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Sub-Saharan Africa (SSA) was colonised for about a century by the British, French and other European countries. Therefore, we examine these forms of colonisation on accounting development in Africa. We use a description-explanatory approach to show how three forms of colonisation have driven the development of accounting in Africa during and post-colonisation era. This paper defines driving forces during the colonisation period as ex-ante driving forces, and after independence, as ex-post driving forces. We identify among the ex-ante driving forces, governance, economic policy, education and language influenced accounting systems/practices, and they are still predominant. Regarding the ex-post, we found four ex-post driving forces that impact accounting in SSA, which supports the instrumental form of accounting colonisation. These four driving forces are foreign aid, foreign trade liberalisation, membership in international associations and prevalence of foreign ownership. This paper provides insights into how accounting practices have evolved in Africa and how colonisation has driven different accounting systems across the continent. Unlike prior studies, which are limited to pre or post-colonial eras, we provide an understanding of accounting development during the colonial and post-colonial era. Therefore, we demonstrate how colonisation still influences accounting development even after independence in many African countries.

In this paper, a robust wheel slip control system based on a sliding mode controller is proposed for improving traction-ability and reducing energy consumption during sudden acceleration for a personal electric vehicle. Sliding mode control techniques have been employed widely in the development of a robust wheel slip controller of conventional internal combustion engine vehicles due to their application effectiveness in nonlinear systems and robustness against model uncertainties and disturbances. A practical slip control system which takes advantage of the features of electric motors is proposed and an algorithm for vehicle velocity estimation is also introduced. The vehicle velocity estimator was designed based on rotational wheel dynamics, measurable motor torque, and wheel velocity as well as rule-based logic. The simulations and experiments were carried out using both CarSim software and an experimental electric vehicle equipped with in-wheel-motors. Through field tests, traction performance and effectiveness in terms of energy saving were all verified. Comparative experiments with variations of control variables proved the effectiveness and practicality of the proposed control design.

Changes in the cultural landscape provide essential evidence about the manner and intensity of the interactions between humans and nature. Czechia has a specific location in Central Europe. It is positioned at the crossroads of European landscape changes. These changes can be documented based on a unique database that shows the development of land use since the middle of the 19th century. In this study, we aimed to address the major processes of landscape change that occurred during four periods over the past 165 years, at the cadastral level on the territory of present-day Czechia. Further we identify and discuss proximate and underlying driving forces of the landscape changes. We used land use data from the year 1845, 1896, 1948, 1990, and 2010 that correspond to key events in Czech history. The major processes and intensity of landscape change were evaluated based on calculations of increases and decreases in land use classes between the first and last year of each examined period. The period 1845–1896 was the only period in which arable land increased, and the most recent period, 1990–2010, was the only period during which a grassing over process was recorded. Afforestation was recorded in all periods. The communist period was characterized by unified changes—urbanization, afforestation, arable land decrease, and landscape devastation. The post-communist period was, in some respects, beneficial to the landscape (e.g., grassing over and afforestation, particularly in mountain areas), but it also led to negative processes, such as strong urbanization and land abandonment. Such changes lead to landscape polarization. The landscape changes in Czechia during the period 1845–2010 reflect many important historical events in Europe. In our analysis, we demonstrate the essential impact of underlying drivers and also identify driving forces specific to the development of the Czech territory.

Implementation of the Grain for Green program (GGP) intensifies land use/cover change (LUCC) in the loess hilly-gully region. Clarifying the response of LUCC to the GGP and its driving forces are basic premises to implement the GGP more effectively for alleviating soil erosion in this region. This study analyzed the spatio-temporal characteristics of conversion of cultivated land to forest land and grassland in two study periods of 2000–2010 and 2010–2018. The transition matrix model and the dynamic degree model were utilized to explore changes among cultivated land, forest land, and grassland based on the remote sensing (RS) and monitoring data of land use in 2000, 2010, and 2018. Secondly, further detection on driving forces of increase of forest land and grassland was conducted through the logistic regression model. Fourteen driving factors were selected: the GGP, elevation, slope, population density, GDP per land area, distance to city, distance to residential area, etc. The results revealed that: (1) Area of cultivated land was mainly transferred to forest land and grassland during two study periods. The conversion of cultivated land to forest land and grassland occupied 21.48% and 68.01% of outward-transferring area of cultivated land from 2000 to 2010, and accounted for 13.26% and 74.3% from 2010 to 2018; (2) From the results of the logistic regression model, elevation, the GGP, annual mean temperature, slope III (6–15°), and GDP per land area were the main driving forces from 2000 to 2010. Moreover, the most prominent driving forces were the GGP, elevation, rural population density, slope III (6–15°), and soil pH from 2010 to 2018. The findings of this study can help us better understand the conversion of cultivated land to forest land and grassland under the GGP and provide a scientific basis to facilitate sustainable development of land resources in the study area.

The new kinetically limited linear driving force (KLLDF) model was assessed against the traditional LDF model in the prediction of twelve different ternary and quaternary experimental breakthrough curves. These breakthrough curves comprised mixtures of CO 2 , N 2 and CH 4 in He adsorbed on carbon molecular sieve MSC 3 K 172 and were conducted at various pressures (30, 50 and 100 psia) and at ambient temperature. The LDF and KLLDF models were implemented in the dynamic adsorption process simulator (DAPS) with the loading dependent LDF mass transfer coefficients and the single gas equilibrium adsorption isotherms measured independently with gravimetric uptake experiments. To make the comparison between the LDF and the KLLDF models as fair as possible, they utilized the same set of thermodynamic and kinetic parameters in DAPS, with no adjustments to any of them. Both the LDF and KLLDF models provided reasonable predictions of the experimental breakthrough curves and in-bed temperature histories, with general trends of no CH 4 uptake, gradual N 2 uptake and fast CO 2 uptake. However, the KLLDF model always provided better predictions, especially when CO 2 was present. The results revealed that the traditional LDF model led to depressed adsorbed phase loadings of CO 2 , thereby underpredicting its breakthrough time in all cases. This depression stemmed from the equilibrium loading in the LDF driving force of the LDF model depending on the gas phase partial pressure of each component outside the pore structure. In contrast, the KLLDF model corrects this issue by making the equilibrium loading in its LDF driving force dependent on the actual loading of each component inside the pore structure. In conjunction with the mixed gas extended Langmuir model, the KLLDF model is perhaps the more appropriate model to use instead of the LDF model for any multicomponent adsorbate-adsorbent systems, whether diffusion limited or not, since it reduces to the LDF model for systems that do not exhibit significant diffusional limitations.

The transformation of resource-exhausted urban land is an urgent problem for sustainable urban development in the world today. Obtaining the urban land use type and analyzing the changes in their land use can lead to better management of the relationship between economic development and resource utilization. In this paper, a residual-intelligent module network was proposed to solve the problems of low classification accuracy and missing objects edge information in traditional computer classification methods. The classification of four Landsat-TM/OLI images from 1993–2020 for Jiaozuo city (the first batch of resource-exhausted cities in China) was realized by this method. The results (overall accuracy was 98.61%, in 2020 images) were better than the comparison models (support vector machine, 2D-convolutional neural network, hybrid convolution networks; overall accuracy was 87.12%, 96.16%, 98.46%, respectively) and effectively reduced the loss of information on the edge of the ground objects. On this basis, six main land use types were constructed by combining field surveys and other methods. The characteristics and driving forces of spatial-temporal change in land use were explored from the aspect of social, economic and policy factors. The results showed that from 1993 to 2020 the cultivated land, forest land, water body and other land types in the study area decreased by 690.97 km2, 57.54 km2, 47.04 km2 and 59.43 km2, respectively. The construction land and bare land increased by 839.38 km2 and 15.57 km2, respectively. The transfer of land use types was mainly from cultivated land to construction land, with a cumulative conversion of 920.95 km2 within 27 years. The driving forces of land use in the study area were analyzed by principal component analysis (PCA) and regression analysis. The spatial-temporal evolution of land use types was affected by policy changes, the level of social development and the adjustment in the economy, industry and agriculture structure. The investment in fixed assets and per capita net income in rural areas were the top two influencing factors and their cumulative contribution rate was 94.62%. The findings of this study can provide scientific reference and theoretical support for land use planning, land reclamation in mining areas, ecological protection and sustainable development in Jiaozuo and other resource-exhausted cities in the world.

The article addresses physicians who work as group supervisors or mentors in a training program after having formally retired. The driving forces to continue to work are analyzed in terms of the development of existential meaning of work at a particular stage of the life cycle. We argue that a deeper understanding of the existential driving forces, that both cause physicians to accept post-retirement mentoring tasks and that is awakened and developed in this specific work, would contribute to a deeper understanding of why individuals continue working into old age. However, in political discussions of an extended working life, similar aspects tend to be disregarded. Understanding the existential driving forces that cause an individual to continue working after retirement may be crucial to comprehending how we can take advantage of the resources of the older workforce and, thus, realize human potential at a later stage of the life cycle.

In mechanical engineering, the building industry, and many other branches of industry, vibration machines are widely used, in which circular and directed oscillations predominate in the form of movement of the working equipment. This article examines methods for generating asymmetric oscillations, which are estimated by a numerical parameter, namely by the coefficient of asymmetry of the magnitude of the driving force when changing the direction of action in a directed motion within each period of oscillations. It is shown that for generating asymmetric mechanical vibrations, vibration devices are used, consisting of vibrators of directed vibrations, called stages. These stages form the total asymmetric driving force. The behavior of the total driving force of asymmetric vibrations and the working equipment of the vibration machine are described by analytical equations, which represent certain laws of motion of the mechanical system. This article presents a numerical analysis of methods for obtaining laws of motion for a two-stage, three-stage, and four-stage vibration device with asymmetric oscillations. An analysis of the methodology for obtaining a generalized law of motion for a vibration device with asymmetric oscillations is performed based on the application of polyharmonic oscillation synthesis methods. It is shown that the method of forming the total driving force of a vibration device based on the coefficients of the terms of the Fourier series has limited capabilities. This article develops, substantiates, and presents a generalized method for calculating and designing a vibration device with asymmetric oscillations by the value of the total driving force and a given value of the asymmetry coefficient in a wide range of rational designs of vibration machines. The proposed method is accompanied by a numerical example for a vibration device with an asymmetry coefficient of the total driving force equal to 10.

Accurate quantification of the crack-tip driving force (∆K) is fundamental to predicting the fatigue life of engineering structures. Analytical formulations of ∆K are rarely available for components with complex geometries. In such cases, finite element (FE) analysis has become a widely accepted approach for determining ∆K. In this study, an FE-based solution for the crack-tip driving force of a fatigue crack in an asymmetric L-shaped bell crank geometry, a representative complex structure, is established. The structure is fabricated from AISI 410 martensitic stainless steel. The FE-predicted ∆KI for crack growth in the Paris regime has been independently validated using the fractal crack-tip driving force model. Results show that the fatigue crack in the bell crank structure is driven by a combined Mode-I (opening) and Mode-II (shearing) crack-tip loading along a curved crack-path trajectory, as dictated by the asymmetric stress distribution. The fatigue crack edge exhibits fractality with fractal dimensions ranging from 1.00 (Euclidean) to 1.18 along the crack length (a−a0) up to 9.947 mm. The FE-calculated crack-tip driving forces of the bell crank structure are comparable with those computed based on the corrected crack edge fractal dimensions, thus validating the FE simulation outcomes. The resulting fatigue crack growth rates, determined from crack-tip driving forces based on validated FE-computed contour integrals, are comparable to those obtained from the ASTM standard tests.

Estimating carbon emissions and assessing their contribution are critical steps toward China’s objective of reaching a “carbon peak” in 2030 and “carbon neutrality” in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs.