Improvement of photogrammetric joint roughness coefficient value by integrating automatic shooting parameter selection and composite error model

In order to improve the accuracy of the photogrammetric joint roughness coefficient(JRC)value,the present study proposed a novel method combining an autonomous shooting parameter selection algorithm with a composite error model.Firstly,according to the depth map-based photogrammetric theory,the estimation of JRC from a three-dimensional(3D)digital surface model of rock discontinuities was presented.Secondly,an automatic shooting parameter selection algorithm was novelly proposed to establish the 3D model dataset of rock discontinuities with varying shooting parameters and target sizes.Meanwhile,the photogrammetric tests were performed with custom-built equipment capable of adjusting baseline lengths,and a total of 36 sets of JRC data was gathered via a combination of laboratory and field tests.Then,by combining the theory of point cloud coordinate computation error with the equation of JRC calculation,a composite error model controlled by the shooting parameters was proposed.This newly proposed model was validated via the 3D model dataset,demonstrating the capability to correct initially obtained JRC values solely based on shooting parameters.Furthermore,the implementation of this correction can significantly reduce errors in JRC values obtained via photographic measurement.Subsequently,our proposed error model was integrated into the shooting parameter selection algorithm,thus improving the rationality and convenience of selecting suitable shooting parameter combinations when dealing with target rock masses with different sizes.Moreover,the optimal combination of three shooting parameters was offered.JRC values resulting from various combinations of shooting parameters were verified by comparing them with 3D laser scan data.Finally,the application scope and limitations of the newly proposed approach were further addressed.

Role of disturbance coefficient in monitoring and treatment of cerebral edema in patients with cerebral hemorrhage

BACKGROUND At present,the conventional methods for diagnosing cerebral edema in clinical practice are computed tomography(CT)and magnetic resonance imaging(MRI),which can evaluate the location and degree of peripheral cerebral edema,but cannot realize quantification.When patients have symptoms of diffuse cerebral edema or high cranial pressure,CT or MRI often suggests that cerebral edema is lagging and cannot be dynamically monitored in real time.Intracranial pressure monitoring is the gold standard,but it is an invasive operation with high cost and complications.For clinical purposes,the ideal cerebral edema monitoring should be non-invasive,real-time,bedside,and continuous dynamic monitoring.The dis-turbance coefficient(DC)was used in this study to dynamically monitor the occu-rrence,development,and evolution of cerebral edema in patients with cerebral hemorrhage in real time,and review head CT or MRI to evaluate the development of the disease and guide further treatment,so as to improve the prognosis of patients with cerebral hemorrhage.AIM To offer a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.METHODS A total of 160 patients with hypertensive cerebral hemorrhage admitted to the Department of Neurosurgery,Second Affiliated Hospital of Xi’an Medical University from September 2018 to September 2019 were recruited.The patients were randomly divided into a control group(n=80)and an experimental group(n=80).Patients in the control group received conventional empirical treatment,while those in the experimental group were treated with mannitol dehydration under the guidance of DC.Subsequently,we compared the two groups with regards to the total dosage of mannitol,the total course of treatment,the incidence of complications,and prognosis.RESULTS The mean daily consumption of mannitol,the total course of treatment,and the mean hospitalization days were 362.7±117.7 mL,14.8±5.2 days,and 29.4±7.9 in the control group and 283.1±93.6 mL,11.8±4.2 days,and 23.9±8.3 in the experimental group(P<0.05).In the control group,there were 20 patients with pulmonary infection(25%),30 with electrolyte disturbance(37.5%),20 with renal impairment(25%),and 16 with stress ulcer(20%).In the experimental group,pulmonary infection occurred in 18 patients(22.5%),electrolyte disturbance in 6(7.5%),renal impairment in 2(2.5%),and stress ulcers in 15(18.8%)(P<0.05).According to the Glasgow coma scale score 6 months after discharge,the prognosis of the control group was good in 20 patients(25%),fair in 26(32.5%),and poor in 34(42.5%);the prognosis of the experimental group was good in 32(40%),fair in 36(45%),and poor in 12(15%)(P<0.05).CONCLUSION Using DC for non-invasive dynamic monitoring of cerebral edema demonstrates considerable clinical potential.It reduces mannitol dosage,treatment duration,complication rates,and hospital stays,ultimately lowering hospital-ization costs.Additionally,it improves overall patient prognosis,offering a promising new approach for non-invasive adjuvant therapy in cerebral edema treatment.

Role of variation coefficient of stone density in determining success of shock wave lithotripsy in urinary calculi

BACKGROUND Various stone factors can affect the net results of shock wave lithotripsy(SWL).Recently a new factor called variation coefficient of stone density(VCSD)is being considered to have an impact on stone free rates.AIM To assess the role of VCSD in determining success of SWL in urinary calculi.METHODS Charts review was utilized for collection of data variables.The patients were subjected to SWL,using an electromagnetic lithotripter.Mean stone density(MSD),stone heterogeneity index(SHI),and VCSD were calculated by generating regions of interest on computed tomography(CT)images.Role of these factors were determined by applying the relevant statistical tests for continuous and categorical variables and a P value of<0.05 was gauged to be statistically significant.RESULTS There were a total of 407 patients included in the analysis.The mean age of the subjects in this study was 38.89±14.61 years.In total,165 out of the 407 patients could not achieve stone free status.The successful group had a significantly lower stone volume as compared to the unsuccessful group(P<0.0001).Skin to stone distance was not dissimilar among the two groups(P=0.47).MSD was significantly lower in the successful group(P<0.0001).SHI and VCSD were both significantly higher in the successful group(P<0.0001).CONCLUSION VCSD,a useful CT based parameter,can be utilized to gauge stone fragility and hence the prediction of SWL outcomes.

Coefficient Estimates for a Subclass of Bi-univalent Strongly Quasi-starlike Functions

The aim of this paper is to establish the Fekete-Szego inequality for a subclass of bi-univalent strongly quasi-starlike functions which is defined in the open unit disk. Furthermore, the coefficients a2 and a3 for functions in this new subclass are estimated.

Coefficient Estimates for a Class of m-fold Symmetric Bi-univalent Function Defined by Subordination

In this paper, we investigate the coefficient estimates of a class of m-fold bi-univalent function de?ned by subordination. The results presented in this paper improve or generalize the recent works of other authors.

UNIFORM HLDER ESTIMATES FOR A TYPE OF NONLINEAR ELLIPTIC EQUATIONS WITH RAPIDLY OSCILLATORY COEFFICIENTS

In this paper, a type of nonlinear elliptic equations with rapidly oscillatory co- efficients is investigated. By compactness methods, we show uniform HSlder estimates of solutions in a C1 bounded domain.

ESTIMATE FOR DISTANCE-COEFFICIENT OF MATRICES

Motivation of this paper is an open problem exposed by B. Beauzamy .Let M be a 3×3 matrix and d(M) is the distance to the diagonal algebra. Let α(M)= sup {‖P ⊥MP‖∶P is a projection in the diagonal algebra} and then call K(M)=d(Μ)α(M) the distance coefficient of M. The following results are obtained: (1) If M has two zero entries apart from its diagonal, then K(M)322; (2) If M has one zero entry apart from its diagonal, then K(M)4132; (3) If M is arbitrary, then K(M)32.

Influence of water coupling coefficient on the blasting effect of red sandstone specimens

This study investigates the impact of different water coupling coefficients on the blasting effect of red sandstone.The analysis is based on the theories of detonation wave and elastic wave,focusing on the variation in wall pressure of the blasting holes.Using DDNP explosive as the explosive load,blasting tests were conducted on red sandstone specimens with four different water coupling coefficients:1.20,1.33,1.50,and 2.00.The study examines the morphologies of the rock specimens after blasting under these different water coupling coefficients.Additionally,the fractal dimensions of the surface cracks resulting from the blasting were calculated to provide a quantitative evaluation of the extent of rock damage.CT scanning and 3D reconstruction were performed on the post-blasting specimens to visually depict the extent of damage and fractures within the rock.Additionally,the volume fractal dimension and damage degree of the post-blasting specimens are calculated.The findings are then combined with numerical simulation to facilitate auxiliary analysis.The results demonstrate that an increase in the water coupling coefficient leads to a reduction in the peak pressure on the hole wall and the crushing zone,enabling more of the explosion energy to be utilized for crack propagation following the explosion.The specimens exhibited distinct failure patterns,resulting in corresponding changes in fractal dimensions.The simulated pore wall pressure–time curve validated the derived theoretical results,whereas the stress cloud map and explosion energy-time curve demonstrated the buffering effect of the water medium.As the water coupling coefficient increases,the buffering effect of the water medium becomes increasingly prominent.

Estimate Beta Coefficient of CAPM Based on a Fuzzy Regression with Interactive Coefficients

In the Capital Asset Pricing Model (CAPM), beta coefficient is a very important parameter to be estimated. The most commonly used estimating methods are the Ordinary Least Squares (OLS) and some Robust Regression Techniques (RRT). However, these traditional methods make strong as sumptions which are unrealistic. In addition, The OLS method is very sensitive to extreme observations, while the RRT methods try to decrease the weights of the extreme observations which may contain substantial information. In this paper, a novel fuzzy regression method is proposed, which makes less assumptions and takes good care of the extreme observations. Simulation study and real word applications show that the fuzzy regression is a competitive method.

THE COMPRESSION LS ESTIMATE OF REGRESSION COEFFICIENT IN MULTIVARIATE LINEAR MODEL

In this paper, compression LS estimate (k) of the regression coefficient B isconsidered when the design matrix present ill-condition in multivariate linear model.The MSE (mean square error)of the estimate(k)=Vec( (k))is less than theMSE of LS estimate β￣* of the regression coefficient β= Vec(B) by choosing the pa-rameter k. Admissibility , numerical stability and relative efficiency of (k)are proved. The method of determining k value for practical use is also suggested

Theorem of Logarithm Expectation and Its Application to Prove Sample Correlation Coefficient as Unbiased Estimate

In statistical theory, a statistic that is function of sample observations is used to estimate distribution parameter. This statistic is called unbiased estimate if its expectation is equal to theoretical parameter. Proving whether or not a statistic is unbiased estimate is very important but this proof may require a lot of efforts when statistic is complicated function. Therefore, this research facilitates this proof by proposing a theorem which states that the expectation of variable x 〉 0 is u if and only if the limit of logarithm expectation of x approaches logarithm of u. In order to make clear of this theorem, the research gives an example of proving correlation coefficient as unbiased estimate by taking advantages of this theorem.

ESTIMATE ACCURACY OF NONLINEAR COEFFICIENTS OF SQUEEZEFILM DAMPER USING STATE VARIABLE FILTER METHOD

The estimate model for a nonlinear system of squeeze film damper (SFD) is described.The method of state variable filter (SVF) is used to estimate the coefficients of SFD.The factors which are critical to the estimate accuracy are discussed

Machine learning-based comparison of factors influencing estimated glomerular filtration rate in Chinese women with or without nonalcoholic fatty liver

BACKGROUND The prevalence of non-alcoholic fatty liver(NAFLD)has increased recently.Subjects with NAFLD are known to have higher chance for renal function impairment.Many past studies used traditional multiple linear regression(MLR)to identify risk factors for decreased estimated glomerular filtration rate(eGFR).However,medical research is increasingly relying on emerging machine learning(Mach-L)methods.The present study enrolled healthy women to identify factors affecting eGFR in subjects with and without NAFLD(NAFLD+,NAFLD-)and to rank their importance.AIM To uses three different Mach-L methods to identify key impact factors for eGFR in healthy women with and without NAFLD.METHODS A total of 65535 healthy female study participants were enrolled from the Taiwan MJ cohort,accounting for 32 independent variables including demographic,biochemistry and lifestyle parameters(independent variables),while eGFR was used as the dependent variable.Aside from MLR,three Mach-L methods were applied,including stochastic gradient boosting,eXtreme gradient boosting and elastic net.Errors of estimation were used to define method accuracy,where smaller degree of error indicated better model performance.RESULTS Income,albumin,eGFR,High density lipoprotein-Cholesterol,phosphorus,forced expiratory volume in one second(FEV1),and sleep time were all lower in the NAFLD+group,while other factors were all significantly higher except for smoking area.Mach-L had lower estimation errors,thus outperforming MLR.In Model 1,age,uric acid(UA),FEV1,plasma calcium level(Ca),plasma albumin level(Alb)and T-bilirubin were the most important factors in the NAFLD+group,as opposed to age,UA,FEV1,Alb,lactic dehydrogenase(LDH)and Ca for the NAFLD-group.Given the importance percentage was much higher than the 2nd important factor,we built Model 2 by removing age.CONCLUSION The eGFR were lower in the NAFLD+group compared to the NAFLD-group,with age being was the most important impact factor in both groups of healthy Chinese women,followed by LDH,UA,FEV1 and Alb.However,for the NAFLD-group,TSH and SBP were the 5th and 6th most important factors,as opposed to Ca and BF in the NAFLD+group.

An Indirect Finite Element Method for Variable-Coefficient Space-Fractional Diffusion Equations and Its Optimal-Order Error Estimates

We study an indirect finite element approximation for two-sided space-fractional diffusion equations in one space dimension.By the representation formula of the solutions u(x)to the proposed variable coefficient models in terms of v(x),the solutions to the constant coefficient analogues,we apply finite element methods for the constant coefficient fractional diffusion equations to solve for the approximations vh(x)to v(x)and then obtain the approximations uh(x)of u(x)by plugging vh(x)into the representation of u(x).Optimal-order convergence estimates of u(x)−uh(x)are proved in both L2 and Hα∕2 norms.Several numerical experiments are presented to demonstrate the sharpness of the derived error estimates.

Using Extreme Value Theory Approaches to Estimate High Quantiles for Stroke Data

This paper aims to explore the application of Extreme Value Theory (EVT) in estimating the conditional extreme quantile for time-to-event outcomes by examining the functional relationship between ambulatory blood pressure trajectories and clinical outcomes in stroke patients. The study utilizes EVT to analyze the functional connection between ambulatory blood pressure trajectories and clinical outcomes in a sample of 297 stroke patients. The 24-hour ambulatory blood pressure measurement curves for every 15 minutes are considered, acknowledging a censored rate of 40%. The findings reveal that the sample mean excess function exhibits a positive gradient above a specific threshold, confirming the heavy-tailed distribution of data in stroke patients with a positive extreme value index. Consequently, the estimated conditional extreme quantile indicates that stroke patients with higher blood pressure measurements face an elevated risk of recurrent stroke occurrence at an early stage. This research contributes to the understanding of the relationship between ambulatory blood pressure and recurrent stroke, providing valuable insights for clinical considerations and potential interventions in stroke management.

Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates

This paper investigates the problem of collecting multidimensional data throughout time(i.e.,longitudinal studies)for the fundamental task of frequency estimation under Local Differential Privacy(LDP)guarantees.Contrary to frequency estimation of a single attribute,the multidimensional aspect demands particular attention to the privacy budget.Besides,when collecting user statistics longitudinally,privacy progressively degrades.Indeed,the“multiple”settings in combination(i.e.,many attributes and several collections throughout time)impose several challenges,for which this paper proposes the first solution for frequency estimates under LDP.To tackle these issues,we extend the analysis of three state-of-the-art LDP protocols(Generalized Randomized Response–GRR,Optimized Unary Encoding–OUE,and Symmetric Unary Encoding–SUE)for both longitudinal and multidimensional data collections.While the known literature uses OUE and SUE for two rounds of sanitization(a.k.a.memoization),i.e.,L-OUE and L-SUE,respectively,we analytically and experimentally show that starting with OUE and then with SUE provides higher data utility(i.e.,L-OSUE).Also,for attributes with small domain sizes,we propose Longitudinal GRR(L-GRR),which provides higher utility than the other protocols based on unary encoding.Last,we also propose a new solution named Adaptive LDP for LOngitudinal and Multidimensional FREquency Estimates(ALLOMFREE),which randomly samples a single attribute to be sent with the whole privacy budget and adaptively selects the optimal protocol,i.e.,either L-GRR or L-OSUE.As shown in the results,ALLOMFREE consistently and considerably outperforms the state-of-the-art L-SUE and L-OUE protocols in the quality of the frequency estimates.

Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

A Formulation of the Porous Medium Equation with Time-Dependent Porosity: A Priori Estimates and Regularity Results

We consider a generalized form of the porous medium equation where the porosity ϕis a function of time t: ϕ=ϕ(x,t): ∂(ϕS)∂t−∇⋅(k(S)∇S)=Q(S).In many works, the porosity ϕis either assumed to be independent of (or to depend very little of) the time variable t. In this work, we want to study the case where it does depend on t(and xas well). For this purpose, we make a change of unknown function V=ϕSin order to obtain a saturation-like (advection-diffusion) equation. A priori estimates and regularity results are established for the new equation based in part on what is known from the saturation equation, when ϕis independent of the time t. These results are then extended to the full saturation equation with time-dependent porosity ϕ=ϕ(x,t). In this analysis, we make explicitly the dependence of the various constants in the estimates on the porosity ϕby the introduced transport vector w, through the change of unknown function. Also we do not assume zero-flux boundary, but we carry the analysis for the case Q≡0.

Prediction of Coefficient of Restitution for Impact Elastoplastic Spheres Considering Finite Plate Thickness

Collisions between objects are a relatively common phenomenon in nature.Analyses of collision processes can greatly contribute to solving problems such as impact-rub faults and particle impacts.The coefficient of restitution is a critical parameter in the analysis of collision processes.Many experiments have shown that the coefficient of restitution is closely related to the plate thickness,and the smaller the plate thickness,the more inaccurate the coefficient of restitution predicted by the existing model,which seriously affects the process of collision analysis.To remedy this shortcoming,this paper proposes a plate thickness influence factor with the ratio of sphere diameter to plate thickness as the variable.The plate thickness influence factor can optimize the coefficient of restitution model to effectively predict the coefficient of restitution of impacting elastoplastic spheres with finite plate thickness.Finally,the validity of the new model is verified using a large amount of experimental data.

ELLIPTIC EQUATIONS IN DIVERGENCE FORM WITH DISCONTINUOUS COEFFICIENTS IN DOMAINS WITH CORNERS

We study equations in divergence form with piecewise Cαcoefficients.The domains contain corners and the discontinuity surfaces are attached to the edges of the corners.We obtain piecewise C^(1,α) estimates across the discontinuity surfaces and provide an example to illustrate the issue regarding the regularity at the corners.