Interaction between systemic iron parameters and left ventricular structure and function in the preserved ejection fraction population:a two-sample bidirectional Mendelian randomization study

BACKGROUND Left ventricular(LV)remodeling and diastolic function in people with heart failure(HF)are correlated with iron status;however,the causality is uncertain.This Mendelian randomization(MR)study investigated the bidirectional causal relationship between systemic iron parameters and LV structure and function in a preserved ejection fraction population.METHODS Transferrin saturation(TSAT),total iron binding capacity(TIBC),and serum iron and ferritin levels were extracted as instrumental variables for iron parameters from meta-analyses of public genome-wide association studies.Individuals without myocardial infarction history,HF,or LV ejection fraction(LVEF)<50%(n=16,923)in the UK Biobank Cardiovascular Magnetic Resonance Imaging Study constituted the outcome dataset.The dataset included LV end-diastolic volume,LV endsystolic volume,LV mass(LVM),and LVM-to-end-diastolic volume ratio(LVMVR).We used a two-sample bidirectional MR study with inverse variance weighting(IVW)as the primary analysis method and estimation methods using different algorithms to improve the robustness of the results.RESULTS In the IVW analysis,one standard deviation(SD)increased in TSAT significantly correlated with decreased LVMVR(β=-0.1365;95%confidence interval[CI]:-0.2092 to-0.0638;P=0.0002)after Bonferroni adjustment.Conversely,no significant relationships were observed between other iron and LV parameters.After Bonferroni correction,reverse MR analysis showed that one SD increase in LVEF significantly correlated with decreased TSAT(β=-0.0699;95%CI:-0.1087 to-0.0311;P=0.0004).No heterogeneity or pleiotropic effects evidence was observed in the analysis.CONCLUSIONS We demonstrated a causal relationship between TSAT and LV remodeling and function in a preserved ejection fraction population.

MAXIMAL FUNCTION CHARACTERIZATIONS OF HARDY SPACES ASSOCIATED WITH BOTH NON-NEGATIVE SELF-ADJOINT OPERATORS SATISFYING GAUSSIAN ESTIMATES AND BALL QUASI-BANACH FUNCTION SPACES

Assume that L is a non-negative self-adjoint operator on L^(2)(ℝ^(n))with its heat kernels satisfying the so-called Gaussian upper bound estimate and that X is a ball quasi-Banach function space onℝ^(n) satisfying some mild assumptions.Let HX,L(ℝ^(n))be the Hardy space associated with both X and L,which is defined by the Lusin area function related to the semigroup generated by L.In this article,the authors establish various maximal function characterizations of the Hardy space HX,L(ℝ^(n))and then apply these characterizations to obtain the solvability of the related Cauchy problem.These results have a wide range of generality and,in particular,the specific spaces X to which these results can be applied include the weighted space,the variable space,the mixed-norm space,the Orlicz space,the Orlicz-slice space,and the Morrey space.Moreover,the obtained maximal function characterizations of the mixed-norm Hardy space,the Orlicz-slice Hardy space,and the Morrey-Hardy space associated with L are completely new.

Improved Particle Swarm Optimization for Parameter Identification of Permanent Magnet Synchronous Motor

In the process of identifying parameters for a permanent magnet synchronous motor,the particle swarm optimization method is prone to being stuck in local optima in the later stages of iteration,resulting in low parameter accuracy.This work proposes a fuzzy particle swarm optimization approach based on the transformation function and the filled function.This approach addresses the topic of particle swarmoptimization in parameter identification from two perspectives.Firstly,the algorithm uses a transformation function to change the form of the fitness function without changing the position of the extreme point of the fitness function,making the extreme point of the fitness function more prominent and improving the algorithm’s search ability while reducing the algorithm’s computational burden.Secondly,on the basis of themulti-loop fuzzy control systembased onmultiplemembership functions,it is merged with the filled function to improve the algorithm’s capacity to skip out of the local optimal solution.This approach can be used to identify the parameters of permanent magnet synchronous motors by sampling only the stator current,voltage,and speed data.The simulation results show that the method can effectively identify the electrical parameters of a permanent magnet synchronous motor,and it has superior global convergence performance and robustness.

Spatiotemporal variations of parameters of internal solitary waves in the northern South China Sea

The dynamic parameters for internal solitary waves(ISWs)derived from the extended Korteweg-de Vries(eKdV)equation play an important role in the understanding and prediction of ISWs.The spatiotemporal variations of the dynamic parameters of the ISWs in the northern South China Sea(SCS)were studied based on the reanalysis of long-term temperature and salinity datasets.The results for spectrum analysis show that there are definite geographical differences for the periodic variation of the parameters:in shallow water,all parameters vary with a wave period of one year,while in deep water wave components of the parameters at other frequencies exist.Using wavelet analysis,the wavelet power spectral densities in deep water exhibited an inter-annual variation pattern.For example,the wave component of the dispersion coefficient with a wave period of about half a year reached its power peak once every two years.Based on previous work,this inter-annual variation pattern was deduced to be caused by dynamic processes.In further work on the regulatory mechanisms,empirical orthogonal function(EOF)decomposition was performed.It was found that the modes of the dispersion coefficient have different geographical distributions,explaining the reason why the wave components in different frequencies appeared in different locations.The numerical simulation results confirm that the variations in the parameters of the ISWs derived from the eKdV equation could affect the waveforms significantly because of changes in the polarity of the ISWs.Therefore,the periodic variations of the dynamic parameters are related to the geographical location because of dynamic processes operating.

Fitness of Four-Parameter Beta Distribution Function for Forecasting Gold Reserve and Its Production Lifespan in Ghana

Ghana, renowned for its abundant gold reserves, plays a significant role in the global mining industry. Effective management and accurate forecasting of these reserves are vital for sustainable resource utilization and economic planning. Forecasting gold reserves and estimating their production lifespan are complex tasks that require robust statistical models capable of capturing the underlying dynamics of gold deposit accumulation and extraction. To this end, the four-parameter Beta distribution function emerges as a promising candidate due to its flexibility and ability to handle non-negative data. This research aims to investigate the fitness and applicability of the four-parameter Beta distribution function for forecasting Ghana’s gold reserves and estimating the production lifespan of this precious resource. The empirical paper relied mainly on quarterly secondary datasets on gold reserve between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Beta, Weibull, Normal, Logistic and Gamma were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the four-parameter Beta distribution provided the best fit for gold reserve in Ghana. At a 99.9% confidence level and considering the current annual average gold production estimate of 3,700,031.248 to 4,302,647.888 ounces, the projected lifespan of gold production in Ghana extends to the year 1,953,765. This astounding estimate suggests that the country’s gold reserves are expected to sustain production for an extended period, providing a critical resource for economic development and supporting the mining industry well into the distant future.

Fitness of Four-Parameter Beta Distribution Function for Forecasting Gold Reserve and Its Production Lifespan in Ghana

Ghana, renowned for its abundant gold reserves, plays a significant role in the global mining industry. Effective management and accurate forecasting of these reserves are vital for sustainable resource utilization and economic planning. Forecasting gold reserves and estimating their production lifespan are complex tasks that require robust statistical models capable of capturing the underlying dynamics of gold deposit accumulation and extraction. To this end, the four-parameter Beta distribution function emerges as a promising candidate due to its flexibility and ability to handle non-negative data. This research aims to investigate the fitness and applicability of the four-parameter Beta distribution function for forecasting Ghana’s gold reserves and estimating the production lifespan of this precious resource. The empirical paper relied mainly on quarterly secondary datasets on gold reserve between the years 2009 and 2022 secured from the Minerals Commission of Ghana, Accra. Several known statistical distributions including Beta, Weibull, Normal, Logistic and Gamma were explored with Maximum Likelihood Estimation (MLE) and evaluated using model selection criteria as AIC and BIC. Goodness of Fits were evaluated using Kolmogorov-Smirnov Test (K-S), Cramer-Von Mises Statistic and Anderson-Darling Statistic. Based on the analysis conducted, the four-parameter Beta distribution provided the best fit for gold reserve in Ghana. At a 99.9% confidence level and considering the current annual average gold production estimate of 3,700,031.248 to 4,302,647.888 ounces, the projected lifespan of gold production in Ghana extends to the year 1,953,765. This astounding estimate suggests that the country’s gold reserves are expected to sustain production for an extended period, providing a critical resource for economic development and supporting the mining industry well into the distant future.

Simulation of γ spectrum-shifting based on the parameter adjustment of Gaussian function space

Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-shifting.The transient characteristics of energy spectrum were described by the Gaussian function space,and then the Gaussian function space was transferred by parameter adjustment method.Furthermore,the spectrum-shifting in measurement of energy spectrum was simulated.The applied example shows that the parameters can be adjusted flexibly by this method to meet the various requirements in simulation of energy spectrum-shifting.This method was one parameterized simulation method with good performance for the practical application.

Berezin Quantization of Gaussian Functions Depending by a Quantum and Compression Parameter

The aim of this work is to study the Berezin quantization of a Gaussian state. The result is another Gaussian state that depends on a quantum parameter α, which describes the relationship between the classical and quantum vision. The compression parameter λ>0 is associated to the harmonic oscillator semigroup.

Effects of sleep bruxism on functional and occlusal parameters:a prospective controlled investigation

This study was conducted to verify the results of a preceding retrospective pilot study by means of a prospective controlled investigation including a larger sample size. Therefore, the aim of this clinical investigation was to analyze the relationship between sleep bruxism and several functional and occlusal parameters. The null hypothesis of this study was that there would be no differences among sleep bruxism subjects and non-sleep bruxism controls regarding several functional and occlusal parameters. Fifty-eight sleep bruxism subjects and 31 controls participated in this study. The diagnosis sleep bruxism was based on clinical criteria of the American Academy of Sleep Medicine. Sixteen functional and occlusal parameters were recorded clinically or from dental study casts. Similar to the recently published retrospective pilot study, with a mean slide of 0.77 mm （s.d., 0.69 mm） in the sleep bruxism group and a mean slide of 0.4 mm （s.d., 0.57 mm） in the control group, the evaluation of the mean comparison between the two groups demonstrated a larger slide from centric occlusion to maximum intercuspation in sleep bruxism subjects （Mann-Whitney U-test; P=O.O08）. However, following Bonferroni adjustment, none of the 16 occlusal and functional variables differed significantly between the sleep bruxism subjects and the non-sleep bruxism controls. The present study shows that the occlusal and functional parameters evaluated do not differ between sleep bruxism subjects and non-sleep bruxism subjects. However, as the literature reveals a possible association between bruxism and certain subgroups of temporomandibular disorders, it appears advisable to incorporate the individual adaptive caoacitv of the stomatognathic svstem into future investigations.

LAD PARAMETER ESTIMATION of SaS BASED on SAMPLE CHARACTERISTIC FUNCTION

Parameter estimation to alpha stable distribution is difficult for without a explicit probability density function. On the base of sample characteristic function,an iterative LAD parameter estimation algorithm for SaS is discussed. The example illustrates that the algorithm is feasible and efficient.

The Most Probable Mechanism Function and Kinetic Parameters of Gibbsite Dissolution in NaOH

Determination of probable mechanism function and kinetic parameters is important to hydrometallurgical kinetics.In this work,the most probable mechanism function and kinetic parameters of gibbsite dissolution in NaOH solution are studied.The sample,the mixture of synthetic gibbsite and sodium hydroxide solution,was scanned in high-pressure differential scanning calorimetry(DSC) equipment with the heating rate of 10 K·min-1. Integral equation and differential equation of non-isothermal kinetics were solved to fit the data related to DSC curve.According to the calculation results,the most probable mechanism function for pure synthetic gibbsite dissolution in sodium hydroxide solution is presented based on the optimum procedure in the database of the mechanism function.The apparent activation energy obtained is(75±1) kJ·mol-1,the frequency factor is 10 8±1mol·s-1,and the reaction is a second order reaction.

Comparison Between Radial Basis Function Neural Network and Regression Model for Estimation of Rice Biophysical Parameters Using Remote Sensing

The radial basis function （RBF） emerged as a variant of artificial neural network. Generalized regression neural network （GRNN） is one type of RBF, and its principal advantages are that it can quickly learn and rapidly converge to the optimal regression surface with large number of data sets. Hyperspectral reflectance （350 to 2500 nm） data were recorded at two different rice sites in two experiment fields with two cultivars, three nitrogen treatments and one plant density （45 plants m^-2）. Stepwise multivariable regression model （SMR） and RBF were used to compare their predictability for the leaf area index （LAI） and green leaf chlorophyll density （GLCD） of rice based on reflectance （R） and its three different transformations, the first derivative reflectance （D1）, the second derivative reflectance （D2） and the log-transformed reflectance （LOG）. GRNN based on D1 was the best model for the prediction of rice LAI and CLCD. The relationships between different transformations of reflectance and rice parameters could be further improved when RBF was employed. Owing to its strong capacity for nonlinear mapping and good robustness, GRNN could maximize the sensitivity to chlorophyll content using D1. It is concluded that RBF may provide a useful exploratory and predictive tool for the estimation of rice biophysical parameters.

Synthetically quantitative evaluation function of characteristic parameters on CO_2 arc welding process

The statistical probability and their variation regularity of the measurable characteristic parameters in the CO 2 arc welding droplet short circuiting transfer process have been studied. The statistical analysis shows that the sensitivity of each characteristic parameter with regard to the variation of the short circuiting transfer process is different. The sensitivity of 4 kinds among these characteristic parameters is more intense than that of the short circuiting transfer frequency. In order to take account of the synthetic influence of these characteristic parameters, by means of the characteristic parameters synthetic value, a quantitative evaluation function is built up to describe and evaluate the short circuiting transfer process of CO 2 arc welding in real time. The testing shows that the evaluation function can give a suitable synthetic valuation for the short circuiting transfer process with a variety of welding variables.

Plasma brain natriuretic peptide, platelet parameters, and cardiopulmonary function in chronic obstructive pulmonary disease

BACKGROUND Chronic obstructive pulmonary disease(COPD)is a chronic respiratory disease with worldwide occurrence and high disability and mortality rate.It occurs mostly in the elderly population with pulmonary heart disease,type II respiratory failure,and other serious complications.AIM To investigate the correlation of plasma brain natriuretic peptide(BNP)and platelet parameters with cardiac function and pulmonary hypertension in patients with COPD and pulmonary heart disease.METHODS From June 2016 to June 2019,52 patients with COPD-pulmonary heart disease(pulmonary heart disease group),30 patients with COPD(COPD group),and 30 healthy individuals(control group)in our hospital were enrolled in the study.The pulmonary heart disease group was further divided into subgroups according to cardiac function classification and pulmonary artery pressure.Plasma BNP and platelet parameters were estimated and compared among each group and subgroup.The correlation of plasma BNP and platelet parameters with cardiac function classification and pulmonary artery pressure was then analyzed.RESULTS In the pulmonary heart disease group,the COPD group,and the control group,the levels of plasma BNP,platelet distribution width(PDW),and mean platelet volume(MPV)showed a decreasing trend(P<0.05),while an increasing trend was found in platelet count(PLT)and plateletcrit(PCT)levels among the three groups(P<0.05).In the pulmonary hypertension mild,moderate,and severe subgroups,the levels of plasma BNP,PDW,and MPV showed an increasing trend(P<0.05),while a decreasing trend was observed in PLT levels(P<0.05);however,PCT levels showed no significant difference among the three subgroups(P>0.05).In the cardiac function grade I,II,III,and IV subgroups,the levels of plasma BNP,PDW,and MPV showed an increasing trend(P<0.05),while a decreasing trend was noted in PLT and PCT levels among the four subgroups(P<0.05).Correlation analysis showed that the levels of plasma BNP,PDW,and MPV in patients with pulmonary heart disease were positively correlated with their pulmonary artery pressure(P<0.05),while PLT was negatively correlated with their pulmonary artery pressure(P<0.05).Moreover,plasma BNP,PDW,and MPV levels were positively correlated with cardiac function grade(P<0.05)of these patients,while PLT and PCT levels were negatively correlated with their cardiac function grade(P<0.05).CONCLUSION Plasma BNP and PLT parameters are significantly correlated with the cardiac function and pulmonary hypertension in patients with COPD and pulmonary heart disease,indicating that these parameters have high clinical relevance in reflecting the health condition of these patients and for guiding their treatment.

Constructing Confidence Regions for Autoregressive-Model Parameters

We discuss formulas and techniques for finding maximum-likelihood estimators of parameters of autoregressive (with particular emphasis on Markov and Yule) models, computing their asymptotic variance-covariance matrix and displaying the resulting confidence regions;Monte Carlo simulation is then used to establish the accuracy of the corresponding level of confidence. The results indicate that a direct application of the Central Limit Theorem yields errors too large to be acceptable;instead, we recommend using a technique based directly on the natural logarithm of the likelihood function, verifying its substantially higher accuracy. Our study is then extended to the case of estimating only a subset of a model’s parameters, when the remaining ones (called nuisance) are of no interest to us.

Derivation the Schemes of Lateral and Vertical Dispersion Parameters: Application in Gaussian Plume Model

The main objective of this paper is to estimate the plume dispersion parameters in lateral direction (σy) and vertical direction (σz) by using power law wind speed and the scheme of eddy diffusivity in unstable condition. Comparison among our model and algebraic [1] and integral [2] formulations were held. We find that our model and two other models are in agreement with observed data.

MODAL PARAMETERS EXTRACTION WITH CROSS CORRELATION FUNCTION AND CROSS POWER SPECTRUM UNDER UNKNOWN EXCITATION

In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross-correlation functions and cross-power spectra between the outputs under the assumption of white-noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross-correlation functions in time domain and Orthogonal Polynomial method using cross-power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross-correlation functions or cross-power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.

Multi-output Gaussian Process Regression Model with Combined Kernel Function for Polyester Esterification Processes

In polyester fiber industrial processes,the prediction of key performance indicators is vital for product quality.The esterification process is an indispensable step in the polyester polymerization process.It has the characteristics of strong coupling,nonlinearity and complex mechanism.To solve these problems,we put forward a multi-output Gaussian process regression(MGPR)model based on the combined kernel function for the polyester esterification process.Since the seasonal and trend decomposition using loess(STL)can extract the periodic and trend characteristics of time series,a combined kernel function based on the STL and the kernel function analysis is constructed for the MGPR.The effectiveness of the proposed model is verified by the actual polyester esterification process data collected from fiber production.

Rheological Behaviour for Polymer Melts and Concentrated SolutionsPart Ⅱ: Material Function with Nagai Chain Constraints and Determination of Their Parameters from Flow Curves

An integral constitutive equation and a set of material functions for describing the strain history of polymer melts were formulated in terms of the Cauchy-Green and Finger tensors. A simple memory function and the dependence of ηo and τt on M3.4 were derived from the theory of non-linear viscoelasticity with constraints of entanglements for polymer melts and substituted into the Oldroye-Walters-Fredickson constitutive equation. An integral constitutive equation for polymer melts was consequently obtained. Some material functions of the constitutive equation related to certain 'test flow' are examined as follows : (1) simple steady shear flow; (2) steady elongation flow; (3) small-amplitude oscillatory shear flow; (4) stress growth upon the inception of steady shear elongation flow; (5) stress relaxation (modulus and compllance). These theoretical relations for simple steady shear flow were compared with experimental data from our laboratory and references for various polymer melts and concentrated solutions. A good agreement between the theory and experiment was achieved.

Measurement of Optical Fiber Geometry Parameters with Bessel Function Fitting Method

Geometry parameters of optical fiber are crucial in evaluating the quality of the optical fiber.Near⁃field light distribution method is recommended in GB15972.20-2008 for the measurement of geometry parameters.To distinguish the boundary between fiber core and cladding,it is necessary to illuminate the fiber.The end face of the core is a bright spot with unclear edge,so the true edge of the core and the cladding cannot be accurately judged.A method is proposed in this paper to measure the geometry parameters of optical fiber by Bessel function fitting.Theoretically,the solution to the electromagnetic vector of mode field satisfies Bessel function,and the boundary between the core and the cladding can be precisely extracted by Bessel function fitting.Edges of the fiber were fitted by elliptical curves,and the geometry parameters of the fibers could be calculated.Results show that the maximum deviations of the diameters and the average differences of the fibers were decreased under normal and abnormal conditions respectively.The proposed method is an efficient way to obtain edge data and can improve the accuracy and stability of geometry parameters of optical fibers.