The application of geostatistics in grain size trend analysis： A case study of eastern Beibu Gulf

There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters （i.e. mean size, sorting and skewness） were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical analysis can also offer useful information for the determination of sediment sampling density in the future field work.

Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years,signed directed graph(SDG) ,one of the qualitative simulation technologies,has been widely applied for chemical fault diagnosis.However,SDG based fault diagnosis,as any other qualitative method,has poor diagnostic resolution.In this paper,a new method that combines SDG with qualitative trend analysis(QTA) is presented to improve the resolution.In the method,a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model.Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consis-tent paths found in the previous step.New consistency rules based on qualitative trends are used to find the real causes from the candidate causes.The resolution can be improved.This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA.The implementation of SDG-QTA based fault diagno-sis is done using the integrated SDG modeling,inference and post-processing software platform.Its application is illustrated on an atmospheric distillation tower unit of a simulation platform.The result shows its good applicability and efficiency.

Innovative trend analysis of annual and seasonal precipitation in Ningxia,China

Based on daily rainfall data from 26 station records,spatial and temporal variations in annual and seasonal precipitation of different rainfall intensities from 1961 to 2018 in Ningxia,China are investigated using the innovative trend analysis(ITA)method.The results show that annual precipitation increases on the northern plain but decreases in the southern mountainous area.The increase in regional annual precipitation is mainly due to an increase in weak precipitation,while the decrease in regional annual rainfall is a result of a reduction in heavy precipitation.Lowintensity precipitation shows an upward trend,while high-intensity precipitation shows a downward trend.The variation trend of extreme precipitation is more obvious.The contributions of different types of extreme precipitation vary by season.During spring,the increase in regional rainfall is mainly caused by the increase in heavy precipitation,while the decrease in regional precipitation is mainly caused by the decrease in weak precipitation.During summer and autumn,the increase in regional precipitation is caused by the increase in light precipitation,while the reduction in regional rainfall is caused by the decrease in heavy precipitation.This study provides support for water resources planning and addressing droughts and floods.

Qualitative Algebra and Graph Theory Methods for Dynamic Trend Analysis of Continuous System

Qualitative algebraic equations are the basis of qualitative simulation,which are used to express the dynamic behavior of steady-state continuous processes.When the values and operation of qualitative variables are redefined,qualitative algebraic equations can be transformed into signed direct graphs,which are frequently used to predict the trend of dynamic changes.However,it is difficult to use traditional qualitative algebra methods based on artificial trial and error to solve a complex problem for dynamic trends.An important aspect of modern qualitative algebra is to model and characterize complex systems with the corresponding computer-aided automatic reasoning.In this study,a qualitative affection equation based on multiple conditions is proposed,which enables the signed di-rect graphs to describe complex systems better and improves the fault diagnosis resolution.The application to an industrial case shows that the method performs well.

Image texture indices and trend analysis for forest disturbance assessment under wood harvest regimes

Effective disturbance indices for Hyrcanian forests in Kheyroud,Nowshahr,Iran were determined.The study area was divided into landscape mosaics based on ecosystem parameters including profile type,slope and elevation.Co-occurrence texture indices were derived as forest disturbance factors on the first five bands of Landsat TM,ETM+and OLI images for the prevailing wood harvest disturbance regimes.These indices were screened using ten types of trend analyses and used for modeling disturbance of the harvesting regime through artificial neural networks.The results show that the selected indices can be useful in distinguishing areas with different disturbance intensities and as such,used in the context of health assessment through the health distance method.The accuracy of the health maps derived from the indices[increasing disturbance]led to give rise higher disturbance classification accuracy.

Feature Extraction Technique for Fault Prognosis Based on Fault Trend Analysis

Fault prognosis is one of the key techniques for prognosis and health management,and an effective fault feature can improve prediction accuracy and performance. A novel approach of feature extraction for fault prognosis based on fault trend analysis was proposed in this paper. In order to describe the ability of tracking fault growth process,definitions and calculations of fault trackability was developed, and the feature which had the maximum fault trackability was selected for fault prognosis. The vibration data in bearing life tests were used to verify the effectiveness of the method was proposed. The results showed that the trackability of energy entropy for bearing fault growth was the maximum,and it was the best fault feature among selected features root mean square( RMS),kurtosis,new moment and energy entropy. The proposed approach can provide a better strategy for fault feature extraction of bearings in order to improve prediction accuracy.

Increasing pancreatic cancer is not paralleled by pancreaticoduodenectomy volumes in Brazil:A time trend analysis

Background: Currently, surgical resection represents the only curative treatment for pancreatic cancer(PC), however, the majority of tumors are no longer resectable by the time of diagnosis. The aim of this study was to describe time trends and distribution of pancreaticoduodenectomies(PDs) performed for treating PC in Brazil in recent years. Methods: Data were retrospectively obtained from Brazilian Health Public System(namely DATASUS) regarding hospitalizations for PC and PD in Brazil from January 2008 to December 2015. PC and PD rates and their mortalities were estimated from DATASUS hospitalizations and analyzed for age, gender and demographic characteristics. Results: A total of 2364 PDs were retrieved. Albeit PC incidence more than doubled, the number of PDs increased only 37%. Most PDs were performed in men(52.2%) and patients between 50 and 69 years old(59.5%). Patients not surgically treated and those 70 years or older had the highest in-hospital mortality rates. The most developed regions(Southeast and South) as well as large metropolitan integrated municipalities registered 76.2% and 54.8% of the procedures, respectively. LMIM PD mortality fluctuated, ranging from 13.6% in 2008 to 11.8% in 2015. Conclusions: This study suggests a trend towards regionalization and volume-outcome relationships for PD due to PC, as large metropolitan integrated municipalities registered most of the PDs and more stable mortality rates. The substantial differences between PD and PC increasing rates reveals a limiting step on the health system resoluteness. Reduction in the number of hospital beds and late access to hospitalization, despite improvement in diagnostic methods, could at least in part explain these findings.

Change Point Detection and Trend Analysis for Time Series

Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends.

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

Long-term,ground-based daily global solar radiation (DGSR) at Zhongshan Station in Antarctica can quantitatively reveal the basic characteristics of Earth’s surface radiation balance and validate satellite data for the Antarctic region.The fixed station was established in 1989,and conventional radiation observations started much later in 2008.In this study,a random forest (RF) model for estimating DGSR is developed using ground meteorological observation data,and a highprecision,long-term DGSR dataset is constructed.Then,the trend of DGSR from 1990 to 2019 at Zhongshan Station,Antarctica is analyzed.The RF model,which performs better than other models,shows a desirable performance of DGSR hindcast estimation with an R^2 of 0.984,root-mean-square error of 1.377 MJ m^(-2),and mean absolute error of 0.828 MJ m^(-2).The trend of DGSR annual anomalies increases during 1990–2004 and then begins to decrease after 2004.Note that the maximum value of annual anomalies occurs during approximately 2004/05 and is mainly related to the days with precipitation (especially those related to good weather during the polar day period) at this station.In addition to clouds and water vapor,bad weather conditions (such as snowfall,which can result in low visibility and then decreased sunshine duration and solar radiation) are the other major factors affecting solar radiation at this station.The high-precision,longterm estimated DGSR dataset enables further study and understanding of the role of Antarctica in global climate change and the interactions between snow,ice,and atmosphere.

Trend Analysis of Large-Scale Twitter Data Based on Witnesses during a Hazardous Event: A Case Study on California Wildfire Evacuation

Social media data created a paradigm shift in assessing situational awareness during a natural disaster or emergencies such as wildfire, hurricane, tropical storm etc. Twitter as an emerging data source is an effective and innovative digital platform to observe trend from social media users’ perspective who are direct or indirect witnesses of the calamitous event. This paper aims to collect and analyze twitter data related to the recent wildfire in California to perform a trend analysis by classifying firsthand and credible information from Twitter users. This work investigates tweets on the recent wildfire in California and classifies them based on witnesses into two types: 1) direct witnesses and 2) indirect witnesses. The collected and analyzed information can be useful for law enforcement agencies and humanitarian organizations for communication and verification of the situational awareness during wildfire hazards. Trend analysis is an aggregated approach that includes sentimental analysis and topic modeling performed through domain-expert manual annotation and machine learning. Trend analysis ultimately builds a fine-grained analysis to assess evacuation routes and provide valuable information to the firsthand emergency responders.

Site and Regional Trend Analysis of Precipitation in Central Macedonia, Greece

The purpose of this paper is to investigate the trend of precipitation in Kilkis region (Greece) at the site and regional level in various time scales. At the site level, the precipitation trend was analyzed using three tests: 1) Mann-Kendall, 2) Sen’s T and 3) Spearman while the trend slope was estimated using the Sen’s estimator. At a regional level, nonparametric spatial tests such as Regional Average Mann-Kendall (RAMK) and BECD’s (Bootstrap Empirical Cumulative Distributions) were elaborated with and without the effect of cross correlation. The trend of precipitation was noticed generally downward at annual time scale and statistically significant at 5% level of significance only in only one station. The results of the analysis of trends at the regional level showed in total the influence of cross correlation in the time series since the number of trends detected is reduced when cross correlation is preserved. Precipitation data from 12 stations were used. The study results benefit water resource management, drought mitigation, socio-economic development, and sustainable agricultural planning in the region.

Dynamic trend analysis on relational effect of environmental protection industry in China

EPI （environmental protection indastry） and three industries constitute aur national economic structuse. By Grey System Theory and correlation effect analytical method for the first time, this paper analyzes the relatioaship degree between environmental protection industry and the three causes including industries involved in China in both qualitative and quantitotive aspects. Both the innate tale and the realistic reasons nf the relational degree are further analyzed by utilizing sastninoble development theory, circulating economy theol., ecological equilibrium theory, externality theory. industrial structure theory, and ecology prinrity rules. From all the analysts, this paper reveals the relationship between EPI and three industries. In addition, it offers suggestions to the feasibility of adjusting the industrial structure and developing the environmental protection industry in our country.

Trend Analysis of the Research on Construction Grammar in CSSCI Journals from 2010 to 2020

This study aims at analyzing the tendency and change in the research on construction grammar from 2010 to 2020.Descriptively,this study includes the publication year,research topic,research direction,research content,and the research methods.Twenty-four CSSCI journals were selected as the research samples using the keyword–“Construction Grammar.”The research topics mainly include Chinese construction research,foreign language construction research,and comparative studies on Chinese and other language constructions.The results showed that there are many Chinese construction research,but the other two research topics still require improvement.Ontology research was the main focus;acquisition research and teaching research are worthy for further exploration.Case studies and theoretical studies were the most concerned contents,whereas studies on language acquisition,pedagogy,and corpus construction were feeble.Qualitative description and theoretical review were the most popular methods,while empirical,quantitative,and diachronic analyses were less frequently used.After analyzing the trends,it has been predicted that the research on construction grammar would continue to heat up in the future,and there would be more research directions and contents along with diversified research methods.

Analysis and prediction of glacier evolution trend(2020-2100)in Northern Xinjiang

Glaciers,as“solid reservoirs”,are precious resources in arid areas.The study of glaciers is of great significance to the sustainable development and management of agriculture and the economy in northern Xinjiang.The area of glacier distribution on the 1963 topographic map data,1975 MSS data,2000 ETM data,2008 CBERS-2 data,2014 and 2018 ETM+were collected as secondary data.According to the remote sensing survey,the glacier areas in Northern Xinjiang are identified during 1963-2018.Based on the evolution of glacier area in the past 55 years,and using two scenarios,the average annual decrease area of a region during the whole 1963-2018 and the period with the minimum reduction area,the glacier areas of Southern Tianshan Mountains,Western Tianshan Mountains,Eastern Tianshan Mountains,the Sawuer Mountains and Altai Mountains in Northern Xinjiang,and the whole northern Xinjiang in 2030,2040,2050,and 2100 are examined and predicted.In 2100,the glacier area in Northern Xinjiang may decrease by 43%-59%.

Analysis of Changing Trend of Summer Precipitation in North China

Based on the reanalysis data of the National Center for Environmental Prediction(NCEP)and the precipitation dataset of the U.S.Climate Prediction Center(CPC),the changing trend of summer precipitation in North China(35°-40°N,110°-125°E)during 1979-2020 was studied.By calculating the monthly climatic precipitation in North China,it is found that precipitation was mainly distributed from June to August,so the trend of precipitation in North China from June to August was mainly analyzed.Firstly,the five-point moving average of regional mean precipitation in North China from June to August during 1979-2020 was conducted.It is found that the fitting curve of the five-point sliding average was basically consistent with the changing trend of regional precipitation,and it showed a certain upward trend.Secondly,the cumulative anomaly of regional average summer precipitation in North China showed a significant upward trend after 2005,which was similar to the moving average result,indicating that the precipitation in the later period increased compared with the earlier period.The changing trend of summer precipitation in North China in the past 42 years was analyzed,and the results show that precipitation showed a significant increasing trend in most areas of North China,so that regional average precipitation also tended to increase significantly.By comparing the precipitation in the past five years(2016-2020)and the last 36 years(1979-2015),it is found that the increase of summer precipitation in North China was more obvious,so the reasons for the increase in precipitation were further analyzed.Since the occurrence of precipitation requires favorable thermal dynamic conditions,the one-dimensional linear regression of water vapor content at 850 hPa and meridional wind speed was conduced,and it is found that the two variables tended to increase obviously,which was consistent with the increasing trend of precipitation.Seen from both the results of regional average and the spatial distribution of trends,the lower atmospheric water vapor content and wind speed showed a significant positive trend,which led to the increase of summer precipitation.Therefore,it can be concluded that there was a certain changing trend of summer precipitation in North China in the past 42 years,which can provide certain reference for the future forecast of summer precipitation in North China.

Trend analysis of noncommunicable diseases and their risk factors in Afghanistan

Background:Afghanistan is suffering from 40-year chronic conflicts,displacement,and demolition of its infrastructure.Afghanistan mortality survey 2010 shows nearly 46%of all deaths in the country were attributed to noncommunicable diseases(NCDs).In this study,we aimed to understand the differences in mortality and premature death due to NCDs by sex and the trend for the next 8 years.Methods:We applied trend analysis using the secondary data from the Institute for Health Metrics and Evaluation,Global Burden of Diseases 2019.The information on NCD mortality,NCD deaths attributed to its risk factors,NCD percent of total years lived with disability(YLDs)attribution to each risk factor extracted from this database from 2008 to 2019.We investigated the trend from 2008 to 2019 for the mentioned factors and then forecast their trends until 2030.Results:Our study shows that Afghanistan has had an increasing death number due to NCDs from 2008 to 2019(50%for both sexes)and this will reach nearly 54%by 2030.Currently,half of NCDs deaths are premature in Afghanistan.The mortality rate and prevalence of risk factors are higher among women.More than 70%of YLDs will be due to NCDs in Afghanistan till 2030.Five risk factors including high systolic blood pressure(28.3%),high body mass index(23.4%),high blood glucose(20.6%),high low-density lipoprotein cholesterol(16.3%),and smoking(12.3%)will have the highest contribution to NCDs death in 2030,respectively.Conclusions:In general,our study indicates that without any specific intervention to address NCDs in Afghanistan,not only the Sustainable Development Goal target for NCDs will not be met,but an increase in almost all risk factors prevalence,as well as NCD mortality,will be seen in Afghanistan.

Effects of temperature and precipitation on drought trends in Xinjiang, China

The characteristics of drought in Xinjiang Uygur Autonomous Region(Xinjiang),China have changed due to changes in the spatiotemporal patterns of temperature and precipitation,however,the effects of temperature and precipitation—the two most important factors influencing drought—have not yet been thoroughly explored in this region.In this study,we first calculated the standard precipitation evapotranspiration index(SPEI)in Xinjiang from 1980 to 2020 based on the monthly precipitation and monthly average temperature.Then the spatiotemporal characteristics of temperature,precipitation,and drought in Xinjiang from 1980 to 2020 were analyzed using the Theil-Sen median trend analysis method and Mann-Kendall test.A series of SPEI-based scenario-setting experiments by combining the observed and detrended climatic factors were utilized to quantify the effects of individual climatic factor(i.e.,temperature and precipitation).The results revealed that both temperature and precipitation had experienced increasing trends at most meteorological stations in Xinjiang from 1980 to 2020,especially the spring temperature and winter precipitation.Due to the influence of temperature,trends of intensifying drought have been observed at spring,summer,autumn,and annual scales.In addition,the drought trends in southern Xinjiang were more notable than those in northern Xinjiang.From 1980 to 2020,temperature trends exacerbated drought trends,but precipitation trends alleviated drought trends in Xinjiang.Most meteorological stations in Xinjiang exhibited temperature-dominated drought trend except in winter;in winter,most stations exhibited precipitation-dominated wetting trend.The findings of this study highlight the importance of the impact of temperature on drought in Xinjiang and deepen the understanding of the factors influencing drought.

Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Trend analysis of cancer incidence and mortality in China

The National Central Cancer Registry of China （NCCRC） up- dated their nationwide statistics of cancer incidence and mor- tality in China according to 2013 population-based cancer registration data （due to the time required for data collection, quality control and analysis, the latest cancer statistics avail- able in China have a 3-year lag behind the current year）.