DuPont Model and Product Profitability Analysis Based on Activity-based Costing and Economic Value Added

Although DuPont analysis is widely used it is not easy to provide accurate performance information based on DuPont profitability analysis, which is established on the basis of traditional accounting earnings. Since Activity-based Costing (ABC) and Economic Value Added (EVA) are advanced approaches to costing activities and estimating economic profit of a firm, DuPont analysis using ABC and EVA information can be more appropriate in understanding Return on Equity (ROE). In this paper we set up an improved EVA-ABC based DuPont analysis system as well as its relative indices. Then it is applied to traditional profitability analysis to get a better performance measurement. The results show that the improved system can reduce the negative impacts of accounting principles and objectively reflect the operating performance of the enterprise. It also provides more accurate information for decision makers. Keywords: DuPont Analysis; Activity-based Costing; Economic Value Added; Profitability Analysi

Product Pricing Based on Activity-Based Costing

Activity-based costing could provide relatively accurate cost information and better serve the enterprise’s product pricing decision. Through the analysis of cost behavior on activities, it divides product costs into unit level, batch level, product-sustaining level and facility level activity costs, which can avoid the overlapping between the costs caused by dividing the costs into variable cost, activity cost and fixed cost. On this base, product pricing model is established based on the information of activity based costing. Case study shows that different pricing methods get different prices, which will provide different product-mix pricing decisions for enterprises. Keywords: Activity-based costing, Pricing decisions, Cost behavio

Empirical linkages between ICT, tourism, and trade towards sustainable environment: evidence from BRICS countries

There is a growing utilisation of information and communication technologies (ICT) in the recent digital era. Trade and tourism have also attained attention as determinants of environmental sustainability. Therefore, this study investigates linkages between ICT, tourism, trade, economic growth, and environmental sustainability in BRICS economies. Advanced panel estimation entitled cross-sectionally augmented autoregressive distributed lags (CSARDL) was applied from 1990 to 2019. Findings suggest the adverse effect of tourism, trade, and growth factors on environmental sustainability, whereas ICT helps promote a sustainable environment among the targeted economies. Likewise, the shortrun results prove that economic growth and tourism are prone to ecological health, while trade possesses an insignificant influence on ecological sustainability. These results suggest the integration of ICT in trade and tourism sectors to mitigate their negative ecological consequences

Revolutionizing building damage detection: A novel weakly supervised approach using high-resolution remote sensing images

ABSTRACTRapidly estimating post-disaster building damage via high-resolution remote sensing (HRRS) imagery is essential for initial disaster relief. However, the complex appearance of building damage poses challenges for existing methods. Specifically, relying solely on post-disaster images lacks building boundary guidance, while change detection methods using dual-temporal imageries are prone to introducing false changes. To address these issues, this paper presents a novel weakly supervised approach that leverages pre- and post-disaster HRRS images for building damage detection. The contributions of this paper are twofold. Firstly, a unique framework is proposed to utilize dual-temporal images. Precisely, the proposed method initially extracts fine-grained sub-building-level individuals from pre-disaster images by combining a fully convolutional neural network (FCN)-based method with superpixel segmentation. Then, these details serve as cues to effectively guide the detection of damaged building areas on post-disaster images, thereby enhancing accuracy. Secondly, we propose a weakly supervised method that solely relies on labeling building damage based on image patches but can ultimately yield pixel-level building damage results. Experiments conducted using HRRS images captured during the 2010 Haiti earthquake demonstrate that the proposed method outperforms existing methodologies. This effort of this paper will contribute to the sustainable development of cities and human settlements

Swelling‐Induced Structural Transformation Strategy: Controllable Synthesis of 2D Porous Polypyrrole/MXene Heterostructures with Tunable Pore Structures

Abstract 2D porous polymers have received great attention in many fields. Particularly, 2D porous polymers are considered as potential electrode materials for supercapacitors. However, the controllable synthesis of 2D porous polymers is not only faced with the difficulty in precisely controlling the reaction dynamics but is also challenged by the complex pore structure fabrication. In this paper, a swelling‐induced structural transformation strategy for the construction of 2D porous polypyrrole/MXene heterostructures (2D porous PPy/MXene) is proposed. The obtained 2D porous PPy/MXene samples own similar chemical compositions with adjusted pore structures (cylindrical mesostructure, spherical mesostructure, and spherical macrostructure), high specific surface areas (≈129–188 m2 g−1), and tunable pore sizes (≈7.8–52 nm). Due to the fast transport and diffusion of electrolytes and more electrode/electrolyte interface offered by cylindrical mesopores with high specific surface areas, the 2D porous PPy/MXene shows superior supercapacitor performances. This work sheds light on the effect of pore structures on supercapacitor performances of 2D porous polymers, and also provides clues for the fabrication of 2D porous polymers with tailorable pore structures as high‐performance energy storage materials

Recent Spatio-Temporal Variations of Suspended Sediment Concentrations in the Yangtze Estuary

Water and sediment are two of the most essential elements in estuaries. Their product, suspended sediment concentration (SSC), is involved in hydrology, geomorphology and ecology. This study was focused on the spatial and temporal variations of SSC in the Yangtze Estuary under new situations after the closure of ~50,000 dams in the Yangtze basin, including the Three Gorges Dam (TGD) in 2003. It was found that the SSC first exhibited an increasing and then a decreasing trend longitudinally from Xuliujing Station to the outer estuary with the Turbidity Maximum Zone located in the mouth bar area. Vertically, the SSC in the bottom layers averaged 0.96 kg/m3, about 2.4 times larger than the surface layers (0.40 kg/m3). During spring tides, the SSCs were always higher than those in neap tides, which was fit for the cognition law. As for the seasonal variations in the North Branch and mouth bar area, the SSCs in the dry season were higher than those in the flood season, while in the upper reach of the South Branch and outer estuary, the seasonal variation of SSCs reversed. This phenomenon primarily reflected the competition of riverine sediment flux and local resuspended sediment flux by wind-induced waves. As for the interannual changes, the SSCs demonstrated overall fluctuant downward trends, determined by riverine sediment flux and influenced by waves. This study revealed the new situation of SSC and can be a reference for other related researches in the Yangtze Estuary

Semi-Automated Mapping of Complex-Terrain Mountain Glaciers by Integrating L-Band SAR Amplitude and Interferometric Coherence

Mapping the outlines of glaciers has primarily relied on the interpretation of satellite optical images. However, the accurate delineation of glaciers in complex terrain mountain regions remains challenging, mainly because the supraglacial debris-covered ablation zones and snow-covered accumulation zones often exhibit the same spectral properties as their adjacent grounds in optical images. This study presents a novel approach by exploring both the satellite synthetic aperture radar (SAR) amplitude and interferometric coherence to map mountain glaciers. This method explores the deviation of the glacier surface signal in the SAR time series to distinguish glacier ice from the surrounding stable ground. To this end, we explored the classifying capabilities of two indices from a set of SAR images, SAR interferometric coherence and amplitude deviation index (ADI), to determine glacier boundary. We found that the two indices complement each other for mapping glaciers. A ratio map based on ADI and SAR coherence (ACR) was then derived, from which the glacier outline was automatically tracked using a specified threshold, followed by manual modification. We validated this approach on two typical valley glaciers, the debris-covered Hailuogou Glacier and debris-free Mozigou Glacier, in Mount Gongga in the southeastern Tibetan Plateau. The results show that the proposed ACR criteria can significantly enhance the contrast between glaciers and their surroundings. By comparing our results with manually delineated glacier outlines from high-resolution cloud-free satellite optical imagery, we found that the misclassification rate and difference rate for our results were 2.6% and 4.2%, respectively. The approach presented in this study can be easily adapted to map the outlines of mountain glaciers worldwide efficiently and is useful for inferring glacier boundary changes in a climate warming context