scholarly journals Emergy and Economic Evaluation of Seven Typical Agroforestry Planting Patterns in the Karst Region of Southwest China

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 138 ◽  
Author(s):  
Zhigang Zou ◽  
Fuping Zeng ◽  
Kelin Wang ◽  
Zhaoxia Zeng ◽  
Leilei Zhao ◽  
...  
Keyword(s):  
Economic Benefit ◽  
Large Scale ◽  
Southwest China ◽  
Economic Benefits ◽  
Karst Region ◽  
Degraded Land ◽  
Land Use Pattern ◽  
The Sustainable Development ◽  
Ecological Industry ◽  
Local Farmers

As a vast degraded land ecosystem, the karst region of southwest China is currently experiencing serious conflicts between restoration of degraded vegetation communities and agricultural activities. Furthermore, it is not clear what land use pattern suits local farmers best. To evaluate the sustainability of the degraded agricultural ecosystems in the region, methods for emergy analysis were used to compare the ecological and economic benefits from seven typical agroforestry planting patterns in the Yunnan province. The eco-efficiencies of the apple pattern (AP), pear pattern (PP), pomegranate pattern (PRP) were all lower than that of the traditional corn pattern (CP), although the economic benefit was higher than that of CP. Ecological benefits of the apple-soybean pattern (ASP) and the pear-pumpkin pattern (PPP) were not significantly improved, while ecological and economic benefits of the pomegranate-grass-sheep pattern (PGSP) was improved significantly. Intercropping pumpkin in PP increased the economic efficiency by 28.3%, which was superior to that of the intercropping of soybeans (4.6%) in AP. These data implied that interplanting crops in AP and PP might result in higher economic benefit than the existing interplanting pattern. The multistory agroforestry planting pattern and raising in PGSP could optimize the relationship among tree-grass-sheep and improve ecological and economic benefits. Additionally, scenario analysis showed that local farmers might enjoy better ecological and economic benefits at a large scale by optimizing current agricultural production patterns. Our results suggest that together, both the local government and farmers can adjust the structure of agroforestry ecosystems to foster the sustainable development of the ecological industry in the karst region of China.

scholarly journals Multi-Objective Optimal Allocation of Water Resources Based on the NSGA-2 Algorithm While Considering Intergenerational Equity: A Case Study of the Middle and Upper Reaches of Huaihe River Basin, China

2020 ◽  
Vol 17 (24) ◽  
pp. 9289
Author(s):  
Jitao Zhang ◽  
Zengchuan Dong ◽  
Tian Chen
Keyword(s):  
Water Resources ◽  
Economic Benefit ◽  
Economic Benefits ◽  
Intergenerational Equity ◽  
Future Generations ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
The Sustainable Development ◽  
Equity Model

With the rapid development of society and the economy, the demand for water resources is increasing. This, combined with the increasing competition for water resources between current and future generations, hinders the sustainable development of society. To alleviate prominent water resources problems, achieve sustainable utilization of water resources and the sustainable development of society and economy, a multi-objective optimal water resources allocation model is proposed, in which different water sources and different water departments are considered to achieve the maximum social and economic benefits of the study area on the premise of water resources sustainability. To meet the needs of future generations, the discount value is introduced to measure intergenerational equity. A case study from seven cities in the upper and middle reaches of the Huaihe River Basin is given to verify the practicality and viability of the model. The non-dominated sorting Genetic Algorithms-2(NSGA-2) was used to find optimal water resources allocation schemes in 2020 and 2050 under the condition of a hydrological drought year (inflow guarantee rate p = 75%). Compared with previous models, the intergenerational equity model considers the sustainability of water resources, has higher social and economic benefits, and ensures the fair distribution of water resources among generations. According to the results, under balanced weight, the water shortage ratio of the seven cities will decrease from 5.24% in 2050 to 1.58% in 2020, and the economic benefit will increase from 79.46(1010CNY) to 168.3(1010CNY), respectively. In addition, the discount value of economic benefit in 2050 is 80.23(1010CNY), which is still higher than that in 2020. This shows that the water resource allocation scheme can eliminate the disparity between supply and demand for water resources and achieve intergenerational equity. Therefore, the intergenerational equity model can alleviate the contradiction of water resources and realize intergenerational equity.

scholarly journals Critical analysis of methodological approaches to assessing sustainability of arctic oil and gas projects

2021 ◽  
Vol 249 ◽  
pp. 463-479
Author(s):  
Aleksei Cherepovitsyn ◽  
Pavel Tcvetkov ◽  
Olga Evseeva
Keyword(s):  
Sustainable Development ◽  
Large Scale ◽  
Oil And Gas ◽  
Sustainability Assessment ◽  
Environmental Safety ◽  
Economic Benefits ◽  
The Arctic ◽  
Development Economic ◽  
The Sustainable Development ◽  
Meta Analyses

Development of hydrocarbon resources in the Arctic is one of the priority tasks for the economy of the Russian Federation; however, such projects are associated with significant risks for the environment of nearby regions. Large-scale development of hydrocarbon resources in the Arctic should be based on the principles of sustainable development, which imply a balance between socio-economic benefits and environmental risks. The purpose of this study is to analyze the gaps in scientific knowledge on the issues of assessing sustainability of Arctic oil and gas projects (OGPs) and systematize the key problematic elements of such assessments. The analysis was carried out in terms of four key elements that determine the feasibility of implementing Arctic OGPs in the context of sustainable development: economic efficiency, social effects, environmental safety and technological availability. The methodology for conducting bibliometric analysis, which included more than 15.227 sources from the Scopus database over the period of 2005-2020, was based on PRISMA recommendations for compiling systematic reviews and meta-analyses. Methodological problems of assessing sustainability of Arctic OGPs were mapped and divided into four key sectors: consideration of factors that determine sustainability; sustainability assessment; interpretation of assessment results; sustainability management. This map can serve as a basis for conducting a series of point studies, aimed at eliminating existing methodological shortcomings of the sustainable development concept with respect to Arctic OGPs.

scholarly journals Livelihood Impacts of Plantation Forests on Farmers in the Greater Mekong Subregion: A Systematic Review of Plantation Forest Models

Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1162
Author(s):  
Alexander van der Meer Simo
Keyword(s):  
Systematic Review ◽  
Land Tenure ◽  
Large Scale ◽  
Economic Benefits ◽  
Future Research ◽  
Plantation Forest ◽  
Plantation Forests ◽  
Local Livelihoods ◽  
Forest Models ◽  
Local Farmers

Background and Objectives: Plantation forests remain a highly contested element of rural development. Successive reviews of large-scale plantations established under land concessions identify predominantly negative impacts on local farmers’ livelihoods. Although concession models of plantation development have been common in the global South, other models characterised by different forms of land tenure, labour arrangements, and plantation design have also emerged. The impacts of these models on the livelihoods of local farmers are likely to be more varied. This paper presents the results of a systematic review on the impacts of different models of plantation forests on the livelihoods of local farmers in the Greater Mekong Sub-region. Materials and Methods: Seventy-two of more than 1000 publications were identified as meeting review criteria and were assessed systematically to identify how plantation forests impacted on the natural, financial, human, physical, and social assets of proximate rural communities. Plantation models included: state forest plantations; land and land-sharing concessions; land purchase programs; and “enrolled”, contracted, and independent smallholders. Results: The results confirm those of earlier studies that land concessions delivered lasting livelihoods benefits only to few communities. A small number of positive examples among these cases demonstrate, however, that these plantation models are not necessarily detrimental to local livelihoods. Other plantation forest models, based on contract farming, land purchase, and independent smallholders have generally brought economic benefits to local people, although differentially. Research Highlights and Conclusions: Overall, this review suggests that plantation forests are not inherently positive or negative for local livelihoods, and all plantation models have the potential to contribute positively to local livelihoods. Future research on this topic needs to adopt more holistic livelihoods perspectives.

scholarly journals Research and Application of Combined Algorithm Based on Sustainable Computing and Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Bo Hu
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Large Scale ◽  
Technology Development ◽  
Search Algorithm ◽  
Economic Benefits ◽  
Data Detection ◽  
The Sustainable Development ◽  
The Impact ◽  
Combined Algorithm

The Internet is a popular form of information technology development in the new century, and it organizes and analyzes big data by taking effective measures to find useful information. With manpower, it is obviously not enough to be in such a huge information system, so the emergence of sustainable computing and artificial intelligence has become the core of large-scale data processing at this stage. This paper studies the application of the combined algorithm based on sustainable computing and artificial intelligence. In this paper, a new combined intelligent search algorithm is proposed by combining sustainable computing with artificial intelligence. The combination algorithm firstly analyzes the value from the aspects of ecological environment and economic benefits and studies the overall evaluation of sustainable development ability. Secondly, the energy analysis method is used to establish a reasonable comprehensive ecosystem and evaluate its impact on the sustainable development of environment and economy. Finally, the impact of resource consumption, wind speed detection, waste discharge, and utilization of renewable resources in a certain area is analyzed by simulation. Through the experimental results, on the one hand, it is proved that the data obtained by the combined algorithm are more accurate than the single algorithm; on the other hand, the combined algorithm can be further sublimated and widely used for other data detection. The combination algorithm proposed in this paper can effectively detect the required data and has high applicability.

Screening for the FV: Q506 Mutation – Evaluation of Thirteen Plasma-based Methods for their Diagnostic Efficacy in Comparison with DNA Analysis

1997 ◽  
Vol 77 (03) ◽  
pp. 436-439 ◽  
Author(s):  
Armando Tripodi ◽  
Barbara Negri ◽  
Rogier M Bertina ◽  
Pier Mannuccio Mannucci
Keyword(s):  
Venous Thrombosis ◽  
Large Scale ◽  
Dna Analysis ◽  
Genetic Defect ◽  
Laboratory Diagnosis ◽  
Economic Benefits ◽  
Factor V ◽  
Factor X ◽  
Diagnostic Efficacy ◽  
Dna Test

SummaryThe factor V (FV) mutation Q506 that causes resistance to activated protein C (APC) is the genetic defect associated most frequently with venous thrombosis. The laboratory diagnosis can be made by DNA analysis or by clotting tests that measure the degree of prolongation of plasma clotting time upon addition of APC. Home-made and commercial methods are available but no comparative evaluation of their diagnostic efficacy has so far been reported. Eighty frozen coded plasma samples from carriers and non-carriers of the FV: Q506 mutation, diagnosed by DNA analysis, were sent to 8 experienced laboratories that were asked to analyze these samples in blind with their own APC resistance tests. The APTT methods were highly variable in their capacity to discriminate between carriers and non-carriers but this capacity increased dramatically when samples were diluted with FV-deficient plasma before analysis, bringing the sensitivity and specificity of these tests to 100%. The best discrimination was obtained with methods in which fibrin formation is triggered by the addition of activated factor X or Russell viper venom. In conclusion, this study provides evidence that some coagulation tests are able to distinguish carriers of the FV: Q506 mutation from non-carriers as well as the DNA test. They are inexpensive and easy to perform. Their use in large-scale clinical trials should be of help to determine the medical and economic benefits of screening healthy individuals for the mutation before they are exposed to such risk factors for venous thrombosis as surgery, pregnancy and oral contraceptives.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

Approaches to Supporting Local and Community Development

2018 ◽  
Author(s):  
Liesel Mack Filgueiras ◽  
Andreia Rabetim ◽  
Isabel Aché Pillar
Keyword(s):  
Large Scale ◽  
Mining Company ◽  
The Sustainable Development ◽  
Social Partnership ◽  
The Public ◽  
Mining Investment ◽  
The Social ◽  
Corporate Social

Reflection about the role of community engagement and corporate social investment in Brazil, associated with the presence of a large economic enterprise, is the major stimulus of this chapter. It seeks to present how cross-sector governance can contribute to the social development of a city and how this process can be led by a partnership comprising a corporate foundation, government, and civil society. The concept of the public–private social partnership (PPSP) is explored: a strategy for building a series of inter-sectoral alliances aimed at promoting the sustainable development of territories where the company has large-scale enterprises, through joint efforts towards integrated long-term strategic planning, around a common agenda. To this end, the case of Canaã dos Carajás is introduced, a municipality in the State of Pará, in the Amazon region, where large-scale mining investment is being carried out by the mining company Vale SA.

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

scholarly journals Analysis and Prediction of “AI + Education” Attention Based on Baidu Index—Taking Guizhou Province as an Example

2021 ◽  
Vol 13 (5) ◽  
pp. 120
Author(s):  
Yulin Zhao ◽  
Junke Li ◽  
Jiang-E Wang
Keyword(s):  
Artificial Intelligence ◽  
Southwest China ◽  
Arima Model ◽  
Modern Technology ◽  
Guizhou Province ◽  
Western Region ◽  
Elastic Coefficient ◽  
The Sustainable Development ◽  
Intelligence Education ◽  
Coefficient Method

Studying the attention of “artificial intelligence + education” in ethnic areas is of great significance for China for promoting the integrated development of new educational modes and modern technology in the western region. Guizhou province is an area inhabited by ethnic minorities, located in the heart of Southwest China. The development of its intelligent education has strong enlightenment for the whole country and the region. Therefore, this paper selects the Baidu Index of “artificial intelligence (AI) + education” in Guizhou province from 2013 to 2020, analyzes the spatial–temporal characteristics of its network attention by using the elastic coefficient method, and builds the ARIMA model on this basis to predict future development. The results show that the public’s attention to “AI + education” differs significantly in time and space. Then, according to the prediction results, this paper puts forward relevant suggestions for the country to promote the sustainable development of education in western ethnic areas.

Sign in / Sign up

Export Citation Format

Share Document