Evaluation of Dosimetric Impact of Uncertainty of Measurement in Estimating External Radiotherapy Dose

Cancer is a major societal public health and economic problem, responsible for one in every six deaths. Radiotherapy is the main technique of treatment for more than half of cancer patients. To achieve a successful outcome, the radiation dose must be delivered accurately and precisely to the tumor, within ± 5% accuracy. Smaller uncertainties are required for better treatment outcome. The objective of the study is to investigate the uncertainty of measurement of external radiotherapy beam using a standard ionization chamber under reference conditions. Clinical farmers type ionization chamber measurement was compared against the National Reference standard, by exposing it in a beam 60Co gamma source. The measurement set up was carried out according to IAEA TRS 498 protocol and uncertainty of measurement evaluated according to GUM TEDDOC-1585. Evaluation and analysis were done for the identified subjects of uncertainty contributors. The expanded uncertainty associated with 56 mGy/nC ND,W was found to be 0.9% corresponding to a confidence level of approximately 95% with a coverage factor of k = 2. The study established the impact of dosimetry uncertainty of measurement in estimating external radiotherapy dose. The investigation established that the largest contributor of uncertainty is the stability of the ionization chamber at 36%, followed by temperature at 22% and positioning of the chamber in the beam at 8%. The effect of pressure, electrometer, resolution, and reproducibility were found to be minimal to the overall uncertainty. The study indicate that there is no flawless measurement, as there are many prospective sources of variation. Measurement results have component of unreliability and should be regarded as best estimates of the true value. .

Measurement Uncertainty Analysis of the Rotary-scan Method for the Measurable Dimension of Cylindrical Workpieces

The measurement uncertainty analysis is carried out to investigate the measurable dimensions of cylindrical workpieces by the rotary-scan method in this paper.Due to the difficult alignment of the workpiece with a diameter of less than 3 mm by the rotary scan method,the measurement uncertainty of the cylindrical workpiece with a diameter of 3 mm and length of 50 mm which is measured by a roundness measuring machine,is evaluated according to GUM(Guide to the Expression of Uncertainty in Measurement)as an example.Since the uncertainty caused by the eccentricity of the measured workpiece is different with the dimension changing,the measurement uncertainty of cylindrical workpieces with other dimensions can be evaluated the same as the diameter of 3 mm but with different eccentricity.Measurement uncertainty caused by different eccentricities concerning the dimension of the measured cylindrical workpiece is set to simulate the evaluations.Compared to the target value of the measurement uncertainty of 0.1μm,the measurable dimensions of the cylindrical workpiece can be obtained.Experiments and analysis are presented to quantitatively evaluate the reliability of the rotary-scan method for the roundness measurement of cylindrical workpieces.

Complexity Considerations in the Heisenberg Uncertainty Principle

This work introduces a modification to the Heisenberg Uncertainty Principle (HUP) by incorporating quantum complexity, including potential nonlinear effects. Our theoretical framework extends the traditional HUP to consider the complexity of quantum states, offering a more nuanced understanding of measurement precision. By adding a complexity term to the uncertainty relation, we explore nonlinear modifications such as polynomial, exponential, and logarithmic functions. Rigorous mathematical derivations demonstrate the consistency of the modified principle with classical quantum mechanics and quantum information theory. We investigate the implications of this modified HUP for various aspects of quantum mechanics, including quantum metrology, quantum algorithms, quantum error correction, and quantum chaos. Additionally, we propose experimental protocols to test the validity of the modified HUP, evaluating their feasibility with current and near-term quantum technologies. This work highlights the importance of quantum complexity in quantum mechanics and provides a refined perspective on the interplay between complexity, entanglement, and uncertainty in quantum systems. The modified HUP has the potential to stimulate interdisciplinary research at the intersection of quantum physics, information theory, and complexity theory, with significant implications for the development of quantum technologies and the understanding of the quantum-to-classical transition.

Efficacy evaluation and survival analysis of the combination of oxaliplatin plus Teysuno (SOX) with immune checkpoint inhibitors in the conversion therapy of locally advanced gastric cancer

Background:The efficacy of combining immune checkpoint inhibitors(ICIs)with chemotherapy in neoadjuvant therapy for locally advanced gastric cancer has been explored.However,limited research exists on its effectiveness in conversion therapy,and its superiority over standalone chemotherapy remains to be elucidated.This study aims to investigate the efficacy and survival outcomes of patients treated with ICIs in combination with conversion therapy for locally advanced gastric cancer.Methods:Retrospective data from patients with locally advanced gastric cancer treated with either oxaliplatin+S-1(SOX)alone or in combination with ICIs in conversion therapywere collected.Clinical andpathological characteristics,disease-free survival,andefficacy assessments in nonoperable patients were compared between the 2 treatment groups.Efficacy was further evaluated through dynamic changes in serum markers,and patients’quality of life was assessed using the QLQ-STO22(Gastric Cancer–Specific Quality of Life Questionnaire)quality-of-life measurement scale.Results:A total of 140 patients underwent conversion therapy:80 in the SOX alone group and 60 in the SOX combined with the ICIs group.There were no significant differences in baseline characteristics between the 2 groups.Compared with the SOX alone group,the SOX combined with ICIs group exhibited a higher conversion rate(83.3%vs 75%,P=0.23),R0 resection rate(90.0%vs 83.3%,P=0.31),pathological complete response(pCR)rate(18%vs 5%,P=0.02),median disease-free survival(21.4 vs 16.9 months,P=0.007),the objective response rate in nonoperable patients(60%vs 40%,P=0.301),and median progression-free survival time(7.9 vs 5.7 months,P=0.009).The QLQ-STO22 quality-of-life assessment revealed statistically significant improvements in pain,swallowing difficulties,and dietary restrictions in the combination therapy group compared with those in the monotherapy group.The enhanced efficacy of immune combination with SOX is evident,as demonstrated by the significantly prolonged surgical duration in operated patients(206.6±26.6 min vs 197.8±19.8 min,P=0.35)and intraoperative blood loss(158.9±21.2 mL vs 148.9±25.1 mL,P=0.59).No significant differences were observed in postoperative complications.Conclusions:Compared with the SOX conversion therapy regimen,SOX combined with ICIs demonstrated higher conversion rates,R0 resection rates,pathological response rates,and disease-free survival without increasing surgical difficulty or complications.Nonoperable patients also experienced longer progression-free survival and objective response rates.

A Nationwide Evaluation of the State of Practice of Performance Measurements for Intelligent Transportation Systems

State departments of transportation’s (DOTs) decisions to invest resources to expand or implement intelligent transportation systems (ITS) programs or even retire existing infrastructure need to be based on performance evaluations. Nonetheless, an apparent gap exists between the need for ITS performance measurements and the actual implementation. The evidence available points to challenges in the ITS performance measurement processes. This paper evaluated the state of practice of performance measurement for ITS across the US and provided insights. A comprehensive literature review assessed the use of performance measures by DOTs for monitoring implemented ITS programs. Based on the gaps identified through the literature review, a nationwide qualitative survey was used to gather insights from key stakeholders on the subject matter and presented in this paper. From the data gathered, performance measurement of ITS is fairly integrated into ITS programs by DOTs, with most agencies considering the process beneficial. There, however, exist reasons that prevent agencies from measuring ITS performance to greater detail and quality. These include lack of data, fragmented or incomparable data formats, the complexity of the endeavor, lack of data scientists, and difficulty assigning responsibilities when inter-agency collaboration is required. Additionally, DOTs do not benchmark or compare their ITS performance with others for reasons that include lack of data, lack of guidance or best practices, and incomparable data formats. This paper is relevant as it provides insights expected to guide DOTs and other agencies in developing or reevaluating their ITS performance measurement processes.

Socio-scientific quantification of the comprehensive benefits of debris flow mitigation measures for villages in western Sichuan, China

Debris flow hazards seriously threaten thesafety and sustainable development of mountainousareas. Numerous debris flow mitigation measures havebeen implemented worldwide;however, acomprehensive assessment of the specific disasterreduction effects of these measures and their economic,social and ecological benefits is yet to be performed.The western region of Sichuan Province frequentlysuffers from geohazards such as debris flow, and thegovernment has adopted many mitigation measures.This study assessed the benefits of debris flowmitigation measures and identified the key influencingfactors via a field-based study conducted in 81 villagesin western Sichuan province, China. A framework forthe evaluation of the benefits of rural debris flowmitigation measures was constructed andquantitatively evaluated using a survey. Snowballsampling was performed to recruit 81 village leadersand 468 farmers. The results showed that managementand engineering measures were the main methodsused to mitigate debris flow;ecological measures wereauxiliary. The average satisfaction scores of farmers forthese three types of measures were 4.07, 3.90, and 3.56,respectively (as measured on a five-point Likert scale).In contrast, in terms of the benefits of these mitigationmeasures, only a small proportion of villages (11.11%)obtained a high level of comprehensive benefits fromthe debris flow mitigation measures, while the majority(88.89%) received medium to low-level benefits. Toimprove this situation, we further studied and foundthat the main factors that restricted villages fromachieving high-level comprehensive benefits were theunpredictable nature of debris flows, labour forceoutflow and remoteness. Effective control measures, agood economic environment and strong governmentassistance were reported as crucial factors forimproving these comprehensive benefits. This studyprovides socio-scientific references for decisionmakingon rural debris flow mitigation measures while keeping villages at the centre of economic development.

Bayesian partial pooling to reduce uncertainty in overcoring rock stress estimation

The state of in situ stress is a crucial parameter in subsurface engineering,especially for critical projects like nuclear waste repository.As one of the two ISRM suggested methods,the overcoring(OC)method is widely used to estimate the full stress tensors in rocks by independent regression analysis of the data from each OC test.However,such customary independent analysis of individual OC tests,known as no pooling,is liable to yield unreliable test-specific stress estimates due to various uncertainty sources involved in the OC method.To address this problem,a practical and no-cost solution is considered by incorporating into OC data analysis additional information implied within adjacent OC tests,which are usually available in OC measurement campaigns.Hence,this paper presents a Bayesian partial pooling(hierarchical)model for combined analysis of adjacent OC tests.We performed five case studies using OC test data made at a nuclear waste repository research site of Sweden.The results demonstrate that partial pooling of adjacent OC tests indeed allows borrowing of information across adjacent tests,and yields improved stress tensor estimates with reduced uncertainties simultaneously for all individual tests than they are independently analysed as no pooling,particularly for those unreliable no pooling stress estimates.A further model comparison shows that the partial pooling model also gives better predictive performance,and thus confirms that the information borrowed across adjacent OC tests is relevant and effective.

Objective Model Selection in Physics: Exploring the Finite Information Quantity Approach

Traditional methods for selecting models in experimental data analysis are susceptible to researcher bias, hindering exploration of alternative explanations and potentially leading to overfitting. The Finite Information Quantity (FIQ) approach offers a novel solution by acknowledging the inherent limitations in information processing capacity of physical systems. This framework facilitates the development of objective criteria for model selection (comparative uncertainty) and paves the way for a more comprehensive understanding of phenomena through exploring diverse explanations. This work presents a detailed comparison of the FIQ approach with ten established model selection methods, highlighting the advantages and limitations of each. We demonstrate the potential of FIQ to enhance the objectivity and robustness of scientific inquiry through three practical examples: selecting appropriate models for measuring fundamental constants, sound velocity, and underwater electrical discharges. Further research is warranted to explore the full applicability of FIQ across various scientific disciplines.

Comprehensive applicability evaluation of four precipitation products at multiple spatiotemporal scales in Northwest China

Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

The Evaluation of Measurement Uncertainty and Its Application in the Vacuum Pressure Measurement

In order to accurately measure the pressure and the pressure difference between two points in the vacuum chamber, a large number of experimental data were used to research the performance of the three capacitance diaphragm gauge and analysis the main influences of the uncertainly degree of pressure in the process. In this paper, three kind of uncertainty, such as the single uncertainty, the synthesis uncertainty and the expanded uncertainty of the three capacitance diaphragm gauges are introduced in detail in pressure measurement. The results show that the performance difference of capacitance diaphragm gauge can be very influential to the accuracy of the pressure difference measurement and the uncertainty of different pressure can be very influential to pressure measurement. That for accurately measuring pressure and pressure difference has certain reference significance.

Uncertainty entropy-based exploratory evaluation method and its applications on missile effectiveness evaluation

Some attributes are uncertain for evaluation work because of incomplete or limited information and knowledge.It leads to uncertainty in evaluation results.To that end,an evaluation method,uncertainty entropy-based exploratory evaluation(UEEE),is proposed to guide the evaluation activities,which can iteratively and gradually reduce uncertainty in evaluation results.Uncertainty entropy(UE)is proposed to measure the extent of uncertainty.First,the belief degree distributions are assumed to characterize the uncertainty in attributes.Then the belief degree distribution of the evaluation result can be calculated by using uncertainty theory.The obtained result is then checked based on UE to see if it could meet the requirements of decision-making.If its uncertainty level is high,more information needs to be introduced to reduce uncertainty.An algorithm based on the UE is proposed to find which attribute can mostly affect the uncertainty in results.Thus,efforts can be invested in key attribute(s),and the evaluation results can be updated accordingly.This update should be repeated until the evaluation result meets the requirements.Finally,as a case study,the effectiveness of ballistic missiles with uncertain attributes is evaluated by UEEE.The evaluation results show that the target is believed to be destroyed.

Monte Carlo Method for the Uncertainty Evaluation of Spatial Straightness Error Based on New Generation Geometrical Product Specification

Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.

Measurement Uncertainty Evaluation of Conicity Error Inspected on CMM

The cone is widely used in mechanical design for rotation, centering and fixing. Whether the conicity error can be measured and evaluated accurately will directly influence its assembly accuracy and working performance. According to the new generation geometrical product specification（GPS）, the error and its measurement uncertainty should be evaluated together. The mathematical model of the minimum zone conicity error is established and an improved immune evolutionary algorithm（IlEA） is proposed to search for the conicity error. In the IIEA, initial antibodies are firstly generated by using quasi-random sequences and two kinds of affinities are calculated. Then, each antibody clone is generated and they are self-adaptively mutated so as to maintain diversity. Similar antibody is suppressed and new random antibody is generated. Because the mathematical model of conicity error is strongly nonlinear and the input quantities are not independent, it is difficult to use Guide to the expression of uncertainty in the measurement（GUM） method to evaluate measurement uncertainty. Adaptive Monte Carlo method（AMCM） is proposed to estimate measurement uncertainty in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. The cone parts was machined on lathe CK6140 and measured on Miracle NC 454 Coordinate Measuring Machine（CMM）. The experiment results confirm that the proposed method not only can search for the approximate solution of the minimum zone conicity error（MZCE） rapidly and precisely, but also can evaluate measurement uncertainty and give control variables with an expected numerical tolerance. The conicity errors computed by the proposed method are 20%-40% less than those computed by NC454 CMM software and the evaluation accuracy improves significantly.

Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors

Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated database.Four assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual index.The corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are analyzed.The combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the samples.Ultimately,the established ensemble model is further validated through test samples with 100%accuracy.The results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.

Analysis and Applications of the Measurement Uncertainty in Electrical Testing

Recently, uncertainty measurement is more and more recognizable in modern data management, conformity assessment, and laboratory accreditation system because of its importance. In this paper, a set of reasonable probability explanations are introduced and an effective method is pro- posed to quantify the assessment indices for the uncertainty measurement of electrical testing laboratory. First of all, the influence from uncertainty factors during the test process is taken into account. With the use of ISO/IEC Guide 98-3 standard and probability theory, the index and model for the measurement uncertainty assessment of a laboratory is then derived. From the simulation results of safety testing, laboratory uncertainty measurement assessment activity for actual electrical appliances, and the confirmation of Monte Carlo simulation method, the appropriateness and correctness of proposed method are verified.

Fire risk evaluation research on fully mechanized coalface based on the uncertainty measure theory

A relatively perfect coalmine fire risk-evaluating and order-arranging model that includes sixteen influential factors was established according to the statistical information of the fully mechanized coalface ground on the uncertainty measure theory. Then the single-index measure function of sixteen influential factors and the calculation method of computing the index weight ground on entropy theory were respectively established. The value assignment of sixteen influential factors was carried out by the qualitative analysis and observational data, respectively, in succession. The sequence of fire danger class of four experimental coalfaces could be obtained by the computational aids of Matlab according to the confidence level criterion. Some conclusions that the fire danger class of the No.l, No.2 and No.3 coalface belongs to high criticality can be obtained. But the fire danger class of the No.4 coalface belongs to higher criticality. The fire danger class of the No.4 coalface is more than that of the No.2 coalface. The fire danger class of the No.2 coalface is more than that of the No.1 coalface. Finally, the fire danger class of the No.1 coalface is more than that of the No.3 coalface.

Multilevel Tests and Measurement Evaluation Methods for the Application of Composite Materials in Spacecraft Structures

With the implementation of new-generation launch vehicles,space stations,lunar and deep space exploration,etc.,the development of spacecraft structures will face new challenges. In order to reduce the spacecraft weight and increase the payload,composite material structures will be widely used. It is difficult to evaluate the strength and life of composite materials due to their complex mechanism and various phenomena in damage and failure.Meanwhile,the structures of composite materials used in spacecrafts will bear complex loads,including the coupling loads of tension,pressure,bending,shear,and torsion. Static loads,thermal loads,and vibration loads may occur at the same time,which asks for verification requirements to ensure the structure safety. Therefore,it is necessary to carry out a systematic multi-level experimental study. In this paper,the building block approach (BBA) is used to investigate the multilevel composite material structures for spacecrafts. The advanced measurement technology is adopted based on digital image correlation (DIC) and piezoelectric and optical fiber sensors to measure the composite material structure deformation. The virtual experiment technology is applied to provide sufficient and reliable data for the evaluation of the composite material structures of spacecrafts.

Helical angle measurement of worm by a coordinate measuring machine and its uncertainty evaluation

The purpose of the study concerns the measurement of worm's helical angle by a coordinate measurement machine in the ambient industrial environment. The novel measurement method and sampling strategy were described firstly. This method used the coordinate measurement machine to measure both of the worm gear's left and right surfaces. The worm surface was reconstructed based on the measured data of all the sampling points. Then a middle cylinder was established to truncate the fitted worm surfaces, and the truncated spiral lines were straightened to calculate the helical angle. The measurement uncertainty of worm's helical angle was evaluated by taking the difference of calculated helical angles along the truncated spiral lines on both the left and right side surfaces of the worm. Twenty-four measurement experiments show that the maximum measurement error of the proposed method is 0.105, and the measurement error ratios are all less than 3.5%. The result means that the measurement method can realize the precision measurement of worm's helical angle and can be employed in the generally industrial application.

The Measurement and Uncertainty Analysis of Antenna Factor of Microwave Antennas Based on Standard Site Method

A method of Standard Site Method (SSM) in the American National Standards Institute’s ANSI C63.5 is described in the frequency ranges from 30 MHz to 1000 MHz. And a measurement system is set up for determining antenna factors (AF) of antennas on an Open Area Test Sites (OATS). AF of antennas including log-periodic antenna and biconical antenna is measured with SSM method by Shanghai Institute of Measurement and Testing Technology (SIMT), which shows good agreement to data measured by National Institute of Metrology (NIM). In the end, it analyzes the measurement uncertainty of SIMT in the 30 MHz to 1000 MHz frequency band and does comparison to that of NIM.

Evaluation of Uncertainty in Measuring the Content of CaM V35S Promoter in Genetically Modified Soybean,GTS40-3-2,by Real-time Quantitative PCR

[ Objective ] This study aimed to investigate the major contributors to the measurement uncertainty in quantitative analysis of genetically modified ingreclients and improve the quality of quantitative detection of genetically modified components. [ Method] The content of CaMV35S promoter （parameter） in GTS40- 3-2 soybean powder samples was measured to estimate the measurement uncertainty preliminarily. [ Result] Type A uncertainty （uA） ＇ type B uncertainty （uB） and combined standard uncertainty （Uc） were 0.0 004, 0.002 and 0.002, respectively. At a confidence level ofp = 95% and freedom degree of Voff = 3 251, coverage factor k = 1.96, expanded uncertainty U = 0.004. The final measurement result was C = 0.028 ± 0. 004, which was dose to the conventional true value （0.03）. Thus, the measurement uncertainty was relatively small, indicating a high quality of measurement. In this study, uncertainty evaluation indicated that the deviation of micro liquid transfer made the greatest contribution to the measurement uncertainty. [ Cludusion ] The deviation of micro liquid transfer should be reduced to im- prove the quality of measurement.