Trend Analysis Method Research Articles

The Spatio-Temporal Patterns of Regional Development in Shandong Province of China from 2012 to 2021 Based on Nighttime Light Remote Sensing.

As a major coastal economic province in the east of China, it is of great significance to clarify the temporal and spatial patterns of regional development in Shandong Province in recent years to support regional high-quality development. Nightlight remote sensing data can reveal the spatio-temporal patterns of social and economic activities on a fine pixel scale. We based the nighttime light patterns at three spatial scales in three geographical regions on monthly nighttime light remote sensing data and social statistics. Different cities and different counties in Shandong Province in the last 10 years were studied by using the methods of trend analysis, stability analysis and correlation analysis. The results show that: (1) The nighttime light pattern was generally consistent with the spatial pattern of construction land. The nighttime light intensity of most urban, built-up areas showed an increasing trend, while the old urban areas of Qingdao and Yantai showed a weakening trend. (2) At the geographical unit scale, the total nighttime light in south-central Shandong was significantly higher than that in eastern and northwest Shandong, while the nighttime light growth rate in northwest Shandong was significantly highest. At the urban scale, Liaocheng had the highest nighttime light growth rate. At the county scale, the nighttime light growth rate of counties with a better economy was lower, while that of counties with a backward economy was higher. (3) The nighttime light growth was significantly correlated with Gross Domestic Product (GDP) and population growth, indicating that regional economic development and population growth were the main causes of nighttime light change.

Water productivity maximization and ecosystem monitoring to estimate tourism economic value

Abstract Water supply from a common pool resource based on productivity indicators for different uses is one of the goals of planning in dry areas. Productivity indicators are defined based on time, geographical location and hydrological conditions in the form of food security, economic benefits and ecosystem restoration. This study was conducted in order to evaluate the contrast between economic criteria and food security in the exploitation of water resources in Lu'an city in Anhui province of China. Probabilistic modeling based on the prediction of uncertain values using the Latin hypercube technique was used for hydrological variables and water resources. The method of data mining and trend analysis of dependent variables was also simulated to estimate economic values in the water cycle. Statistical information of 32 years from 1991 to 2022 has been collected and used as an annual average per population. The results showed that the economic value of water consumption in the tourism industry has increased compared to agriculture. The total water provided for food security is equal to 6.5 m3 per person, the excess of which can be allocated to other uses through weighting indicators based on ecosystem and quality.

Reference System Element Identification Atlas – methods and tools to identify references system elements in product engineering

Companies target innovations, successful new products. One major challenge is to increase efficiency and decrease the risk of developing new successful products. We want to reach these goals by improving the reusability of already existing knowledge elements extracted from e.g., already existing (sub-)systems or their documentation. These elements are called reference system elements and are meant to be the starting point for product development projects. Based on a systematic literature review complemented by an expert workshop and analysis of established methods and tools in product engineering, we developed the Reference System Elements Identification Atlas to support the identification of suiting reference system elements. Within the Reference System Elements Identification Atlas, we collected 30 methods and tools to identify reference system elements and allocated them to the various knowledge spaces they search. All 30 methods and tools were grouped in five clusters – creativity methods, data analysis methods, market/competition analysis methods, similarity methods, and trend analysis methods. We observed that methods and tools are hardly related to the identification of reference system elements in literature explicitly. We believe the Reference System Elements Identification Atlas provides valuable support to collect valuable reference system elements as the starting point in product engineering.

Gender Inequality in Higher Education and Research

Significant economic and social differences in the living and working conditions of men and women, structural changes in society actualize the need to research the prerequisites and consequences of the existence of gender inequality in the country. The purpose of the paper is to investigate the causes and nature of gender inequality in the long term. The object of the research is the sphere of education and science of certain countries of Europe and America, Southeast Asia, the Middle East and North Africa. The main hypothesis of the study is the assumption of a relationship between gender inequality in the field of education and indicators of the country’s social development (Human Development Index and level of education). Methodological tools of the conducted research are methods of trend and structural analysis. The information base of the research is data from the Organization for Economic Cooperation and Development, the World Economic Forum, and the United Nations, the research period is 1950-2021. The results of the analysis of the Gender Equality Index during 1950-2000 in terms of its four dimensions (health, socio-economic resources, gender disparity in households and gender disparity in politics) proved the presence of a significant gender gap in some countries of the world: the countries of Eastern and Western Europe are more developed compared to other regions of the world (South and Southeast Asia, the Middle East and North Africa). According to the results of empirical calculations, the dependence between the level of human development and gender inequality has been proven: the higher the level of human development of the country, the lower the inequality in education. The study of gender inequality in the field of scientific research was carried out based on the analysis of publications in 50 international journals, book collections of Bengal Economic Association, Indian Economic Association and other professors of reputed institutions in India and abroad. Based on the results of the analysis, it was concluded that the publishing activity of women is lower than that of men: only 22.07% of publications in national and international journals, 23.65% of volumes of book collections and 27.90% of book chapters were published by women. The reasons for the low activity of women in the field of scientific research include: low opportunities for visiting the sites of scientific research institutions, field surveys or laboratory work; limited opportunities for training and advanced training at seminars and classes; lack of time to carry out research activities; discrimination based on personal interests and gender bias; much less interest in regular research due to social, psychological and physical reasons; excessive family load, etc.

Trend Analysis of Civil Aviation Incidents Based on Causal Inference and Statistical Inference

The efficient management of aviation safety requires the precise analysis of trends in incidents. While classical statistical models often rely on the autocorrelation of indicator sequences for trend fitting, significant room remains for performance improvement. To enhance the accuracy and interpretability of trend analyses for aviation incidents, we propose the Causal-ARIMA model, which is grounded in causal inference theory, and we employ four distinct modeling strategies to fit the trend of incidents in China’s civil aviation sector between 1994 and 2020. The objective is to validate the performance of the Causal-ARIMA model and identify optimal trend analysis strategies. The four modeling strategies account for causation factors, stationarity, and causality with operational volume, incorporating models like AR, ARMA, ARIMA, and Causal-ARIMA. Our findings reveal that ensemble techniques incorporating the Causal-ARIMA model (Strategy 2 and 3) outperform classical trend analysis methods (Strategy 1) in terms of model fit. Specifically, the causality-based binary fitting technique (Strategy 3) achieves the most uniformly dispersed fitting performance. When the premises for using the Causal-ARIMA model are relaxed, applying it to variables without Granger causal relationships results in uneven model performance (Strategy 4). According to our study, the Causal-ARIMA model can serve as a potent tool for the analysis of trends in the domain of aviation safety. Modeling strategies based on the Causal-ARIMA model provide valuable insights for aviation safety management.

Spatial−temporal variation of ecological environment quality and driving factors from 2000 to 2020 in Wuliangsu Lake Basin, Northern China

Due to global climate change and the intensification of human activities, the ecological function of Wuliangsu Lake Basin has been seriously degraded. Obtaining accurate spatial–temporal dynamics of regional ecological environment quality is essential for the evaluation of ecological management and restoration effects. This study assessed the trend changes and drivers of the Remote Sensing Ecological Index (RSEI) in the Wuliangsu Lake Basin from 2000−2020. Firstly, the trend analysis method and hurst index were used to analyze the temporal and spatial variation of RSEI. Then the main factors of RSEI variation were analyzed using meteorological data, integrated nighttime lighting data, and population density data. Overall, the RSEI shows an increasing trend from the west to the east with a rate of 0.0034 year−1 over the last 21 years. The area change of RSEI was 54.22%, 63.80% and 52.43% for 2000−2006, 2007−2013 and 2014−2020, respectively, which indicates that most areas have a stable ecological environment. However, the overall Future Improvement Trend (FIT) area of RSEI is 42.21%, mainly in Dengkou area, Urad Qianqi and central area. This indicates that the RSEI remains stable locally and shows an overall improving trend. The results of the correlation analysis showed that the areas influenced by meteorological and human factors were highly coincident, mainly in Dengkou and northern Linhe areas and Urad Qianqi. Considering the lagging effect of ecological engineering, the sustainable development status of RSEI in the western and eastern regions will maintain an improving trend in the future. Our study confirms the complex relationship between RSEI and meteorological and human activities, which is crucial for the scientific management of watershed ecosystems under the influence of anthropogenic factors.

Impacts of Extreme-High-Temperature Events on Vegetation in North China

Understanding the response of vegetation to temperature extremes is crucial for investigating vegetation growth and guiding ecosystem conservation. North China is a vital hub for China’s economy and food supplies, and its vegetation is highly vulnerable to complex heatwaves. In this study, based on remote sensing data, i.e., the normalized difference vegetation index (NDVI), spatio-temporal variations in vegetation and extreme high temperatures are investigated by using the methods of trend analysis, linear detrending, Pearson correlation and ridge regression. The impacts of extreme-high-temperature events on different vegetation types in North China from 1982 to 2015 are explored on multiple time scales. The results indicate that the NDVI in North China exhibits an overall increasing trend on both annual and monthly scales, with the highest values for forest vegetation and the fastest growth trend for cropland. Meanwhile, extreme-high-temperature events in North China also display an increasing trend. Before detrending, the correlations between the NDVI and certain extreme-high-temperature indices are not significant, while significant negative correlations are observed after detrending. On an annual scale, the NDVI is negatively correlated with extreme temperature indices, except for the number of warm nights, whereas, on a monthly scale, these negative correlations are only found from June to September. Grassland vegetation shows relatively strong correlations with all extreme temperature indices, while forests show nonsignificant correlations with the indices. This study offers new insight into vegetation dynamic variations and their responses to climate in North China.

The Effect of COVID-19 on Chinas Real Estate Market via Different Angles

The trend of the real estate industry has become a hot topic of concern in contemporary society, and some studies have shown that after the epidemic, real estate has been conducted. The profitability of enterprises has declined significantly since there are many different opinions. This article aims to find the reasons from the three different perspectives of home buyers, housing enterprises, and governments based on the feature analysis method. The trend analysis method investigates the sales and pending sales of real estate products in the country. According to the analysis, real estate has indeed been on a downward spiral in recent years. The buyer does not have sufficient funds to buy a house. The cash flow of housing enterprises is also extremely tight, and in the year of the outbreak of the new crown epidemic, the volume of sales almost fell exponentially. Governments also need to continue to issue policies in a changing economic environment spectator control. In summary, China's real estate is still full of difficulties. These results shed light on guiding further exploration of real estate market.

Modern paradigm of personnel management system of the transport industry

Methods. The scientific foundations of the research are general scientific theories – recognized concepts of enterprise personnel management; classification and analytical method – in the process of clarifying the constituent elements of personnel development, specifying the content of personnel technologies, researching the factors of employee activity activation. The used methods of statistical and trend analysis made it possible to identify trends and factors in the formation of the personnel management paradigm at domestic enterprises Results. The dominant trends of changes in personnel management of a modern enterprise are singled out: active use of HR technologies; transferring the implementation of individual business processes to external executors under outsourcing conditions; building new career models; automation of HR processes; formation of learning culture; taking into account changes in the labor market during personnel management. It has been demonstrated that traditional personnel management systems are transformed today into talent management, training and development of creative and intellectual activity of personnel. Employees who have a well-developed intuition, a sufficient level and set of knowledge, skills and abilities become a key factor in the success of the enterprise in the modern conditions of the digital world. Novelty. The specifics of effective personnel technologies in the field of personnel management of enterprises in the transport industry are summarized and the feasibility of their application to increase the competitiveness of companies in modern conditions of a radical change in the business paradigm is substantiated. Practical value consists in the possibility of applying the provided proposals regarding personnel management of transport industry enterprises, in particular, regarding their introduction of progressive personnel technologies using elements of the digital economy to increase the efficiency of economic activity in conditions of uncertainty. New personnel management systems are supposed to ensure the mobility of all company employees, sociality, knowledge and people management and, as a result, change the organizational structure, culture, perception of changes, transformation of personnel competencies and the management system as a whole.

Spatiotemporal characterization of relative humidity trends and influence of climatic factors in Bangladesh

The frequency and intensity of climate change and resulting impacts are more prevalent in South Asian countries, particularly in Bangladesh. Relative humidity (RH) is a crucial aspect of climate, and higher RH variability has far-reaching impacts on human health, agriculture, environment, and infrastructure. While temperature and rainfall have gained much research attention, RH studies have received scant attention in the research literature. This study investigated the trends and variability of RH levels in Bangladesh and the influence of other meteorological factors over the past 40 years. Variabilities in the meteorological factors were identified by calculating descriptive statistics. Innovative trend analysis (ITA) and Mann-Kendall test (MK-test) methods were utilized to assess monthly, seasonal, and annual trends. The magnitude of temperature, rainfall, and windspeed influences on RH variability were identified using Pearson's correlation, Spearman rank correlation, and Kendall correlation model. Variability analysis showed higher spatial variations in RH levels across the country, and RH skewed negatively in all stations. Results reveal that daily, monthly, seasonal, and annual trends of RH exhibited positive trends in all stations, with an increasing rate of 0.083–0.53% per year in summer, 0.43–0.68% per year in winter, and 0.58–0.31% per year in the rainy season. Both ITA and MK-test provided consistent results, indicating no discrepancies in trend results. All three models indicate that temperature, rainfall, and windspeed have weak to moderate positive influences on changing RH levels in Bangladesh. The study will contribute to decision-making to improve crop yields, health outcomes, and infrastructure efficiency.

Evolution pattern and driving mechanism of eco-environmental quality in arid oasis belt — A case study of oasis core area in Kashgar Delta

Kashgar Oasis is an ecologically fragile area in the southern margin of the Tarim Basin, which is affected by both natural conditions and human activities. Exploring the spatiotemporal dynamics and driving factors of ecological environment quality in this area is significant for maintaining regional ecological security and ecological protection. This study aims to examine the multi-year RSEI, calculated based on the GEE platform from 1990 to 2020 in the study area, located in the core area of the Oasis. The trend analysis method analyzed the spatiotemporal pattern of RSEI and dynamic evolution. Additionally, the regularity of migration directions was explored through gravity transfer and the linear directional mean. Finally, the driving forces factors were quantified by geographic detectors. The results showed that: (1) The ecological environment quality of the study area showed an increasing trend from 1990 to 2020, with the mean value of RSEI increasing from 0.542 to 0.577, an overall increase of 6.84%. (2) The improved and stable areas account for 60.901% and 5.428%, respectively, and the improved areas were mainly distributed in a large area, while the degraded area was mainly mildly degraded and had a patchy structure. (3) The change direction of different grades showed an east–west extension trend, with areas of significant improvement and slight degradation being more aligned with river flow. (4) The results showed that land use and land cover (LULC), representing human activities, had the most significant explanatory power, and the q-value of single factor detection and interaction detection of LUC-GDP were 0.506 and 0.550, respectively. This indicated that the fluctuations of eco-environmental quality in this area are closely related to the local land use patterns. This study can provide a reference for implementing local ecological environment protection and environmental restoration projects.

Порівняння потужності критеріїв наявності тренду в часових рядах

The subject of research is methods, mathematical models, and methods of continuous analysis of a multidimensional set of output variables and state variables of power and energy installations built on the basis of gas turbine engines, which in general constitute time series. The purpose of this work is to establish the power of trend and randomness criteria by statistical modeling of time series with a linear trend and the use of known trend and randomness statistics to establish their empirical distributions and operational characteristics for comparing trend criteria by their power. The tasks faced by the developers were to determine the empirical distributions of known parametric and non-parametric trend statistics when applying the linear trend model in superposition with a random component, and set the level of errors of the first kind (false solution), with a given level of errors of the second kind (false anxiety). The methods that were used to achieve the established goal of the research: general methods of trend analysis, methods of applied statistics, and methods of conducting computer experiments. The results of the research provide a rationale for the approach to establishing the power of known criteria of trend and randomness. The limitation of the known methods of applied statistics is that it is theoretically only possible to refute the hypothesis regarding the randomness of the initial data at a certain level of significance, which determines the level of errors of the second kind (false alarms). Establishing the level of errors of the first kind (wrong decision) poses significant difficulties, because in the presence of a trend, the time series can no longer be stationary. But it is the statistical level of such errors that actually determines the strength of the criteria for the presence of a trend in the time series. The resolution of this contradiction is proposed by means of statistical modeling of time series with a linear trend and the use of well-known trend and randomness statistics to establish their empirical distributions and operational characteristics and to compare trend criteria according to their power. Statistical modeling was performed for a number of trend and randomness statistics, namely: the most common parametric statistics: correlation criterion and its modifications, Fisher's criterion, and Student's criterion; and non-parametric Wald-Wolfowitz criteria; Bartles; as well as the inversion criterion. According to the results of statistical modeling, it was established that the Student's criterion is the most powerful of the parametric criteria, and the inversion criterion is the most powerful of the non-parametric criteria. It is understood that such conclusions are valid when the assumptions regarding the initial statistical model of data generation in the form of a superposition of a linear trend and a random component as a sample from the general population of independent and normally distributed random variables and the corresponding algorithm for processing time series counts for the formation of decisive statistics are fulfilled. The scientific novelty of the obtained results lies in the fact that for the first time, the issue of comparing the power of parametric and non-parametric criteria of trend and randomness with respect to the applied model of data generation in the form of a linear trend in superposition with a random component was considered. The practical significance of the obtained results lies in the fact that the research results make it possible to choose an appropriate criterion based on its power for solving applied tasks of monitoring the technical condition of power and energy installations built on the basis of gas turbine engines.

ANALISIS VOLUME PENJUALAN PRODUK BENIH PADI UNGGUL DI PT. PERTANI (PERSERO) SEMARANG, JAWA TENGAH

This research aimed to perceive the trend of sales volume and to analyze the correlation of sale’s factors with prime rice seed sales volume in PT. Pertani (Persero) Semarang in 2016-2020. This research was conducted at PT. Pertani (Persero) Semarang, Central Java. The locus of this research was chose using purposive sampling method. This research used case study as a research method where researcher did the research intensively, deeply, and detailed about the sales of prime rice seed in PT. Pertani (Persero) Semarang. Primary data was collected from an interview with PT. Pertani (Persero) Semarang’s employees. Secondary data including monthly production report, monthly sales report, marketing report of prime rice seed product at PT. Pertani (Persero) Semarang was collected through a time series method for 5 consecutive years from 2016-2020. Data was analized with trend analysis and pearson correlation method. The result of trend analysis shows a positive trend of prime rice seed sales volume in 2016-2020. The result of pearson correlation analysis shows that prices and marketing expenses are strongly correlated.

Enhancing groundwater management using aggregated-data analysis and segmented robust regression: A case study on spatiotemporal changes in water quality

Groundwater quality management, crucial for ensuring sustainable water resources and public health, is the scope of this study. Our objective is to demonstrate the significance of secondary data analysis for the spatiotemporal characterization of groundwater quality. To this end, we develop and employ a robust trend analysis method, in tandem with a spatiotemporal data aggregation method, to accurately identify shifts in groundwater quality over time, even in the face of inflection points or breakpoints. The methods and results reveal diverse trends and characteristics in water quality over space and time across the entire dataset from selected regions in South Korea, emphasizing the importance of analyzing aggregated data beyond individual business locations. The conclusions indicate that this study contributes to the development of more reliable and effective groundwater quality management strategies by addressing gaps in traditional monitoring methods and the challenges of limited monitoring resources and uneven data quality. Future research directions include the application of the developed methods to other regions and data sources, opening avenues for further advances in groundwater quality management.

Long-Term Trends of Astroclimatic Parameters above the Terskol Observatory

Astroclimatic conditions characterize the quality of an astronomical site. The Terskol Observatory was founded over 42 years ago in 1980. The astronomical site (coordinates 43°16′29″ N, 42°30′03″ E) is located about 10 km from Mt. Elbrus in the northern Caucasus Mountains. The paper presents the results of an analysis of long-term variations from 1980 to 2022 of astroclimatic parameters such as total cloud cover, precipitable water vapor, and wind speed at a level of 200 hPa above the Terskol Observatory using atmospheric ERA5 Reanalysis data from the European Center for Medium-Range Weather Forecast. The probability distributions and seasonal variations of the astroclimatic parameters are also presented. Long-term trends of the astroclimatic parameters are studied with statistically significant trend analysis methods using the Mann–Kendall test and the Sen’s slope test to estimate the magnitude of the changes. The results show non-significant decreases of annual average 200-hPa wind speed and increases in precipitable water vapor, but significant (99 per cent confidence level) long-term decreasing of total cloud cover above the Terskol Observatory.

Trends in Extreme Precipitation Indices in Northwest Ethiopia: Comparative Analysis Using the Mann–Kendall and Innovative Trend Analysis Methods

This study analyzed long-term extreme precipitation indices using 4 × 4 km gridded data obtained from the National Meteorological Agency of Ethiopia between 1981 and 2018. The study examined trends in extreme precipitation over three districts (Lay Gayint, Tach Gayint, and Simada) in the northwestern highlands of Ethiopia. Innovative Trend Analysis (ITA) and Mann–Kendall (MK) trend tests were used to study extreme precipitation trends. Based on the ITA result, the calculated values of nine indices (90% of the analyzed indices) showed significant increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 70% (seven indices) showed significantly increasing trends at p < 0.01. On the other hand, 60% of the extreme indices showed significant downward trends (p < 0.01) in Simada. The MK test revealed that 30% of the extreme indices had significantly increasing trends (p < 0.01) in Lay Gayint. In Tach Gayint, 30% of the extreme indices showed significant increasing trends at p < 0.05, while 10% of the extreme indices exhibited significant increasing trends at p < 0.01. In Simada, 20% of the extreme indices showed significant increasing trends at p < 0.05. Overall, the results showed that the ITA method can identify a variety of significant trends that the MK test misses.

Simulasi Pinjaman Daerah sebagai alternatif pilihan Pembiayaan Pembangunan Infrastruktur di Kabupaten Batang Hari

Regional Loans are one of the alternative sources of financing in the Regional Revenue and Expenditure Budget to fund activities that are initiatives of the Regional Government in the framework of Local Government affairs based on the provisions of laws and regulations. Regional loans can be used to finance infrastructure and/or investment in regional infrastructure and facilities in the framework of public services. In addition, Regional Loans can also be used to cover regional cash flow. This study aims to determine the financial capability of the Batang Hari Regency Government and determine the number of feasible loans if the Batang Hari Regency Government makes regional loans as an alternative to financing infrastructure development. The data used in this study is secondary time series data derived from the Batang Hari Regency Government Budget Realization Report for the 2017-2021 period. The analysis tools used are the ratio of regional financial ability to repay loans with the Debt Service Coverage Ratio (DSCR), the Maximum Loan Limit (BMP) and to determine the amount of loans that can be made by regions in 2017-2021 by calculating regional revenue plans and regional spending plans, which are carried out using the Trend analysis method. Based on the simulation result conducted, the Batang Hari Regency Government has a Debt Service Coverage Ratio (DSCR) value of 4.81 which exceeds the minimum standard set at 2.5. The results of the analysis also show a Maximum Loan Limit of Rp. 740,070,216,978. Based on data obtained in fiscal year 2021. When viewed from the projection results, the loan that can be obtained by the Regional Government of Batang Hari Regency according to the analysis of the BMP Maximum Loan Limit in 2022 is IDR 706,263,200,215. Net funds are obtained from the projected results for 2022 of Rp. 503,718,603,808 and the maximum installments that can be prepared are Rp. 201,487,441,523.

COMPARISON OF INNOVATIVE TREND ANALYSIS METHODS FOR HYDROMETEOROLOGICAL PARAMETERS IN THE KARASU SUB-BASIN

Türkiye, which has a complex climate structure, is shown among the countries that will be most affected by climate change with the effect of global warming. These effects will differ in different regions due to their topographic structure, location, and orographic characteristics. Trend analyzes are used to determine the direction and magnitude of this variability. In this study, trend analysis was carried out by using hydrometeorological data obtained from streamflow and meteorology stations located in the Karasu Sub-Basin located in the Euphrates-Tigris Basin. Three innovative trend methods, namely the Şen-Innovative Trend Analysis, Onyutha Trend Test, Combination of Wilcoxon Test and Scatter Diagram trend tests, were used together with the classical Mann-Kendall method in the monthly scale analysis of hydrometeorological data of the 1979-2020 period. Both graphical and statistical trend analysis can be done with innovative methods. The results obtained in the study, in which trend analyses were evaluated at the α=0.05 significance level, reveal significant and insignificant decreasing trends in the parameters of mean streamflow, maximum precipitation, total precipitation, mean and minimum relative humidity. Significant and insignificant increasing trends were determined in the maximum, minimum, and mean temperature, maximum relative humidity, and mean wind speed data. The trends obtained in the methods used in general are consistent with each other. The findings of this study could lead to a better knowledge of the region's hydrology and contribute sustainable water management. The trend analysis methods used in the study are thought to be quite helpful in the analysis of hydro-meteorological time series.

Quantitative analysis of spatiotemporal changes and driving forces of vegetation net primary productivity (NPP) in the Qimeng region of Inner Mongolia

Vegetation is an essential component of terrestrial ecosystems, and understanding the drivers of vegetation change is of great importance for ecological management. In recent years, vegetation growth has increased under the combined effect of global warming and human activities in Inner Mongolia. The net primary productivity (NPP) was used as an indicator to study the spatial and temporal changes in vegetation in the Qimeng Region (QR). The residual trend analysis method was used to analyze the relative contributions of climate variations (CV) and human activities (HA) to NPP changes across the QR, while their drivers were explored using a geographical detector approach to quantify the driving forces of NPP. The results show that (1) NPP exhibited a fluctuating growth trend from 2003 to 2020, with an overall growth rate of 2.91%/year. (2) Precipitation, GDP and population density were the dominant driving factors for the spatial distribution of NPP. The combined explanatory power of any two dominant factors exceeded the power of any dominant individual factor, and the interaction between climate and human factors had a significant effect on NPP. (3) The change in NPP was influenced by the combined effect of HA and CV, accounting for 37.69% of the total area, with the relative contribution of HA being 51.75%. Finally, the relative contribution of human activities was slightly higher than that of climate change, confirming the initial success of the Grain to Green Program as well as ecological conservation projects. This paper provides a scientific basis for the local government to carry out the conversion of cropland to forest.

Dataset Analysis of the Risks for Russian IT Companies Amid the COVID-19 Crisis

The motivation for this research was to strive towards specifying the risks for businesses under the conditions of the COVID-19 pandemic and crisis in the IT sector in Russia. This paper is aimed at performing a dataset analysis of the risks for Russian IT companies amid the COVID-19 crisis. The sample contains the top 100 largest IT companies in Russia in 2020 and covers the data on these companies for 2019–2020. The influence of the COVID-19 crisis pandemic on the risks for IT companies in Russia is assessed with the help of the authors’ methodological approach to the dataset analytics of companies’ risks with the use of the method of trend analysis, analysis of variance and the hierarchical synthesis concept by T. Saaty. A specific feature of the authors’ methodological approach is its taking into account of the pre-crisis level of risks for companies. Due to this, the authors’ methodological approach allows for the most precise and correct determination of the scale and character of the influence of the COVID-19 pandemic and crisis on the risks for companies. The role of human resources in the management of risks for IT companies under the conditions of the COVID-19 pandemic and crisis in Russia is determined with the help of regression analysis; the regularity of the change in revenue, and the position of the company in the ranking (its competitiveness) in terms of the growth of the number of employees, are described mathematically. The key conclusions are that the influence of the COVID-19 pandemic and crisis on the risks for IT companies in Russia in 2020 was weak, and human resources played an important role in risk management. The theoretical significance of the paper lies in its rethinking of human resources management of Russian IT companies from the position of risk amid the COVID-19 crisis. The practical significance of the authors’ conclusions lies in the discovery of the high risk resilience of Russian IT companies to the pandemic and the formation of their risk profile amid the COVID-19 crisis, in which the main, though low, risk is the risk of reduction in competitiveness, whilst the risk of reduction in revenue is minimal.