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  • Open Access

    ARTICLE

    Chitosan Nanoparticles as Biostimulant in Lettuce (Lactuca sativa L.) Plants

    Silvia C. Ramírez-Rodríguez1, Pablo Preciado-Rangel1, Marcelino Cabrera-De La Fuente2, Susana González-Morales2, Hortensia Ortega-Ortiz3,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 777-787, 2024, DOI:10.32604/phyton.2024.048096

    Abstract Biodegradable nanoparticles such as chitosan nanoparticles (CSNPs) are used in sustainable agriculture since they avoid damage to the environment; CSNPs have positive effects such as the accumulation of bioactive compounds and increased productivity in plants. This study aimed to investigate the impact of applying CSNPs on lettuce, specifically focusing on enzymatic activity, bioactive compounds, and yield. The trial was conducted using a completely randomized design, incorporating CSNPs: 0, 0.05, 0.1, 0.2, 0.4, and 0.8 mg mL. The doses of 0.4 mg mL improve yields up to 24.6% increases and 0.1 mg mL of CSNPs increases total phenols by 31.2% and… More >

  • Open Access

    ARTICLE

    Transcriptome Analysis of Inflorescence Development at the Five-Leaf Stage in Castor (Ricinus communis L.)

    Yong Zhao1,#, Yaxuan Jiang3,#, Li Wen1, Rui Luo2, Guorui Li2, Jianjun Di2, Mingda Yin2, Zhiyan Wang2, Fenglan Huang2,4,5,6,7,*, Fanjuan Meng3,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 713-723, 2024, DOI:10.32604/phyton.2024.047657

    Abstract The yield of castor is influenced by the type of inflorescence and the proportion of female flowers. However, there are few studies on the genetic mechanism involved in the development and differentiation of castor inflorescences. In this study, we performed transcriptomic analyses of three different phenotypes of inflorescences at the five-leaf stage. In comparison to the MI (complete pistil without willow leaves), 290 and 89 differentially expressed genes (DEGs) were found in the SFI (complete pistil with willow leaves) and the BI (monoecious inflorescence), respectively. Among the DEGs, 104 and 88 were upregulated in the SFI and BI, respectively, compared… More >

  • Open Access

    ARTICLE

    Unexpected Diversity in Ecosystem Nutrient Responses to Experimental Drought in Temperate Grasslands

    Biying Qiu1,2, Niwu Te2, Lin Song2, Yuan Shi2, Chuan Qiu2, Xiaoan Zuo3, Qiang Yu4, Jianqiang Qian5, Zhengwen Wang2, Honghui Wu6,7, Wentao Luo2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 831-841, 2024, DOI:10.32604/phyton.2024.047560

    Abstract The responses of ecosystem nitrogen (N) and phosphorus (P) to drought are an important component of global change studies. However, previous studies were more often based on site-specific experiments, introducing a significant uncertainty to synthesis and site comparisons. We investigated the responses of vegetation and soil nutrients to drought using a network experiment of temperate grasslands in Northern China. Drought treatment (66% reduction in growing season precipitation) was imposed by erecting rainout shelters, respectively, at the driest, intermediate, and wettest sites. We found that vegetation nutrient concentrations increased but soil nutrient concentrations decreased along the aridity gradient. Differential responses were… More >

  • Open Access

    ARTICLE

    Mitigating Carbon Emissions: A Comprehensive Analysis of Transitioning to Hydrogen-Powered Plants in Japan’s Energy Landscape Post-Fukushima

    Nugroho Agung Pambudi1,2,4,*, Andrew Chapman, Alfan Sarifudin1,3, Desita Kamila Ulfa4, Iksan Riva Nanda5

    Energy Engineering, Vol.121, No.5, pp. 1143-1159, 2024, DOI:10.32604/ee.2024.047555

    Abstract One of the impacts of the Fukushima disaster was the shutdown of all nuclear power plants in Japan, reaching zero production in 2015. In response, the country started importing more fossil energy including coal, oil, and natural gas to fill the energy gap. However, this led to a significant increase in carbon emissions, hindering the efforts to reduce its carbon footprint. In the current situation, Japan is actively working to balance its energy requirements with environmental considerations, including the utilization of hydrogen fuel. Therefore, this paper aims to explore the feasibility and implications of using hydrogen power plants as a… More >

  • Open Access

    ARTICLE

    A Study of the Effect of the Miller Cycle on the Combustion of a Supercharged Marine Diesel Engine

    Lingjie Zhao, Cong Li*

    Energy Engineering, Vol.121, No.5, pp. 1363-1380, 2024, DOI:10.32604/ee.2024.046918

    Abstract The Miller cycle is a program that effectively reduces NOx emissions from marine diesel engines by lowering the maximum combustion temperature in the cylinder, thereby reducing NOx emissions. To effectively investigate the impact of Miller cycle optimum combustion performance and emission capability under high load conditions, this study will perform a one-dimensional simulation of the performance of a marine diesel engine, as well as a three-dimensional simulation of the combustion in the cylinder. A 6-cylinder four-stroke single-stage supercharged diesel engine is taken as the research object. The chassis dynamometer and other related equipment are used to build the test system,… More >

  • Open Access

    ARTICLE

    A Compact UHF Antenna Based on Hilbert Fractal Elements and a Serpentine Arrangement for Detecting Partial Discharge

    Xiang Lin1,*, Jian Fang1, Ming Zhang1, Kuang Yin1, Yan Tian1, Yingfei Guo2, Qianggang Wang2

    Energy Engineering, Vol.121, No.5, pp. 1127-1141, 2024, DOI:10.32604/ee.2024.046861

    Abstract Efforts to protect electric power systems from faults have commonly relied on the use of ultra-high frequency (UHF) antennas for detecting partial discharge (PD) as a common precursor to faults. However, the effectiveness of existing UHF antennas suffers from a number of challenges such as limited bandwidth, relatively large physical size, and low detection sensitivity. The present study addresses these issues by proposing a compact microstrip patch antenna with fixed dimensions of 100 mm × 100 mm × 1.6 mm. The results of computations yield an optimized antenna design consisting of 2nd-order Hilbert fractal units positioned within a four-layer serpentine… More > Graphic Abstract

    A Compact UHF Antenna Based on Hilbert Fractal Elements and a Serpentine Arrangement for Detecting Partial Discharge

  • Open Access

    ARTICLE

    Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

    Yang Li1,2, Jianjun Zhao2, Xiaolong Yang2, He Wang1,*, Yuyan Wang1

    Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784

    Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established, and a comprehensive energy storage… More >

  • Open Access

    ARTICLE

    Weather-Driven Solar Power Forecasting Using D-Informer: Enhancing Predictions with Climate Variables

    Chenglian Ma1, Rui Han1, Zhao An2,*, Tianyu Hu2, Meizhu Jin2

    Energy Engineering, Vol.121, No.5, pp. 1245-1261, 2024, DOI:10.32604/ee.2024.046644

    Abstract Precise forecasting of solar power is crucial for the development of sustainable energy systems. Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic (PV) power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data. To overcome these challenges, this research presents a cutting-edge, multi-stage forecasting method called D-Informer. This method skillfully merges the differential transformation algorithm with the Informer model, leveraging a detailed array of meteorological variables and historical PV power generation records. The D-Informer model exhibits remarkable superiority over competing models across multiple performance metrics,… More > Graphic Abstract

    Weather-Driven Solar Power Forecasting Using D-Informer: Enhancing Predictions with Climate Variables

  • Open Access

    ARTICLE

    Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

    Dong Pan1, Xu Gui1, Jiayin Xu1, Yuming Shen1, Haoran Xu2, Yinghao Ma2,*

    Energy Engineering, Vol.121, No.5, pp. 1309-1328, 2024, DOI:10.32604/ee.2024.046464

    Abstract With the increasing urgency of the carbon emission reduction task, the generation expansion planning process needs to add carbon emission risk constraints, in addition to considering the level of power adequacy. However, methods for quantifying and assessing carbon emissions and operational risks are lacking. It results in excessive carbon emissions and frequent load-shedding on some days, although meeting annual carbon emission reduction targets. First, in response to the above problems, carbon emission and power balance risk assessment indicators and assessment methods, were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios, considering power supply regulation… More >

  • Open Access

    ARTICLE

    Deep-Ensemble Learning Method for Solar Resource Assessment of Complex Terrain Landscapes

    Lifeng Li1, Zaimin Yang1, Xiongping Yang1, Jiaming Li2, Qianyufan Zhou3,*, Ping Yang3

    Energy Engineering, Vol.121, No.5, pp. 1329-1346, 2024, DOI:10.32604/ee.2023.046447

    Abstract As the global demand for renewable energy grows, solar energy is gaining attention as a clean, sustainable energy source. Accurate assessment of solar energy resources is crucial for the siting and design of photovoltaic power plants. This study proposes an integrated deep learning-based photovoltaic resource assessment method. Ensemble learning and deep learning methods are fused for photovoltaic resource assessment for the first time. The proposed method combines the random forest, gated recurrent unit, and long short-term memory to effectively improve the accuracy and reliability of photovoltaic resource assessment. The proposed method has strong adaptability and high accuracy even in the… More >

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