Evaluation Of Statistical Methods Research Articles

Bioinformatics analysis of correlation between protein function and intrinsic disorder

The correlation of molecular function and protein intrinsic disorder is an important aspect of understanding the relationship between function, sequence and structure. This research was inspired by statistical correlation evaluation method described by Xie et al. (J Proteome Res 6 (2007) 1882–1898, reference study), where the authors analyzed the relationship between structure and function of proteins from Swiss-Prot database and where these functions were described with Swiss-Prot function keywords. In this research, we investigated whether the conclusions from the reference study stand for another dataset with richer functional annotation. We used CAFA3 challenge training dataset where the function was described with terms from Gene Ontology (GO terms). In order to compare the results with the previous work, we associated the GO terms with the corresponding Swiss-Prot function keywords. The results were compared with the reference study by first repeating the analysis with Swiss-Prot function keywords and then by GO terms. We used PONDR VSL2b disorder predictor to label over 66,000 CAFA3 proteins as putatively disordered or ordered. Out of 186 Swiss-Prot keywords (belonging to molecular function type) with more than 20 annotated proteins, we found 47 to be highly order related and 44 highly disorder related. Using the same dataset and annotation constraints, out of 1781 GO term (belonging to molecular function type), we found 746 to be highly order related and 564 highly disorder related. GO term results are presented as interactive graphs displaying complex hierarchical structure of Gene Ontology. Comparison of two functional annotations, GO and Swiss-Prot keywords, showed consistent results in cases when it was possible to map a Swiss-Prot keyword to a corresponding GO term. Because of the small number of such cases, we propose a new method for deriving the missing mappings between Swiss-Prot keywords and GO terms with the highest likelihood by measuring similarity (Jaccard index) between sets of protein annotated by different functions. Comparison with results from the reference study revealed prevalence of binding related functions (disorder related) in the current dataset even though the same functions were not present in previous results.

Evaluation of some elite turmeric genotypes in terai region of West Bengal

An investigation was carried out in the year 2018-19 and 2019-20 in 22 elite turmeric genotypes in terai region of West Bengal for evaluation and characterization according to DUS descriptors. The genotypes were collected from different sources from West Bengal and different turmeric growing regions of the country. The characters were evaluated on the basis of DUS descriptors which were developed by IISR (Indian Institute of Spices Research). Randomized Block Design (RBD) was adopted as statistical method for evaluation of 22 genotypes along with DMRT test for finding the statistical results of the different characters. Qualitative characters like pseudostem habit, leaf deposition, leaf margin, rhizome habit and rhizome shape were also characterized in all the genotypes and grouped according to pattern of divisions of descriptors. TCP 191, LTS-1, TCP 111, TCP 246, TCP 190, TCP 120, TCP 90, TCP 235, TCP58, TCP 232 showed better result than local check variety TCP-2 (Suranjana) after the completion of the investigation. All the varieties excelled in production than national variety PRATIVA, so they can be recommended in this terai region of West Bengal.

System design object-based multi-agent network storage (OBMA-MNSS)

Information superiority is the key to ensure the success of information construction, and information storage system is the basis to obtain information superiority. Based on the analysis of the statistical methods of network value evaluation and the influence of storage system networking on information construction, according to the demand of information construction for data storage application, combined with the latest development of storage technology, an object-based multi-agent military network storage system is proposed. The design goal, design idea and prototype design of the system are given.

Cyclostratigraphy of the Lower Triassic Kangan Formation in the Salman gas field, eastern Persian Gulf, Iran

Cyclostratigraphy plays a pivotal role in detecting and reporting Milankovitch cycles in sedimentary successions which allows for creating an independent astronomical time scale and estimates of sediment accumulation rates. In this study, cyclostratigraphic analysis of petrophysical logs from Lower Triassic Kangan Formation was performed in two wells of the Salman gas field, eastern part of the Persian Gulf, Iran. The results of power spectral analysis in the two studied wells reveal the main spectral peaks at wavelengths of long-eccentricity, short-eccentricity, obliquity, and precession cycles. Based on the orbital tuning using the long-eccentricity cycles, a floating astronomical time scale was established, according to which the depositional duration of Kangan Formation was estimated to be 1.6 ± 0.1 Myr. As well as, the duration of the Induan Stage of the Early Triassic Epoch in this study is estimated to be at least 1.6 Myr. Also, by integrating cyclostratigraphic analysis, results of the statistical methods of sedimentation rate evaluation, i.e., evolutionary correlation coefficient (COCO), it was estimated that the sedimentation rates of Kangan Formation in the two studied wells of Salman gas field increased from ~8 cm/kyr in the bottom to about 12–18 cm/kyr in the upper part, which were linked with the delayed life recovery in Early Triassic. We also observed an enhanced sedimentary noise (ESN) interval in eCOCO maps of the K1 member (upper part of Kangan Formation) at two studied wells, which were linked with the global sea-level fall in the late Griesbachian substage of the Early Triassic. The results of this study show that cyclostratigraphy has made an effective contribution towards analyzing sea-level change and estimating sediment accumulation rates and depositional duration of the Kangan Formation.

Reliability analysis using bootstrap information criterion for small sample size response functions

Statistical model selection and evaluation methods like Akaike information criteria (AIC) and Monte Carlo simulation (MCS) have often established efficient output for reliability analysis with large sample size. Information criterion can provide better model selection and evaluation in small sample sizes setup by considering the well-known measure of bootstrap resampling. Our purpose is to utilize the capabilities of bootstrap resampling in information criterion to check for uncertainty arising from model selection as well as statistics of interest for small sample size using reliability analysis. In this study, therefore, a unique and efficient simulation scheme is proposed which contemplates the best model selection devised from efficient bootstrap simulation or variance reduced bootstrap information criterion to be combined with reliability analysis. It is beneficial to compute the spread of reliability values as against solitary fixed values with desirable statistics of interest for uncertainty analysis. The proposed simulation scheme is verified using a number of sample size focused response functions under repetitions-centred approach with AIC-based reliability analysis for comparison and MCS for accuracy. The results show that the proposed simulation scheme aids the statistics of interest by reducing the spread and hence the uncertainty in sample size-based reliability analysis when compared with conventional methods.

On reliability analysis method through rotational sparse grid nodes

This study aims to develop a rotational sparse grid (R-SPGR) method for statistical moment evaluation and structural reliability analysis with enhanced accuracy and efficiency. The optimal rotational angle in the proposed R-SPGR method is determined by an optimization approach, in which the objective function is constructed in terms of discrepancy between the marginal moments of each input uncertain variables calculated from these rotational sparse grid nodes and their exact values. The R-SPGR nodes allow capturing more information of exact probability distribution for the system response, which is considered critically important to the calculation of statistical moments accurately. Following this, the probability density function (PDF) and failure probability of system response can be efficiently determined by using the saddlepoint approximation technique. To demonstrate the effectiveness of the proposed method, four benchmark examples, one structural analysis example and one practical example of industrial robot are provided here, in which the results obtained from the proposed R-SPGR method are compared with those calculated from the conventional sparse grid (SPGR) method, the maximum entropy problem with fractional moments (ME-FM) method and Monte Carlo simulation (MCS) method. From these illustrative examples involving a wide range of complexity, it is demonstrated that the proposed R-SPGR method has fairly high accuracy and efficiency for structural reliability analysis.

Dynamics of incidence of mental and behavior disorders in children of Ukraine: a 25-years’ observation experience.

Disorders of the psyche and behavior among children is an urgent problem of modern pediatric science and medical practice. The high prevalence of this pathology may be a result of the unfavorable psychological state of society, aggressive effects of the unfiltered information and negative influence of the environment (including radiatioactive factors) on the mind and body of the child. We have studied a 25-years’ trends in morbidity of mental illneses and behavior disorders among children of Ukraine in order to determine the impact of environmental factors (in particular - radioactivity after Chernobyl disaster in 1986) on their development. We have performed an analysis of the incidence and prevalence of psychiatric and behavioral disorders (PBD) among children from different regions of Ukraine, including radioactive regions, contaminated after Chernobyl disaster. We used methods of statistical evaluation and epidemiological analysis of statistical data about the mental health of children of the country, aquired from the Ministry of Health of Ukraine. Over the past 25 years, we have observed trend of reducing the incidence of PBD among children of Ukraine to 3.77 cases per 1,000 children (p<0.01) with prevalence of this pathology among children from large industrial and agricultural regions of the country. We have connected this trend with significant toxic influence of environmental factors on the child's organism. The incidence of PBD in the last 25 years among children from the regions of the country contaminated by the Chernobyl accident in 1986 (especially in Chernihiv and Zhytomyr regions) has exceeded the national incidence rates of PBD and its incidence among children from regions without territories of radiological control. In early 1990s the incidence of mental and behavioral disorders was high among children affected by Chornobyl accident. But over the last 25 years the incidence of PBD has become lower and now its level is even lower than among children who permanently lived in areas contaminated by radiation after the Chernobyl accident and the national incidence rate of PBD among children. The results of our 25-years’ follow-up of PBD morbidity among Ukrainian children have shown that children with prolonged exposure to ecotoxic factors, including radiation, have higher levels of prevalence and incidence of mental and behavioral disorders compared with other children. All this testify that there is a need of a proper correction programs and special attention to this cohort of children.

Determination of Industry Indicators of Financial Analysis of Enterprises (on the Example of the Industry for the Production of Crude Oil and Natural Gas)

The aim of the study is the development of theoretical and methodological principles of the analysis of industry financial indicators. The relevance of the topic is confirmed on the one hand by the demand for industry indicators for all persons interested in financial and comparative analysis of enterprises, on the other hand by the complexity and lack of methods for deriving industry indicators of the financial analysis of enterprises.Materials and methods. The study used a system and comparative analysis, methods of economic and financial analysis of the financial statements of enterprises in the industry, and methods of statistical evaluation of the main parameters of the sample with a lognormal distribution. The main attention is paid to the use of multivariate statistical analysis, the use of the model of lognormal distributions recommended for distributions with pronounced right-hand asymmetry. As the statistical material, the accounting data of the enterprises of the industry for the extraction of crude oil and natural gas for 2016 were used. The sample size was 185 enterprises. In the course of the study, the authors solved the following tasks: proposed stages of analysis for determining industry financial indicators, tested the hypothesis of a lognormal distribution of marginal distributions of the main financial indicators of the sample, tested the hypothesis of a jointly normal distribution of a multi-factor random vector of financial indicators of the sample, obtained the most likely values of financial analysis indicators for the industry of crude oil and natural gas production.Results. The theoretical significance of the work is the algorithm proposed by the authors for calculating industry-specific indicators of financial analysis, characterized by obtaining modal values based on the analysis of the multidimensional logarithmically normal distribution of the vector of financial indicators of a sample of enterprises. In the course of the study, the authors obtained distributions for the main indicators with a pronounced right-hand asymmetry and tested the hypothesis of the lognormal distribution of marginal distributions. The paper presents an algorithm for testing the hypothesis of joint normality of a ninedimensional random vector. Median and modal values of industry and financial indicators were obtained. The authors analyzed the differences between the median and modal results of the study. For analysis, a three-dimensional random vector is considered, including revenue, return on equity and turnover of accounts receivable. The difference between median and modal results is explained by the right-hand asymmetry of the distribution. The recommendations, given by the authors for determining industry indicators of financial analysis of enterprises in the industry for the extraction of crude oil and natural gas are practical in nature and are applicable to all industries.Conclusion. In the work, it is shown that the orientation toward generally established recommended values of coverage indicators, financial leverage, immobilization, profitability and turnover seems incorrect due to the variety of specific features of enterprises in various industries. We recommend calculating the most likely industry coefficients by groups depending on the size of the enterprise (revenue or capitalization).

Breaking force analysis of cotton ring-spun yarns

The most important factor influencing the production efficiency of final textile products made from yarns as well as the product performance are the tensile properties of the yarn. The breaking force of spun yarns, assessed with standard static procedure, depends on several parameters, one of them being the testing conditions. In our research, the effect of testing conditions (climatic conditions, the ratio gauge length/constant rate of extension and sampling, which refers to the number of yarn package and the position of package winding, taken from the bobbin) on the breaking force of 100% cotton ring-spun yarns was analyzed using the statistical evaluation method “ANOVA”. The results clearly indicate that indeed all input parameters of testing conditions have a statistically significant effect on the breaking force of the yarn. When we judge the suitability of yarns to withstand a certain tension produced by technological procedures, not only average breaking force should be focused on. The information regarding the tested minimum breaking force of yarn becomes very important regarding our decision whether yarn fulfills the prescribed value of breaking force.

Statistical Evaluation of Clinical Trials Under COVID-19 Pandemic.

When conducting clinical trials under COVID-19 pandemic, protocol deviations and/or protocol violations are inevitably encountered due to possible environment change which may have an impact on the accuracy and reliability of clinical evaluation of the test treatment under investigation. Protocol deviations and/or violations include, but are not limited to, eligibility criteria, testing procedure, dose and dose regiment, treatment duration and clinical operation of the intended trial. FDA published guidance in March 2020 to assist investigators and institutional boards (IRBs) in assuring the safety of trial participants, maintaining compliance with good clinical practice, and minimizing risks to trial integrity during the COVID-19 pandemic. The purpose of this article is to proposal methods for statistical evaluation in terms of (i) possible shift in target patient population and (ii) assessment of reproducibility of clinical studies conduct under COVID-19 pandemic environment. The proposed methods can be used to determine whether the clinical results of the intended trials are acceptable from both statistical and regulatory perspectives.

Benchmark dose analyses of toxic endpoints in lung cells provide sensitivity and toxicity ranking across metal oxide nanoparticles and give insights into the mode of action

IntroductionThe benchmark dose (BMD) is a dose that produces a predetermined change in the response rate of an adverse effect. This approach is increasingly utilized to analyze quantitative dose-response relationships. To proof this concept, statistical analysis was compared with the BMD approach in order to rank the sensitivity as well as the toxicity and to describe the mode of action. MethodsBronchial (BEAS-2B) and alveolar epithelial cells (A549) were exposed to a wide concentration range (0.4–100 μg/mL) of five metal oxide nanoparticles (CeO2, CuO, TiO2, ZnO, ZrO2). Eight toxicity endpoints were determined representing integrity of lysosomal and cell membrane, oxidative stress level, glutathione based detoxification (glutathione S-transferase), oxidative metabolism (cytochrome P450), alteration of the mitochondrial membrane potential, alteration of phase II antioxidative enzyme (NAD(P)H:quinone oxidoreductase), and de novo DNA synthesis. ResultsBased on the BMD calculated for the most sensitive test, the toxicity decreased in the following order: ZnO > CuO > TiO2>ZrO2>CeO2 in BEAS-2B. Both statistical evaluation methods revealed a higher sensitivity of BEAS-2B cells. The BMD-derived mode of action for CuO confirmed the existing hypotheses and provided insights into less known mechanisms. ConclusionThe findings proofed that BMD analysis is an effective tool to evaluate different aspects of risk assessment.

Decision Trees for Evaluation of Mathematical Competencies in the Higher Education: A Case Study

The assessment of knowledge and skills acquired by the student at each academic stage is crucial for every educational process. This paper proposes and tests an approach based on a structured assessment test for mathematical competencies in higher education and methods for statistical evaluation of the test. A case study is presented for the assessment of knowledge and skills for solving linear algebra and analytic geometry problems by first-year university students. The test includes three main parts—a multiple-choice test with four selectable answers, a solution of two problems with and without the use of specialized mathematical software, and a survey with four questions for each problem. The processing of data is performed mainly by the classification and regression tree (CART) method. Comparative analysis, cross-tables, and reliability statistics were also used. Regression tree models are built to assess the achievements of students and classification tree models for competency assessment on a three-categorical scale. The influence of 31 variables and groups of them on the assessment of achievements and grading of competencies is determined. Regression models show over 94% fit with data and classification ones—up to 92% correct classifications. The models can be used to predict students’ grades and assess their mathematical competency.

Evaluation of statistical methods used in the estimation of breakdown voltage distribution

Multiple-level and up-and-down test methods are commonly employed in laboratories to obtain the breakdown voltage distribution of self-restoring insulation, which is applied for equipment evaluation and for risk calculation in insulation coordination studies. This study investigates the reliability of the methods and proposes a methodology for evaluating their performance. The accuracy and precision of the estimated distribution parameters were analysed considering the variation of the test parameters. Algorithms that simulate the random nature of the tests were developed and applied in simulations. Then, a case study of risk calculation was carried out. The results indicated that both methods estimate the critical flashover voltage with acceptable accuracy and precision, even for the minimum parameters defined by standards. However, estimating the standard deviation is the critical step of the tests. The proposed methodology allows parameter definition for a given reliability requirement in the case of the constant voltage method. In the case of the up-and-down method, however, high dispersion was observed for all analysed cases, which indicates that this method presents low reliability for calculating flashover risk and, therefore, its use for insulation coordination studies is not recommended.

Exceedance Probability Assessment of Pedestrian Wind Environment Based on Multiscale Coupling Numerical Simulation

AbstractThis paper presents exceedance probability assessment, which is a statistical evaluation method for pedestrian wind environment based on numerical simulations with multiscale coupling techn...

Ley de Benford con muestras pequeñas: una prueba exacta nueva útil en ciencias de la salud durante epidemias

Benford or “first digit” law has been used successfully to evaluate epidemiological surveillance systems, especially during epidemics. Conventional statistical methods for evaluation (x2 and log-likelihood ratio) are controversial when the number of data is small (n <7). In this methodological note a new test is proposed to evaluate compliance with Benford’s law with small samples, which can be used with biomedical, medical and public health data.

Dynamic Evaluation Method of Caprock Microscopic Sealing in CO2 Sequestration Project

The existing statistical evaluation methods of caprock sealing ability in CO2 sequestration engineering only take into account the sealing ability of caprocks before sequestration but cannot reflect the retained sealing ability of caprock after hydrochemical reactions. A microscopic sealing evaluation method of caprock was established based on the microscopic mechanism of chemical reaction and the breakthrough pressure of caprock which, changes with the time of CO2 sequestration, was taken as the dynamic evaluation index. The results show that the change of microstructure parameters such as the average pore radius after dissolution is the essential reason that affects the variation of the caprock microscopic sealing property. Dissolution or precipitation of different caprock minerals during the chemical reaction process is the key factor that determines the decrease or increase of caprock microscopic sealing property. The evaluation method can reflect the change of microscopic sealing property of the caprocks in different areas as the sealing time goes and provides an efficient and practical quantitative evaluation method for the initial formation site selection and safety sealing in the later stage.

A statistical method for pitch measurement and evaluation

Nano grating is one of the common standards in micro-nano scale dimensional measurement and calibration. Errors terming from the measurement system, measurement procedure, data process and the object (specimen) affect the grating evaluation result. Either more precise measurement systems or optimization in methodology is underdeveloped to realize more accurate measurement. In this study, a measuring procedure, using scanning probe microscopy to measure 1D grating, is put forward firstly, mainly to reduce cosine error. Then a measuring statistical model is established based on the statistical characteristics of measurement system, terming from both the machine and the standard. By measuring the grating area for enough times, the mathematical equations are fitted and the statistical characteristic variables, i.e. the mathematical expectation and variance of both the measurement machine error and the grating are to be solved. Practically, the grating is measured in roughly the same area for several times using a nano measurement machine, with unknown error. The grating pitch as well as the errors of the machine stage were evaluated.

Новые индустриальные города: методический аспект исследования

The paper is devoted to characteristic of new industrial cities as a new type of industrial cities, formed under the new industrialization and digital economy. The authors developed and tested their own methodology for their selection based on the use of available data as well as the nature of the object of the research. The methods, applied for the research are statistical methods and methods for expert evaluation. Twenty-eight Russian cities could be regarded as new industrial ones. Most of them have more than 250,0 thousand people. The results may be used in investigation of new industrial cities from the economics, management, urban planning and others points of view. The presented methodology may be test for others countries except for the Russian Federation.

ANALYSIS OF AQI CHANGE CHARACTERISTICS AND CORRELATION WITH PM2.5 AND PM10 IN BEIJING-TIANJIN-HEBEI REGION

Abstract. The paper analyzed the variation characteristics of AQI and its correlation with PM2.5 and PM10 of in Beijing-Tianjin-Hebei region from July 2015 to July 2018 based on hours of pollutants in Beijing-Tianjin-Hebei region, using AQI calculation method and statistical correlation evaluation method. Results showed that:(1) The air quality compliance rate in Beijing-Tianjin-Hebei region was 67%, the average AQI was 97.6577, and the air quality was good. The distribution frequency of primary pollutants was PM2.5, followed by PM10, which accounts for 78.9% of the distribution frequency of the six major pollutants, indicated that PM2.5 and PM10 had a greater impact on the air quality of Beijing-Tianjin-Hebei. (2) The correlation between AQI and PM2.5 and PM10 was significantly positively correlated. R2 was 0.8225 and 0.7749, respectively, P < 0.01, indicated that both showed a greater impact on air quality. (3) AQI and PM2.5 and PM10 showed a gradual decrease trend at 9h–16h, ie 9h highest and 16h lowest. The AQI fluctuated between 94.2816 and 103.3562, indicated that the air quality at 9h–16h was good or slightly polluted. (4) The spatial distribution of AQI, PM2.5 and PM10 was characterized by low northwest and high southeast, and the southeastern part was gradually decreasing from 9h–16h. AQI was negatively correlated with elevation. The higher the elevation, the better the air quality, and the worse the air quality.

Анализ методов статистической оценки эксплуатационной надежности вычислительных комплексов

Анализ методов статистической оценки эксплуатационной надежности вычислительных комплексов