Prevalence of visual impairment and estimation of refractive errors among school children in Kakamega,Kenya

AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Uncertainties in landslide susceptibility prediction:Influence rule of different levels of errors in landslide spatial position

The accuracy of landslide susceptibility prediction(LSP)mainly depends on the precision of the landslide spatial position.However,the spatial position error of landslide survey is inevitable,resulting in considerable uncertainties in LSP modeling.To overcome this drawback,this study explores the influence of positional errors of landslide spatial position on LSP uncertainties,and then innovatively proposes a semi-supervised machine learning model to reduce the landslide spatial position error.This paper collected 16 environmental factors and 337 landslides with accurate spatial positions taking Shangyou County of China as an example.The 30e110 m error-based multilayer perceptron(MLP)and random forest(RF)models for LSP are established by randomly offsetting the original landslide by 30,50,70,90 and 110 m.The LSP uncertainties are analyzed by the LSP accuracy and distribution characteristics.Finally,a semi-supervised model is proposed to relieve the LSP uncertainties.Results show that:(1)The LSP accuracies of error-based RF/MLP models decrease with the increase of landslide position errors,and are lower than those of original data-based models;(2)70 m error-based models can still reflect the overall distribution characteristics of landslide susceptibility indices,thus original landslides with certain position errors are acceptable for LSP;(3)Semi-supervised machine learning model can efficiently reduce the landslide position errors and thus improve the LSP accuracies.

Prevalence of refractive errors in school-aged and preadolescent children in Colombia

AIM:To describe the distribution of refractive errors by age and sex among schoolchildren in Soacha,Colombia.METHODS:This was an observational cross-sectional study conducted in five urban public schools in the municipality of Soacha.A total of 1161 school-aged and pre-adolescent children,aged 5-12y were examined during the school year 2021-2022.Examinations included visual acuity and static refraction.Spherical equivalent(SE)was analysed as follows:myopia SE≤-0.50 D and uncorrected visual acuity of 20/25 or worse;high myopia SE≤-6.00 D;hyperopia SE≥+1.00 D(≥7y)or SE≥+2.00 D(5-6y);significant hyperopia SE≥+3.00 D.Astigmatism was defined as a cylinder in at least one eye≥1.00 D(≥7y)or≥1.75 D(5-6y).If at least one eye was ametropic,children were classified according to the refractive error found.RESULTS:Of the 1139 schoolchildren included,50.6%were male,58.8%were aged between 5 and 9y,and 12.1%were already using optical correction.The most common refractive error was astigmatism(31.1%),followed by myopia(20.8%)and hyperopia(13.1%).There was no significant relationship between refractive error and sex.There was a significant increase in astigmatism(P<0.001)and myopia(P<0.0001)with age.CONCLUSION:Astigmatism is the most common refractive error in children in an urban area of Colombia.Emmetropia decreased and myopia increased with age.

Prevalence of Refractive Errors among School Children Aged 5 to 15 Years Old at CHU-IOTA

Introduction: Undetected refractive errors constitute a health problem among school children who cannot take advantage of educational opportunities. The authors studied the prevalence of refractive errors in school children aged 5 to 15 at CHU-IOTA. Patients and Method: This is a prospective, descriptive cross-sectional study carried out in the ophthalmic-pediatrics department of CHU-IOTA, from October to November 2023. Results: We received 340 school children aged 5 to 15, among whom 111 presented ametropia, i.e. a prevalence of 32.65%. The average age was 11.42 ± 2.75 years and a sex ratio of 0.59. The average visual acuity was 4/10 (range 1/10 and 10/10). We found refractive defects: astigmatism 73.87%, hyperopia 23.87% of cases and myopia 2.25%. The decline in distance visual acuity was the most common functional sign. Ocular abnormalities associated with ametropia were dominated by allergic conjunctivitis (26.13%) and papillary excavation (6.31%) in astigmatics;allergic conjunctivitis (9.01%) and papillary excavation (7.20%) in hyperopic patients;turbid vitreous (0.90%), myopic choroidosis (0.45%) and allergic conjunctivitis (0.45%) in myopes. Conclusion: Refractive errors constitute a reality and a major public health problem among school children.

An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

Relationships between Terrain Features and Forecasting Errors of Surface Wind Speeds in a Mesoscale Numerical Weather Prediction Model

Numerical weather prediction(NWP)models have always presented large forecasting errors of surface wind speeds over regions with complex terrain.In this study,surface wind forecasts from an operational NWP model,the SMS-WARR(Shanghai Meteorological Service-WRF ADAS Rapid Refresh System),are analyzed to quantitatively reveal the relationships between the forecasted surface wind speed errors and terrain features,with the intent of providing clues to better apply the NWP model to complex terrain regions.The terrain features are described by three parameters:the standard deviation of the model grid-scale orography,terrain height error of the model,and slope angle.The results show that the forecast bias has a unimodal distribution with a change in the standard deviation of orography.The minimum ME(the mean value of bias)is 1.2 m s^(-1) when the standard deviation is between 60 and 70 m.A positive correlation exists between bias and terrain height error,with the ME increasing by 10%−30%for every 200 m increase in terrain height error.The ME decreases by 65.6%when slope angle increases from(0.5°−1.5°)to larger than 3.5°for uphill winds but increases by 35.4%when the absolute value of slope angle increases from(0.5°−1.5°)to(2.5°−3.5°)for downhill winds.Several sensitivity experiments are carried out with a model output statistical(MOS)calibration model for surface wind speeds and ME(RMSE)has been reduced by 90%(30%)by introducing terrain parameters,demonstrating the value of this study.

Prevalence and Factors Associated with Refractive Errors among University Students at Mbarara University of Science and Technology, Uganda

Introduction: WHO estimated that uncorrected refractive errors are the leading cause of visual impairment and second leading cause of blindness globally. University students are prone to developing refractive errors due to their curriculum that requires a lot of near work affecting their performance and quality of life unknowingly. Genetic and environmental factors are thought to play a role in the development of refractive errors. This study addresses the paucity of knowledge about refractive errors among university students in East Africa, providing a foundation for further research. Objectives: To determine the prevalence and factors associated with refractive errors among students in the Faculty of Medicine at Mbarara University of Science and Technology. Methodology: This was a cross-sectional descriptive and analytical study in which 368 undergraduate students selected using random sampling were assessed for refractive errors from March 2021-July 2021. Eligible participants were recruited and their VA assessment done after answering a questionnaire. Students whose VA improved on pin hole had subjective retinoscopy and results were compiled and imported to STATA 14 for analysis. Results: The prevalence of refractive errors was 26.36% with (95% CI) among university students especially myopia. Myopia is most predominant at 60%, followed by 37% Astigmatism and hyperopia of 3% among medical students. Astigmatism consisted of largely myopic astigmatism 72% (26) and 28% (10) compound/mixed astigmatism only. Student positive family history of refractive error was found to have a statistically significant relationship with refractive errors with AOR 1.68 (1.04 - 2.72) (95% CI) and P (0.032). Conclusion: The prevalence of refractive errors among university students, especially myopia, was found to be high and family history was associated with students having refractive errors.

Relative peripheral refractive errors in Chinese children with myopic anisometropia

AIM:To compare relative peripheral refractive errors(RPREs)in Chinese children with and without myopic anisometropia(MAI)and to explore the relationship between RPRE and myopia.METHODS:This observational cross-sectional study included 160 children divided into two groups according to the interocular spherical equivalent refraction(SER)difference≥1.0 D in the MAI group(n=80)and<1.0 D in the non-MAI group(n=80).The MAI group was further divided into two subgroups:ΔSER<2.0 D group and ΔSER≥2.0 D group.Basic ocular biometric parameters of axial length(AL),average keratometry(Ave K),cylinder(CYL),surface regularity index(SRI),and surface asymmetry index(SAI)were recorded.In addition,multispectral refraction topography was performed to measure RPRE,and the parameters were recorded as total refraction difference value(TRDV),refraction difference value(RDV)0-10,RDV10-20,RDV20-30,RDV30-40,RDV40-53,RDV-superior(RDV-S),RDV-inferior(RDV-I),RDV-temporal(RDV-T)and RDV-nasal(RDV-N).RESULTS:In the non-MAI group,the interocular differences of all parameters of RPRE were not significant.In the MAI group,the interocular differences of TRDV,RDV10-53,RDV-S,RDV-I,RDV-T,and RDV-N were significant.In subgroup analysis,the interocular differences of TRDV,RDV30-53,RDV-I,and RDV-T were significant in ΔSER<2.0 D group and ΔSER≥2.0 D group,but the interocular differences of RDV10-30,RDV-S and RDV-N were only significant in the ΔSER≥2.0 D group.In correlation analysis,ΔTRDV,ΔRDV 10-53,ΔRDV-S,and ΔRDV-N were negatively correlated with ΔSER but positively correlated with ΔAL.CONCLUSION:The more myopic eyes have larger hyperopic RPRE in Chinese children with MAI in certain retinal range,and partialΔRPRE is closely associated with ΔSER and ΔAL.

Numerical Investigations on the Resonance Errors of Multiscale Discontinuous Galerkin Methods for One-Dimensional Stationary Schrödinger Equation

In this paper,numerical experiments are carried out to investigate the impact of penalty parameters in the numerical traces on the resonance errors of high-order multiscale discontinuous Galerkin(DG)methods(Dong et al.in J Sci Comput 66:321–345,2016;Dong and Wang in J Comput Appl Math 380:1–11,2020)for a one-dimensional stationary Schrödinger equation.Previous work showed that penalty parameters were required to be positive in error analysis,but the methods with zero penalty parameters worked fine in numerical simulations on coarse meshes.In this work,by performing extensive numerical experiments,we discover that zero penalty parameters lead to resonance errors in the multiscale DG methods,and taking positive penalty parameters can effectively reduce resonance errors and make the matrix in the global linear system have better condition numbers.

Prevalence of refractive errors in children of Puerto Rico

AIM:To determine the prevalence of refractive error in 5-to 17-year-old schoolchildren in Puerto Rico.METHODS:A quantitative descriptive study of 2867 children aged 5 to 17y from all seven educational regions of Puerto Rico was conducted from 2016–2019.Refractive error was determined via static and subjective refraction.Children with distance acuity≤20/40 or near visual acuity≤20/32 had a cycloplegic refraction.Data analysis included descriptive statistics,correlation coefficient,Kruskal-Wallis,Chi-square,and t test calculations.RESULTS:Twenty percent of the children had a spherical equivalent refractive error≤-0.50 D,3.2%had a spherical equivalent≥+2.00 D,and 10.4%had astigmatism≥1 D.There was a statistically(but non-clinically)significant myopic change in spherical equivalent refractive error with age(P<0.001).The prevalence of myopia increased with age(P<0.001)but not hyperopia(P=0.59)or astigmatism(P=0.51).Males had a significantly higher hyperopic spherical equivalent than females(P<0.001).Females had a higher prevalence of myopia(P<0.001)than males,but there was no difference in the hyperopia(P=0.74)or astigmatism prevalence(P=0.87).CONCLUSION:The prevalence of a spherical equivalent equal to or less than-0.50 D(myopia,20.7%)is one of the highest among similar-aged children worldwide.Further studies should explore the rate of myopia progression in children in Puerto Rico.Individual children must be monitored to examine the need for treatment of myopia progression.

Uncorrected refractive errors are important causes of avoidable visual impairment in Hungary: re-evaluation of two existing national data sets

·AIM: To review existing data for the prevalence of corrected, uncorrected, and inadequately corrected refractive errors and spectacle wear in Hungary.·METHODS: Data from two nationwide cross-sectional studies were analysed. The Rapid Assessment of Avoidable Blindness study collected population-based representative national data on the prevalence of visual impairment due to uncorrected refractive errors and spectacle coverage in 3523 people aged ≥50y(Group I). The Comprehensive Health Test Program of Hungary provided data on the use of spectacles in 80 290 people aged ≥18y(Group Ⅱ).·RESULTS: In Group I, almost half of the survey population showed refractive errors for distant vision, about 10% of which were uncorrected(3.2% of all male participants and 5.0% of females). The distance spectacle coverage was 90.7%(91.9% in males;90.2% in females). The proportion of inadequate distance spectacles was found to be 33.1%. Uncorrected presbyopia was found in 15.7% of participants. In all age groups(Group Ⅱ), 65.4% of females and 56.0% of males used distance spectacles,and approximately 28.9% of these spectacles were found to be inappropriate for dioptric power(with 0.5 dioptres or more). The prevalence of inaccurate distance spectacles was significantly higher in older age groups(71y and above) in both sexes.·CONCLUSION: According to this population-based data, uncorrected refractive errors are not rare in Hungary. Despite recent national initiatives, fur ther steps are required to reduce uncorrected refractive errors and associated negative effects on vision, such as avoidable visual impairment.

Positional Error Model of Line Segments with Modeling and Measuring Errors Using Brownian Bridge

Spatial linear features are often represented as a series of line segments joined by measured endpoints in surveying and geographic information science.There are not only the measuring errors of the endpoints but also the modeling errors between the line segments and the actual geographical features.This paper presents a Brownian bridge error model for line segments combining both the modeling and measuring errors.First,the Brownian bridge is used to establish the position distribution of the actual geographic feature represented by the line segment.Second,an error propagation model with the constraints of the measuring error distribution of the endpoints is proposed.Third,a comprehensive error band of the line segment is constructed,wherein both the modeling and measuring errors are contained.The proposed error model can be used to evaluate line segments’overall accuracy and trustability influenced by modeling and measuring errors,and provides a comprehensive quality indicator for the geospatial data.

STAP method based on atomic norm minimization with array amplitude-phase error calibration

In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.

Liver immunity,autoimmunity,and inborn errors of immunity

The liver is the front line organ of the immune system.The liver contains the largest collection of phagocytic cells in the body that detect both pathogens that enter through the gut and endogenously produced antigens.This is possible by the highly developed differentiation capacity of the liver immune system between self-antigens or non-self-antigens,such as food antigens or pathogens.As an immune active organ,the liver functions as a gatekeeping barrier from the outside world,and it can create a rapid and strong immune response,under unfavorable conditions.However,the liver's assumed immune status is anti-inflammatory or immuno-tolerant.Dynamic interactions between the numerous populations of immune cells in the liver are key for maintaining the delicate balance between immune screening and immune tolerance.The anatomical structure of the liver can facilitate the preparation of lymphocytes,modulate the immune response against hepatotropic pathogens,and contribute to some of its unique immunological properties,particularly its capacity to induce antigen-specific tolerance.Since liver sinusoidal endothelial cell is fenestrated and lacks a basement membrane,circulating lymphocytes can closely contact with antigens,displayed by endothelial cells,Kupffer cells,and dendritic cells while passing through the sinusoids.Loss of immune tolerance,leading to an autoaggressive immune response in the liver,if not controlled,can lead to the induction of autoimmune or autoinflammatory diseases.This review mentions the unique features of liver immunity,and dysregulated immune responses in patients with autoimmune liver diseases who have a close association with inborn errors of immunity have also been the emphases.

Robust Beamforming Under Channel Prediction Errors for Time-Varying MIMO System

The accuracy of acquired channel state information(CSI)for beamforming design is essential for achievable performance in multiple-input multiple-output(MIMO)systems.However,in a high-speed moving scene with time-division duplex(TDD)mode,the acquired CSI depending on the channel reciprocity is inevitably outdated,leading to outdated beamforming design and then performance degradation.In this paper,a robust beamforming design under channel prediction errors is proposed for a time-varying MIMO system to combat the degradation further,based on the channel prediction technique.Specifically,the statistical characteristics of historical channel prediction errors are exploited and modeled.Moreover,to deal with random error terms,deterministic equivalents are adopted to further explore potential beamforming gain through the statistical information and ultimately derive the robust design aiming at maximizing weighted sum-rate performance.Simulation results show that the proposed beamforming design can maintain outperformance during the downlink transmission time even when channels vary fast,compared with the traditional beamforming design.

Quantum Codes Do Not Increase Fidelity against Isotropic Errors

In this article, we study the ability of error-correcting quantum codes to increase the fidelity of quantum states throughout a quantum computation. We analyze arbitrary quantum codes that encode all qubits involved in the computation, and we study the evolution of n-qubit fidelity from the end of one application of the correcting circuit to the end of the next application. We assume that the correcting circuit does not introduce new errors, that it does not increase the execution time (i.e. its application takes zero seconds) and that quantum errors are isotropic. We show that the quantum code increases the fidelity of the states perturbed by quantum errors but that this improvement is not enough to justify the use of quantum codes. Namely, we prove that, taking into account that the time interval between the application of the two corrections is multiplied (at least) by the number of qubits n (due to the coding), the best option is not to use quantum codes, since the fidelity of the uncoded state over a time interval n times smaller is greater than that of the state resulting from the quantum code correction.

Knowledge,attitude,and practices related to medication errors among nursing professionals:a questionnaire-based study in a tertiary care hospital

Objective:To evaluate the level of understanding(knowledge),beliefs(attitude),and behavior(practice)of staff nurses toward medication errors(MEs).Methods:Self-administered questionnaires were distributed to nursing professionals who had at least 1 year of work experience.Each questionnaire contained 19 items assessing“knowledge,”“attitude,”and“practice”attributes toward MEs.Results:Responses from 47 nursing respondents were included for the final analysis.The mean knowledge score was 3.8±1.1(out of 6);66%and 79%of the respondents had awareness of medication repor ting systems and interventions in preventing MEs,respectively.Lack of adequate knowledge in recognizing MEs(P=0.003),or presuming MEs are not as important enough to be reported(P=0.002),was considered as the major reason for under-repor ting of MEs.Nurses with higher knowledge score were against administration of medication through a different route than that prescribed by the physician(P=0.023),and tried to rectify an ME(P=0.020)and stayed with the patient until an oral medication had been swallowed(P=0.037).Conclusions:The nursing professionals were aware of the ME repor ting system and methods to prevent the occurrence of MEs.They also exhibited a positive attitude and followed optimal practices in controlling MEs.

Characterizing prediction errors of a new tree height model for cut-to-length Pinus radiata stems through the Burr TypeⅫdistribution

Unlike height-diameter equations for standing trees commonly used in forest resources modelling,tree height models for cut-to-length(CTL)stems tend to produce prediction errors whose distributions are not conditionally normal but are rather leptokurtic and heavy-tailed.This feature was merely noticed in previous studies but never thoroughly investigated.This study characterized the prediction error distribution of a newly developed such tree height model for Pin us radiata(D.Don)through the three-parameter Burr TypeⅫ(BⅫ)distribution.The model’s prediction errors(ε)exhibited heteroskedasticity conditional mainly on the small end relative diameter of the top log and also on DBH to a minor extent.Structured serial correlations were also present in the data.A total of 14 candidate weighting functions were compared to select the best two for weightingεin order to reduce its conditional heteroskedasticity.The weighted prediction errors(εw)were shifted by a constant to the positive range supported by the BXII distribution.Then the distribution of weighted and shifted prediction errors(εw+)was characterized by the BⅫdistribution using maximum likelihood estimation through 1000 times of repeated random sampling,fitting and goodness-of-fit testing,each time by randomly taking only one observation from each tree to circumvent the potential adverse impact of serial correlation in the data on parameter estimation and inferences.The nonparametric two sample Kolmogorov-Smirnov(KS)goodness-of-fit test and its closely related Kuiper’s(KU)test showed the fitted BⅫdistributions provided a good fit to the highly leptokurtic and heavy-tailed distribution ofε.Random samples generated from the fitted BⅫdistributions ofεw+derived from using the best two weighting functions,when back-shifted and unweighted,exhibited distributions that were,in about97 and 95%of the 1000 cases respectively,not statistically different from the distribution ofε.Our results for cut-tolength P.radiata stems represented the first case of any tree species where a non-normal error distribution in tree height prediction was described by an underlying probability distribution.The fitted BXII prediction error distribution will help to unlock the full potential of the new tree height model in forest resources modelling of P.radiata plantations,particularly when uncertainty assessments,statistical inferences and error propagations are needed in research and practical applications through harvester data analytics.

Spatial Expression of Assembly Geometric Errors for Multi-axis Machine Tool Based on Kinematic Jacobian-Torsor Model

Assembly geometric error as a part of the machine tool system errors has a significant influence on the machining accuracy of the multi-axis machine tool.And it cannot be eliminated due to the error propagation of components in the assembly process,which is generally non-uniformly distributed in the whole working space.A comprehensive expression model for assembly geometric error is greatly helpful for machining quality control of machine tools to meet the demand for machining accuracy in practice.However,the expression ranges based on the standard quasistatic expression model for assembly geometric errors are far less than those needed in the whole working space of the multi-axis machine tool.To address this issue,a modeling methodology based on the Jacobian-Torsor model is proposed to describe the spatially distributed geometric errors.Firstly,an improved kinematic Jacobian-Torsor model is developed to describe the relative movements such as translation and rotation motion between assembly bodies,respectively.Furthermore,based on the proposed kinematic Jacobian-Torsor model,a spatial expression of geometric errors for the multi-axis machine tool is given.And simulation and experimental verification are taken with the investigation of the spatial distribution of geometric errors on five four-axis machine tools.The results validate the effectiveness of the proposed kinematic Jacobian-Torsor model in dealing with the spatial expression of assembly geometric errors.