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  • Open Access


    Soil NOx Emission Prediction via Recurrent Neural Networks

    Zhaoan Wang1, Shaoping Xiao1,*, Cheryl Reuben2, Qiyu Wang2, Jun Wang2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 285-297, 2023, DOI:10.32604/cmc.2023.044366

    Abstract This paper presents designing sequence-to-sequence recurrent neural network (RNN) architectures for a novel study to predict soil NOx emissions, driven by the imperative of understanding and mitigating environmental impact. The study utilizes data collected by the Environmental Protection Agency (EPA) to develop two distinct RNN predictive models: one built upon the long-short term memory (LSTM) and the other utilizing the gated recurrent unit (GRU). These models are fed with a combination of historical and anticipated air temperature, air moisture, and NOx emissions as inputs to forecast future NOx emissions. Both LSTM and GRU models can capture the intricate pulse patterns… More >

  • Open Access


    Effects of I-EGR and Pre-Injection on Performance of Gasoline Compression Ignition (GCI) at Low-Load Condition

    Binbin Yang1,*, Leilei Liu1, Yan Zhang1, Jingyu Gong1, Fan Zhang2, Tiezhu Zhang1

    Energy Engineering, Vol.120, No.10, pp. 2233-2250, 2023, DOI:10.32604/ee.2023.028898

    Abstract Gasoline compression ignition (GCI) has been considered as a promising combustion concept to yield ultra-low NOX and soot emissions while maintaining high thermal efficiency. However, how to improve the low-load performance becomes an urgent issue to be solved. In this paper, a GCI engine model was built to investigate the effects of internal EGR (i-EGR) and pre-injection on in-cylinder temperature, spatial concentration of mixture and OH radical, combustion and emission characteristics, and the control strategy for improving the combustion performance was further explored. The results showed an obvious expansion of the zone with an equivalence ratio between 0.8~1.2 is realized… More >

  • Open Access


    Inter-Provincial Transaction Model in Two-Level Electricity Market Considering Carbon Emission and Consumption Responsibility Weights

    Chunlei Jiao1, Hongyan Hao2, Ming Li1,*, Rifucairen Fu1, Yichun Liu3, Shunfu Lin3, Ronghui Liu3

    Energy Engineering, Vol.120, No.10, pp. 2393-2416, 2023, DOI:10.32604/ee.2023.028574

    Abstract In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading, how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem. The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market, complete the intra-provincial consumption responsibility weight index, and consume renewable energy across provinces and regions. This paper combines power generation and consumption within the province, uses inter-provincial renewable energy trading to meet the load demand within the province and completes the index of intra-provincial… More >

  • Open Access



    Junjie Chen* , Baofang Liu, Longfei Yan, Deguang Xu

    Frontiers in Heat and Mass Transfer, Vol.11, pp. 1-15, 2018, DOI:10.5098/hmt.11.2

    Abstract The combustion and emissions characteristics of methane-air mixtures in high-temperature catalytic micro-combustors were studied numerically. Both the heterogeneous and homogeneous chemistry were modeled simultaneously using detailed reaction mechanisms in order to better understand the role of each pathway in determining the product distributions. Computational fluid dynamics simulations were performed at a variety of pressures, temperatures, compositions, and combustor dimensions to determine their effects on the combustion and emissions characteristics. Comparisons were made between the results obtained for a purely heterogeneous case, a purely homogeneous case, and a coupled homogeneousheterogeneous case. It was shown that homogeneous and heterogeneous chemistry take place… More >

  • Open Access


    Study of Parental Worry and Its Associated Factors in Childhood Cancer Survivorship

    Étude sur les inquiétudes parentales et ses facteurs associés dans le cadre de la rémission d’un cancer pédiatrique

    M. Vander Haegen, A.-M. Etienne

    Psycho-Oncologie, Vol.16, No.4, pp. 343-350, 2022, DOI:10.3166/pson-2022-0218

    Abstract Introduction: Studies on worry and distress in parents of a childhood cancer survivor are less developed in the literature. The aim of the study was to examine the intensity of worry and its association with intolerance of uncertainty factor and anxiety–depressive symptoms.
    Methods: In total, 61 parents of a childhood cancer survivor (4–6 years of remission) participated in the study. Parents completed several questionnaires assessing worry, intolerance of uncertainty, and anxiety–depressive symptoms.
    Results: The majority of parents suffer from anxiety symptoms and intense worries about the health of their childhood cancer survivor. The factor of intolerance of uncertainty seems to… More >

  • Open Access


    Parents of Children Suffering from Cancer or in Remission from Cancer: a Need to Accompany Them!

    Parents d’un enfant atteint de cancer ou en rémission de cancer : une nécessité de les accompagner !

    M. Vander Haegen, C. Flahault, K. Lamore

    Psycho-Oncologie, Vol.16, No.4, pp. 339-341, 2022, DOI:10.3166/pson-2022-0215

    Abstract When cancer strikes a child, parents (and family) find themselves involved at many levels in the trajectory of the disease and treatment. This trajectory of care varies from family to family. For several years, the psycho-medical world has been implementing actions in the field to support parents of a child with cancer or in remission from cancer. As health professionals, we must continue these actions and develop a strong and harmonious partnership with parents because they are the first relays for the medical care of the child.

    Résumé Lorsqu’un cancer touche un enfant, les parents (et la famille) se retrouvent… More >

  • Open Access


    Investigating the Effects of Eichhornia Crassipes Biodiesel and Liquefied Petroleum Gas on the Performance and Emissions of a Dual-Fuel Engine

    Hawraa S. Mohammed*, Mahmoud A. Mashkour

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.9, pp. 2329-2343, 2023, DOI:10.32604/fdmp.2023.026890

    Abstract This study considers the effect of Eichhornia Crassipes Biodiesel (ECB) blends on the performances, combustion, and emission characteristics of a direct injection compression ignition engine operated in a dual-fuel mode (DFM) and equipped with an Exhaust gas recirculation technique (EGR). In particular, a single-cylinder, four-stroke, water-cooled diesel engine was utilized and four modes of fuel operation were considered: mode I, the engine operated with an ordinary diesel fuel; mode II, the engine operated with the addition of 2.4 L/min of liquefied petroleum gas (LPG) and 20% EGR; mode III, 20% ECB with 2.4 L/min LPG and 20% EGR; mode IV,… More >

  • Open Access


    Modeling of Combined Economic and Emission Dispatch Using Improved Sand Cat Optimization Algorithm

    Fadwa Alrowais1, Jaber S. Alzahrani2, Radwa Marzouk1, Abdullah Mohamed3, Gouse Pasha Mohammed4,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6145-6160, 2023, DOI:10.32604/cmc.2023.038300

    Abstract Combined Economic and Emission Dispatch (CEED) task forms multi-objective optimization problems to be resolved to minimize emission and fuel costs. The disadvantage of the conventional method is its incapability to avoid falling in local optimal, particularly when handling nonlinear and complex systems. Metaheuristics have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black box. Therefore, this paper focuses on the design of an improved sand cat optimization algorithm based CEED (ISCOA-CEED) technique. The ISCOA-CEED technique majorly concentrates on reducing fuel costs and the emission of generation… More >

  • Open Access


    Acoustic Emission Recognition Based on a Three-Streams Neural Network with Attention

    Kang Xiaofeng1, Hu Kun2,*, Ran Li3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2963-2974, 2023, DOI:10.32604/csse.2023.025908

    Abstract Acoustic emission (AE) is a nondestructive real-time monitoring technology, which has been proven to be a valid way of monitoring dynamic damage to materials. The classification and recognition methods of the AE signals of the rotor are mostly focused on machine learning. Considering that the huge success of deep learning technologies, where the Recurrent Neural Network (RNN) has been widely applied to sequential classification tasks and Convolutional Neural Network (CNN) has been widely applied to image recognition tasks. A novel three-streams neural network (TSANN) model is proposed in this paper to deal with fault detection tasks. Based on residual connection… More >

  • Open Access


    Regional Renewable Energy Optimization Based on Economic Benefits and Carbon Emissions

    Cun Wei1, Yunpeng Zhao2,*, Mingyang Cong1, Zhigang Zhou1,*, Jingzan Yan3, Ruixin Wang1, Zhuoyang Li1, Jing Liu1

    Energy Engineering, Vol.120, No.6, pp. 1465-1484, 2023, DOI:10.32604/ee.2023.026337

    Abstract With increasing renewable energy utilization, the industry needs an accurate tool to select and size renewable energy equipment and evaluate the corresponding renewable energy plans. This study aims to bring new insights into sustainable and energy-efficient urban planning by developing a practical method for optimizing the production of renewable energy and carbon emission in urban areas. First, we provide a detailed formulation to calculate the renewable energy demand based on total energy demand. Second, we construct a dual-objective optimization model that represents the life cycle cost and carbon emission of renewable energy systems, after which we apply the differential evolution… More >

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