQ, encompassing 40 ecological sources, 39 ecological corridors, and 40 ecological nodes, predominantly located in the river source regions. (3) The KEPAs were restructured into an ecological framework comprising two ecological axes, four ecological belts, four ecological cores, and multiple nodes in the QMQ. In response to the factors contributing to the degradation of marsh wetlands, adaptive measures including prioritizing natural restoration, modifying grazing strategies, executing ecological restoration projects as a minimum, and designating protected areas have been recommended. This research could contribute to enhancing the efficiency of regional territorial planning and offer a theoretical foundation for improving the ecological protection framework of regional marsh wetlands.

Frequency analysis of tetra layered FGM cylindrical shell with S-S Edge condition

A Cylindrical shell consists of a curved surface that extends around a central axis, with its thickness being relatively small compared to its height and radius. It has wide range applications in pressure vessels and tanks, heat exchangers, aerospace etc. This article analyzes four shell surfaces, the first and third layers of functionally graded material, and the second and fourth layers of isotropic material. The natural frequency is influenced by several thick layers. The shell frequency equation is obtained by usig the Rayleigh-Ritz approach. The strain and curvature-displacement relations are derived from Sander’s shell theory. Characteristic beam functions are employed to assess the dependence of axial modal and trigonometric volume fraction law is used to attain the vibration anaylsis. Results are acquired for different thickness-to-radius and length-to-radius ratios under various edge conditions. For simply supported edge circumstances, the natural frequencies are calculated by using MATLAB software.

Identification and characteristic analysis of internal defects in rock-filled concrete based on deep learning method

The distribution characteristics and geometric morphology characteristics of defects within RFC are important factors affecting the strength properties and rupture morphology of RFC. However, the excessive size of commonly used aggregates for RFC leads to difficulties in conducting in-depth experimental studies indoors. Based on the improved U-Net and image processing technology, this research establishes an integrated model for the identification, classification, and extraction of defects inside the RFC, quantitatively counts and analyzes the acquired defect distribution characteristics and geometrical morphology characteristics, and establishes a defect characteristic distribution function that can be used for the numerical reconstruction of defects. In order to realize the acceleration of U-Net training using training weights, use VGG-16 with the fully connected layer removed instead of the Encoder part of the U-Net. The integrated model in this research can realize automatic identification, classification, and extraction of multiple types of defects at the same time, and the established distribution function of defect characteristics provides a data basis and new ideas for the establishment of RFC three-dimensional numerical models containing real defects.

Entwining Yang–Baxter maps over Grassmann algebras

In this work we construct novel solutions to the set-theoretical entwining Yang–Baxter equation. These solutions are birational maps involving non-commutative dynamical variables which are elements of the Grassmann algebra of order n. The maps arise from refactorisation problems of Lax supermatrices associated to a nonlinear Schrödinger equation. In this non-commutative setting, we construct a spectral curve associated to each of the obtained maps using the characteristic function of its monodromy supermatrix. We find generating functions of invariants for the entwining Yang–Baxter maps from the moduli of the spectral curves. Moreover, we show that a hierarchy of birational entwining Yang–Baxter maps with commutative variables can be obtained by fixing the order n of the Grassmann algebra, and we present the cases n=1 (dual numbers) and n=2. Then we discuss the integrability properties, such as Lax matrices, invariants, and measure preservation, for the obtained discrete dynamical systems.

Parameter estimation for stable distributions and their mixture

In this paper, we consider estimating the parameters of univariate α-stable distributions and their mixtures. First, using a Gaussian kernel density distribution estimator, we propose an estimation method based on the characteristic function. The optimal bandwidth parameter was selected using a plug-in method. We highlight another estimation procedure for the Maximum Likelihood framework based on the False position algorithm to find a numerical root of the log-likelihood through the score functions. For mixtures of α-stable distributions, the EM algorithm and the Bayesian estimation method have been modified to propose an efficient and valuable tool for parameter estimation. The proposed methods can be generalised to multiple mixtures, although we have limited the mixture study to two components. A simulation study is carried out to evaluate the performance of our methods, which are then applied to real data. Our results appear to accurately estimate mixtures of α-stable distributions. Applications concern the estimation of the number of replicates in the Mayotte COVID-19 dataset and the distribution of the N-acetyltransferase activity of the Bechtel et al. data for a urinary caffeine metabolite implicated in carcinogens. We compare the proposed methods, together with a detailed discussion. We conclude with the limitations of this study, together with other forthcoming work and a future implementation of an R package or Python library for the proposed methods in data modelling.

Pricing vulnerable reset options under stochastic volatility jump diffusion model using 3-D FFT

. Under the comprehensive model of assets which satisfy the triple conditions of stochastic jump, stochastic volatility, and stochastic interest rate, the pricing problem of reset options with default risk is investigated. First, two-dimensional log-normal distribution and radical process with reverting property are applied to describe sudden jump of assets and time-varying characteristics of volatility and interest rate, respectively. Further, through the principle of risk neutral pricing with the characteristic function method, we establish the joint characteristic function related to the options. Second, according to measure transform and payoff function decomposition, the analytical pricing and hedging share formulas of vulnerable reset options are given. Third, 3-D fast Fourier transform is constructed to obtain a fast and asymptotic solution of option prices. Finally, the accuracy and stability of 3-D fast Fourier transform is analyzed through numerical examples. The experimental results show that the proposed method can solve the complex pricing problem of vulnerable reset options more efficiently.

Inference with Non-Homogeneous Lognormal Diffusion Processes Conditioned on Nearest Neighbor

In this work, we approach the forecast problem for a general non-homogeneous diffusion process over time with a different perspective from the classical one. We study the main characteristic functions as mean, mode, and α-quantiles conditioned on a future time, not conditioned on the past (as is normally the case), and we observe the specific formula in some interesting particular cases, such as Gompertz, logistic, or Bertalanffy diffusion processes, among others. This study aims to enhance classical inference methods when we need to impute data based on available information, past or future. We develop a simulation and obtain a dataset that is closer to reality, where there is no regularity in the number or timing of observations, to extend the traditional inference method. For such data, we propose using characteristic functions conditioned on the past or the future, depending on the closest point at which we aim to perform the imputation. The proposed inference procedure greatly reduces imputation errors in the simulated dataset.

Advanced Scanning Technology for Volume Change Measurement of Residual Soil

Weathering processes of rocks lead to the formation of residual soil layers, which are typically characterized by a deep groundwater table and a thick unsaturated zone. Hence, the calculation of a slope’s safety factor under the influences of climatic circumstances is a function of unsaturated characteristics, such as the soil–water characteristic curve (SWCC). To determine the SWCC, the volume of the soil specimen must be determined in order to compute the void ratio and degree of saturation. The drying processes of the soil specimen led to uneven soil volume change during laboratory SWCC testing, demanding the development of a soil shrinkage curve. Several methods for measuring soil volume change have been developed over the years. However, there are significant limitations, and it is rarely used due to the difficulty linked to accurately measuring the soil volume during drying processes. In this study, a revised scanning approach is developed to evaluate residual soil volume change utilizing 3D scanning technology. The proposed method is applied in a case study on residual soil from the Old Alluvium in Singapore. The laboratory data and analysis results suggested that 3D scanning technology should be required to provide a correct estimation of the air-entry value of soil.

Evaluating the Effect of Hyperbaric Oxygen Therapy to Treat Mastectomy Skin Flap Ischemia in Breast Reconstruction: A Single-Institution Retrospective Analysis

BackgroundMastectomy skin flap ischemia is a well-known postoperative complication following mastectomy and breast reconstruction. Hyperbaric oxygen therapy (HBOT) has shown promising results for reducing the adverse effects associated with mastectomy skin flap ischemia and associated necrosis; however, there is paucity of literature regarding the indications for HBOT following breast cancer surgery. This study aimed to assess HBOT efficacy in treating and mitigating complications from postoperative tissue ischemia. Secondarily, it explored how patient-related factors may impact the success of HBOT. MethodsA retrospective analysis was conducted from January 2018 to October 2023. The study analyzed 23 patients at a single institution who were treated with HBOT for diagnosed skin flap ischemia following mastectomy and immediate breast reconstruction. Patient demographics, preoperative, and operative details were collected, as well as postoperative outcomes. The authors deemed HBOT a “success” if there were no major complications and a “failure” if there were ≥1 major complication reported within 6 months following the last HBOT treatment. Logistic regression modeled the odds of HBOT success as a function of patient characteristics. ResultsHBO was deemed a success in 15/23 patients (65%) and a failure in 8/23 (35%). Of the successes, 11 received immediate post-operative HBOT. Average age at surgery was 49 years, average BMI was 24, and average number of HBOT treatments was 11. Logistic regression analysis revealed that preceding minor complications and age both trended towards significance regarding their impact on HBO outcome. Odds of success decreased by 92% in the presence of minor complications (OR = 0.08; p<0.09) and increased by 15% with every 1-year increase in age (OR = 1.16; p<0.07) ConclusionsIn this retrospective analysis, HBOT was successful in treating postoperative mastectomy skin flap ischemia and preventing major complications in the majority of patients. Notably, age at time of surgery and presence of minor complications were the only variables found to potentially impact the success of HBOT. Future studies on a larger scale are needed to better evaluate HBOT’s therapeutic utility in mastectomy flap necrosis.

Power spectra of Dyson’s circular ensembles

The power spectrum is a Fourier series statistic associated with the covariances of the displacement from average positions of the members of an eigen-sequence. When this eigen-sequence has rotational invariance, as for the eigen-angles of Dyson’s circular ensembles, recent work of Riser and Kanzieper has uncovered an exact identity expressing the power spectrum in terms of the generating function for the conditioned gap probability of having k=0,…,N eigenvalues in an interval. These authors moreover showed how for the circular unitary ensemble integrability properties of the generating function, via a particular Painlevé VI system, imply a computational scheme for the corresponding power spectrum, and allow for the determination of its large N limit. In the present work, these results are extended to the case of the circular orthogonal ensemble and circular symplectic ensemble, where the integrability is expressed through four particular Painlevé VI systems for finite N, and two Painlevé III′ systems for the limit N→∞, and also via corresponding Fredholm determinants. The relation between the limiting power spectrum S∞(ω), where ω denotes the Fourier variable, and the limiting generating function for the conditioned gap probabilities is particularly direct, involving just a single integration over the gap endpoint in the latter. Interpreting this generating function as the characteristic function of a counting statistic allows for it to be shown that S∞(ω)∼ω→01πβ|ω|, where β is the Dyson index.

Enhancing Detection of Small Earthquake Events from the 2017 Mw 6.5 Botswana Earthquake Using Cross-Correlation Back-Projection Analysis

On 3 April 2017, an Mw 6.5 earthquake occurred in central Botswana, situated inside the southern African plate. However, in a region with sparse station coverage like Botswana, the earthquake catalog is usually largely incomplete at smaller magnitudes. Here we propose a modified back-projection method using a correlation characteristic function, which represents energy similarity and mitigates interference due to waveform complexity in regional seismic networks, aiming to enhance the detection of small seismic events. The energy-related characteristic function exhibits robust detections for low signal-to-noise ratio data, a capability not achievable by traditional arrival time picking methods. Detection reliability is ensured through a dual search constraint, optimizing effective signal count, considering nearby epicentral station signals, and accounting for seismic events clustering, which involves discarding seismic events from regions with infrequent earthquake occurrences. A total of 365 events (magnitude completeness of ∼ M 2), about four times more than the catalog obtained by other methods, have been detected within seven days after the Botswana mainshock. Most are low signal-to-noise ratio events for that are not localized by traditional methods. The resulting earthquake sequence occurred in at least three NW-SE fault strands between the Kaapvaal Craton and the Limpopo Belt. Our results, when combined with other geophysical data, suggest that the Botswana earthquake mainly results from the difference of intraplate basal dragging forces at various tectonic regions driven by the clockwise plate motions, which would generate extensional strains along the weak edges of rigid blocks.

Wavelet transform-based mode decomposition for EEG signals under general anesthesia.

Mode decomposition methods are used to extract the characteristic intrinsic mode function (IMF) from various multidimensional time series signals. We analyzed an electroencephalogram (EEG) dataset for sevoflurane anesthesia using two wavelet transform-based mode decomposition methods, comprising the empirical wavelet transform (EWT) and wavelet mode decomposition (WMD) methods, and compared the results with those from the previously reported variational mode decomposition (VMD) method. To acquire the EEG data, we used the software application EEG Analyzer, which enabled the recording of raw EEG signals via the serial interface of a bispectral index (BIS) monitor. We also created EEG mode decomposition software to perform empirical mode decomposition (EMD), VMD, EWT, and WMD operations. When decomposed into six IMFs, the EWT enables narrow band separation of the low-frequency bands IMF-1 to IMF-3, in which all central frequencies are less than 10 Hz. However, in the upper IMF of the high-frequency band, which has a center frequency of ≥ 10 Hz, the dispersion within the frequency band covered was widespread among the individual patients. In WMD, a narrow band of clinical interest is specified using a bandpass filter in a Meyer wavelet filter bank within a specific mode-decomposition discipline. When compared with the VMD and EWT methods, the IMF that was decomposed via WMD was accommodated in a narrow band with only a small variance for each patient. Multiple linear regression analyses demonstrated that the frequency characteristics of the IMFs obtained from WMD best tracked the changes in the BIS upon emergence from general anesthesia. The WMD can be used to extract subtle frequency characteristics of EEGs that have been affected by general anesthesia, thus potentially providing better parameters for use in assessing the depth of general anesthesia.

Genome-Wide Analysis Unveiled the Characteristic Features and Functions of AFC Genes of Bread Wheat (Triticum aestivum L.)

Genome-Wide Analysis Unveiled the Characteristic Features and Functions of AFC Genes of Bread Wheat (Triticum aestivum L.)

Predictors of consistent condom use among male construction workers who have engaged in concurrent sex with regular sex partners, casual sex partners, and sex workers over a 3-month period

ABSTRACT This study investigates the predictors of consistent condom use among male construction workers in South Africa who reported concurrent sexual relationships with regular partners, casual partners, and sex workers over a 3-month period. A cross-sectional survey was used to collect data from a convenience sample of 450 male workers across 18 construction work sites in the Western Cape province. Of these, 245 (54%) indicated that they had engaged in sex with all three partner types during the 3-month study period. Hierarchical multiple linear regression was then used to assess consistent condom use as a function of demographic, experiential, behavioural and cognitive characteristics. Three statistically significant predictors of consistent condom use were identified: perceived control over condom use (β = 0.252, p < 0.001), positive attitude toward condom use (β = 0.154, p < 0.05) and fear of HIV infection (β = 0.121, p < 0.05). These findings highlight the high prevalence of sexual concurrency among study participants. It also suggests that amid declining condom use, interventions which focus on enhancing an individuals’ condom application skills and efficacy, that foster positive attitudes toward condom use and that strategically incorporate fear-based messaging within a multilevel framework may potentially increase condom use among individuals in concurrent sexual relationships.