Statistical analysis on the influence of mechanical parameters in the vibration of pylons

We present a statistical investigation of the degree of influence that assumptions made in relation to the mechanical parameters of a pylon have on its ground-induced vibrations.The study is set up by using as a key kinematic variable the displacement at the top of a reference,a stand-alone pylon with a uniform cross-section and fixity at its base.Next,statistics are produced using a dimensionless displacement ratio defined between the‘parental’and the‘subsidiary’cases,the latter defined for the pylon(a)resting on compliant soil,(b)having an attached top mass,and(c)being non-uniform with height.Furthermore,two materials are examined,namely,steel and reinforced concrete(R/C).More specifically,this displacement ratio is independent of the excitation and plays the role of a transfer function between the base and the top of the pylon.Both horizontal and vertical motions are considered,and the equations of motion are solved in the frequency domain.The ensuing statistical analysis is conducted for the following parameter combinations:(a)pylon founded on soft,intermediate,and stiff soil;(b)low,intermediate,and high-mass ratios of the attached mass to the pylon′s mass;(c)a constant and quadratic degree of pylon tapering with height.Spearman correlation coefficients are calculated for all the above combinations to arrive at statistical results that establish validity bounds and quantify the degree of influence of each assumption on the pylon′s response.

Effect of Jianpi Bushen formula for colon cancer patients who underwent adjuvant chemotherapy:Statistical analysis plan for a multicenter trial

Background:Patients with colon cancer who receive chemotherapy usually experience various gastrointestinal adverse reactions,including nausea,vomiting,and diarrhea,which make it challenging for them to adhere to treatment.As an effective traditional Chinese medicine,the Jianpi Bushen formula has been widely used to alleviate the side effects of chemotherapy.Objective:To evaluate the efficacy and safety of Jianpi Bushen formulae for patients who undergo chemotherapy.This statistical analysis plan(SAP)is intended to enhance the transparency and research quality of our randomized controlled trial.Methods:Our study is a multicenter,double-blind,randomized controlled clinical trial.This trial aimed to compare the completion rate of chemotherapy in colon cancer patients who are using and not using Jianpi Bushen formula.To attenuate possible selection bias in the final report,we declared the overall trial design,outcome measures,subgroup analyses,and safety measures.Also,we described the data management and statistical analysis methods in detail.Conclusion:The SAP provides more detailed information than the trial protocol for data management and statistical analysis methods.Further post-hoc analyses can be performed by referring to the SAP,and possible selection bias can be attenuated.

Statistical Analysis and Countermeasures for Specimen Rejection in the Emergency Department

The rejected specimens from the Emergency Department of the Center of Clinical Laboratory from January 1,2022 to January 1,2023 were analyzed to reduce the specimen rejection rates and to improve the quality of inspection.The results showed that there were 1488 samples of rejected specimens and the non-conforming rate was 0.58%.The departments involved were mainly the Emergency Department,the Hematology Department,the Cardiology Department,the Intensive Care Department,and the Brain Surgery Department.Among the reasons for rejection,blood hemolysis accounted for 43.15%,blood coagulation accounted for 26.61%,and the rate of insufficient specimens was 17.14%.Among them,the sample rejection rate for arterial blood gas analysis was the highest,which accounted for 1.74%;followed by specimens for coagulation test,which was 1.18%.These results indicate the main reason for producing rejected specimens is mainly due to not following the standard operating procedure.Specimen rejection can largely be avoided if the standards for specimen collection are strictly followed.

STATISTICAL ANALYSIS AND NUMERICAL SIMULATION OF POYANG LAKE'S INFLUENCE ON TROPICAL CYCLONES

Based on the Tropical Cyclone(TC briefly thereafter)Yearbook 1980-2009,this paper first analyzes the number and intensity change of the TCs which passed directly over or by the side of Poyang Lake(the distance of TC center is less than 1°longitude or 1°latitude from the Lake)among all the landfalling TCs in China during the past 30 years.Two cases are examined in detail in this paper.One is severe typhoon Rananim with a speed of 3.26 m/s and a change of 1 hPa in intensity when it was passing the Lake.The other is super typhoon Saomai with a faster moving speed of 6.50 m/s and a larger change in intensity of 6 hPa.Through numerical simulation experiments,this paper analyzes how the change of underlying surface from water to land contributes to the differences in intensity,speed and mesoscale convection of the two TCs when they passed the Lake.Results show that the moisture and dynamic condition above the Lake were favorable for the maintenance of the intensity when Rananim was passing through Poyang Lake,despite the moisture supply from the ocean was cut off.As a result,there was strong convection around the lake which led to a rainfall spinning counter-clockwise as it was affected by the TC movement.However,little impact was seen in the Saomai case.These results indicate that for the TCs coming ashore on Poyang Lake with a slow speed,the large water body is conducive to the sustaining of the intensity and strengthening of the convection around the TC center and the subsequent heavy rainfall.On the contrary,a fast-moving TC is less likely to be influenced by the underlying surface in terms of intensity and speed.

Solar term peak of onset and death in 1 597 patients with acute ischemic stroke Circular statistical analysis

BACKGROUND： Previously, time data were analyzed by using constituent ratio or relative ratio; however, circular statistical analysis could exactly provide average peak phase of diseases. OBJECTIVE： To investigate the correlation of solar term peak with onset and death of acute ischemic stroke. DESIGN： Retrospective case analysis. SETTINGS： Emergency Department of Foshan Municipal Hospital of Traditional Chinese Medicine; Department of Science and Education, the Second People＇s Hospital of Foshan. PARTICIPANTS： A total of 1 597 patients with acute ischemic stroke were selected from Emergency Room, Department of Neurology, Foshan Municipal Hospital of Traditional Chinese Medicine from 1994 to 2002. There were 875 males and 722 females, and their ages ranged from 33 to 97 years. All cases met the diagnostic criteria of acute cerebral infarction modified by the Second National Cerebrovascular Disease Academic Meeting; meanwhile, they were diagnosed with CT/MRI test. Patients and their relatives provided the confirmed consent. METHODS： Solar term of onset was retrospectively analyzed in 1 597 patients with acute ischemic stroke; among them, solar term of death in 90 cases were analyzed by using circular statistical analysis to calculate peak phase of onset and death of acute ischemic stroke and investigate the correlation of solar term with onset and death of acute ischemic stroke. MAIN OUTCOME MEASURES： Onset and death time of patients with acute ischemic stroke. RESULTS： Solar term of onset in 1 597 patients, especially solar term of death in 90 patients, was not concentrated （P 〉 0.05）, and specific peak phase was not found out. Acute ischemic stroke low attacked from vernal equinox to summer begins, but death caused by acute ischemic stroke high attacked from grain buds to autumn begins. CONCLUSION： Patients with acute ischemic stroke do not have specific solar term peak of onset and death.

Optimal Deep Learning Enabled Statistical Analysis Model for Traffic Prediction

Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions.

Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.

Constructing refined null models for statistical analysis of signed networks

The establishment of effective null models can provide reference networks to accurately describe statistical properties of real-life signed networks.At present,two classical null models of signed networks(i.e.,sign and full-edge randomized models)shuffle both positive and negative topologies at the same time,so it is difficult to distinguish the effect on network topology of positive edges,negative edges,and the correlation between them.In this study,we construct three re-fined edge-randomized null models by only randomizing link relationships without changing positive and negative degree distributions.The results of nontrivial statistical indicators of signed networks,such as average degree connectivity and clustering coefficient,show that the position of positive edges has a stronger effect on positive-edge topology,while the signs of negative edges have a greater influence on negative-edge topology.For some specific statistics(e.g.,embeddedness),the results indicate that the proposed null models can more accurately describe real-life networks compared with the two existing ones,which can be selected to facilitate a better understanding of complex structures,functions,and dynamical behaviors on signed networks.

Statistical Analysis of the Asphalt Mixtures Volumetric Properties

Based on statistics principle,random error and systematic error were considered and the volumetric properties of the two mixtures types,namely A and B,were statistically analyzed using different distribution methods.Seventy-two samples of mixture A and fifty-two of mixture B were fabricated using the Marshall method.The probability distributions were compared on the basis of goodness of fit.Weibull model was found to be most appropriate model for describing the asphalt mixtures volumetric properties distribution.The two-parameter Weibull distribution function applied well to model the bulk specific gravity and voids filled with asphalt data,whereas,the three-parameter Weibull distribution appeared to be more appropriate in the discussing of air voids and voids in mineral aggregate.The experimetal results is revealed that compared with the mean value,the peak value of Weibull distribution was suggested as an alternative and more powerful parameter for describing the test data distribution characteristic.The analysis of test results also revealed that there were significant differences in the volumetric properties of the two tested mixtures for the same confidence level.The confidence interval decreased with the decreasing in reliability.

Statistical Analysis with Dingo Optimizer Enabled Routing for Wireless Sensor Networks

Security is a vital parameter to conserve energy in wireless sensor networks(WSN).Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission.But the available routing techniques do not involve security in the design of routing techniques.This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme(SADO-RRS)for WSN.The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN.In addition,the presented SADORRS technique derives a new statistics based linear discriminant analysis(LDA)for attack detection,Moreover,a trust based dingo optimizer(TBDO)algorithm is applied for optimal route selection in the WSN and accomplishes secure data transmission in WSN.Besides,the TBDO algorithm involves the derivation of the fitness function involving different input variables of WSN.For demonstrating the enhanced outcomes of the SADO-RRS technique,a wide range of simulations was carried out and the outcomes demonstrated the enhanced outcomes of the SADO-RRS technique.

A statistical analysis of geomechanical data and its effect on rock mass numerical modeling:a case study

Geomechanical data are never sufficient in quantity or adequately precise and accurate for design purposes in mining and civil engineering.The objective of this paper is to show the variability of rock properties at the sampled point in the roadway's roof,and then,how the statistical processing of the available geomechanical data can affect the results of numerical modelling of the roadway's stability.Four cases were applied in the numerical analysis,using average values(the most common in geomechanical data analysis),average minus standard deviation,median,and average value minus statistical error.The study show that different approach to the same geomechanical data set can change the modelling results considerably.The case shows that average minus standard deviation is the most conservative and least risky.It gives the displacements and yielded elements zone in four times broader range comparing to the average values scenario,which is the least conservative option.The two other cases need to be studied further.The results obtained from them are placed between most favorable and most adverse values.Taking the average values corrected by statistical error for the numerical analysis seems to be the best solution.Moreover,the confidence level can be adjusted depending on the object importance and the assumed risk level.

Statistical Analysis for the Driving Cycle of Beijing's Bus

According to the test data of the driving model for Beijing's bus routes, 9 parameters and the actual values of Beijing bus are confirmed to evaluate the driving cycle, 2 ways of establishing driving cycle model are analyzed, the formula of calculating driving cycle is acquired, and the calculating driving cycle model and the statistical driving cycle model for the buses in Beijing urban areas are set up. This study provides scientific basis for selecting the bus type and confirming the design parameters and the running method in Beijing.

A Statistical Analysis on Papers and Authors in Wuhan University Journal of Natural Sciences in 2003

The author of this article counts and analyzes the papers and authors printed in 2003 Wuhan University Journal of Natural Sciences by means of bibliometric statistical methods, of which the characteristics of papers and authors are expounded. The result shows that the ratio of reprinting of this journal has been increased and the areas where the authors come from and their organization scattered in the whole world are widened as well, which implies a better-known fame of the journal. Key words Wuhan University Journal of Natural Sciences - papers analysis - authors analysis - statistical analysis CLC number G 353.1 Biography: HU Min(1961-), famale, Associate professor, research direction; editing science and biochemistry.

THE STOCHASTIC BOUNDARY ELEMENT METHOD IN STATISTICAL ANALYSIS OF MODERATELY THICK PLATES

In this paper a stochastic boundary element method (SEEM) is developed to analyze moderately thick plates with random material parameters and random thickness. Based on the Taylor series expansion, the boundary integration equations concerning the mean and deviation of the generalized displacements are derived, respectively. It is found that the randomness of material parameters is equivalent to a random load, so the mean and covariance matrices of unknown generalized boundary displacements and tractions can be obtained. Furthermore, the mean and covariance of generalized displacements and forces at internal points can also be obtained. A numerical example has been worked out with the method proposed and necessary analysis is made for the results.

Implementation of Statistical Analysis to Determine Optimum Ultimate Pit

The ultimate pit may affect other aspects in the life of a mine such as economical, technical, environmental, and social aspects. What makes it even more complex is that most often there are many pits which are economically minable. This calls for a heuristic approach to determine which of these pits is the ultimate pit. This study presents a means of selecting an ultimate pit during design operations of the Hebei Limestone mine. During optimization processes of the mine, many pit shells were created using Whittle Software. Normally, Whittle Software optimizes these processes and assigns a revenue factor of 1 for the ultimate pit. Unfortunately, the pit shells created did not satisfy the criteria with a revenue factor of 1 based on the parameters. As a result of this, statistical analysis was implemented to further understand the relationship, variability, and correlation of the pit shells created (data). Correlation Analysis, K-means++ Analysis, Principal Component Analysis, and Generalized Linear models were used in the analysis of the pit shells created. The results portray a salient relationship of the optimization variables. In addition, the proposed method was tested on Whittle Sample projects which satisfy the selection of ultimate pit selection with a revenue factor of 1. The results show that the proposed model produced almost the same results as the Whittle model with a revenue factor of 1 and was also able to determine the ultimate pit in cases which did not satisfy the Whittle selection criteria.

Geochemical Modeling and Statistical Analysis for Groundwater Evolution Assessment in Wadi Qasab, Sohag, Eastern Desert, Egypt

Qasab basin is one of the most promising areas for the sustainable development in the Eastern Desert fringes of the Nile Valley, Egypt. The integration between statistical analysis, stable isotopes as well as geochemical modeling tools delineated the geochemical possesses affecting groundwater quality and detected the main recharge source in Qasab basin. The most of groundwater samples are brackish (88%), while the minority (12%) of the samples are fresh. The electrical conductivity of groundwater ranged from 1135 to 10,030 μS/cm. The statistical analysis and hydrochemical diagrams suggest that the groundwater quality is mainly controlled by several intermixed processes (rock weathering and agricultural activities). The mineralization of the Pleistocene groundwater is regulated by the rock weathering source, evaporation processes and reverse cation exchange. The isotopic signatures (δ2H and δ18O) represent two groundwater groups. The first group, is enriched with the isotopic signature of δ18O, which ranges from 0.9‰ to 5.5‰. This group is mostly affected by the recent meteoric recharge from the surface water leakage. The second group, is relatively depleted with the isotopic signature of δ18O, reflecting a palaeo recharge source of colder climate. The δ18O‰ varies from -10.1‰ to -6.4‰, indicating upward leakage of the Nubian sandstone aquifer through deep seated faults. The inverse geochemical model reflects that the salinity source of the groundwater samples is due to the leaching and dissolution processes of carbonate, sulphate and chloride minerals from the aquifer matrix. This study can demonstrate the hydrochemistry assessment guide to support sustainable development in Qasab basin to ensure that adequate groundwater management can play to reduce poverty and support socioeconomic development.

Quality assessment of Jinhongtang Granule using UFLC-MS/MS and multivariate statistical analysis

Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for Jinhongtang is not available.In present study,we developed a UFLC-MS/MS method to determine 16 analytes in 20 batches of home-made and commercial Jinhongtang.Multivariate statistical analysis revealed the significant differences in the quality of home-made and commercial Jinhongtang and the difference in the quality of home-made samples was more significant.The integrated strategy based on UFLC-MS/MS and multivariate statistical analysis provided a new basis for the overall quality assessment of Jinhongtang.

Study on the Relationship between Soil and Environment Based on Multivariate Statistical Analysis

[Objective] The study aimed to study the relationship between soil and environment on the basis of multivariate statistical analysis. [ Method] Through field investigation, sampling and laboratory analysis, we discussed the relationship between soil properties and environmental factors in Mizhi County, North Shaanxi by using Canoco multivariate statistical analysis. [ Result]According to the effects of various environmental factors on soil properties, the influencing order of environmental factors was land use way 〉 vegetation type 〉 vegetation restoration years 〉 vegeta- tion coverage 〉 slope aspect 〉 gradient 〉 elevation. In a word, soil properties were significantly affected by land use way and vegetation type which were the most important environmental factors of soil properties in spatial variation, while vegetation restoration years were closely related to the ac- cumulation of soil nutrients. [ Condusion]The research could provide theoretical references for the construction of ecological environment in Loess Plateau of China.

Multivariate Statistical Analysis of Large Datasets: Single Particle Electron Microscopy

Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and revealing its underlying general rules. Among the most powerful mathematical tools for organizing and helping to structure complex, heterogeneous and noisy data are the tools provided by multivariate statistical analysis (MSA) approaches. These eigenvector/eigenvalue data-compression approaches were first introduced to electron microscopy (EM) in 1980 to help sort out different views of macromolecules in a micrograph. After 35 years of continuous use and developments, new MSA applications are still being proposed regularly. The speed of computing has increased dramatically in the decades since their first use in electron microscopy. However, we have also seen a possibly even more rapid increase in the size and complexity of the EM data sets to be studied. MSA computations had thus become a very serious bottleneck limiting its general use. The parallelization of our programs—speeding up the process by orders of magnitude—has opened whole new avenues of research. The speed of the automatic classification in the compressed eigenvector space had also become a bottleneck which needed to be removed. In this paper we explain the basic principles of multivariate statistical eigenvector-eigenvalue data compression;we provide practical tips and application examples for those working in structural biology, and we provide the more experienced researcher in this and other fields with the formulas associated with these powerful MSA approaches.

The Application of SPSS in Statistical Analysis Project-A Study of the Inheritance of Chinese Traditional Shadow Play in Schools

Chinese traditional shadow play has been selected into the List of Intangible Cultural Heritage in 2011.Yet,reflecting abundant national cultural values,such traditional art form is degenerating and fading out from people’s sight.As the earliest statistical analysis software,Statistical Package for the Social Science(SPSS)is comprehensive in analyzing and managing statistical data.This study explores the application of SPSS in minimizing the workload of researchers while raising the validity of data in supporting the analysis of the survey data which reflected the inheritance and development of Chinese traditional shadow play in schools.