Di Hu¹, Shouli Yi^1,*, Di Lin², Suping Gao³, Ting Lei³, Wenji Li⁴, Tingdan Xu¹, Songlin Jiang¹

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 681-697, 2024, DOI:10.32604/phyton.2024.049166

Abstract In plants, heteromorphic self-incompatibility (HetSI) is a strategy for avoiding self-pollination and promoting outcrossing, and during this process, numerous protein-protein interaction events occur between the pistil and pollen. Previous studies in Primula and Fagopyrum that focused on HetSI systems have provided interesting insights; however, the molecular mechanism underlying HetSI remains largely unknown. In this study, we profiled the proteome of Plumbago auriculata stigmas before and after self-incompatible (SI) and self-compatible (SC) pollination. Comparative analyses were conducted by 4D-DIA (Four-dimensional data independent acquisition), a promising technology that increases the sensitivity and reduces the spectral complexity of proteomic analysis by adding a… More >

Wissal Saadellaoui¹, Samiha Kahlaoui¹, Kheiria Hcini¹, Abir Haddada¹, Noomene Sleimi^2,*, Roberta Ascrizzi³, Guido Flamini³, Fethia Harzallah-Skhiri⁴, Sondes Stambouli-Essassi¹

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 725-744, 2024, DOI:10.32604/phyton.2024.048110

Abstract In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardaria draba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatile organic compounds (96.7%–98.9%) were identified; 4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones, 1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the main group, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane (44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in the two fractions of EOs, representing 98.8%… More >

Silvia C. Ramírez-Rodríguez¹, Pablo Preciado-Rangel¹, Marcelino Cabrera-De La Fuente², Susana González-Morales², Hortensia Ortega-Ortiz^3,*

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 >

Nugroho Agung Pambudi^1,2,4,*, Andrew Chapman, Alfan Sarifudin^1,3, 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 >

Xiang Lin^1,*, 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

Lifeng Li¹, Zaimin Yang¹, Xiongping Yang¹, Jiaming Li², Qianyufan Zhou^3,*, 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 >

Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion… More >

Siyuan Liu^1,*, Jinying Huang², Jiancheng Ma¹, Licheng Jing², Yuxuan Wang²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 761-777, 2024, DOI:10.32604/cmc.2024.049484

Abstract Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems, such as relatively ideal speed conditions and sample conditions. In engineering practice, the rotational speed of the machine is often transient and time-varying, which makes the sample annotation increasingly expensive. Meanwhile, the number of samples collected from different health states is often unbalanced. To deal with the above challenges, a complementary-label (CL) adversarial domain adaptation fault diagnosis network (CLADAN) is proposed under time-varying rotational speed and weakly-supervised conditions. In the weakly supervised learning condition, machine prior information is used for sample annotation via cost-friendly complementary label learning.… More >

Kranthi Alluri, S. Gopikrishnan^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 943-961, 2024, DOI:10.32604/cmc.2024.048621

Abstract Secure authentication and accurate localization among Internet of Things (IoT) sensors are pivotal for the functionality and integrity of IoT networks. IoT authentication and localization are intricate and symbiotic, impacting both the security and operational functionality of IoT systems. Hence, accurate localization and lightweight authentication on resource-constrained IoT devices pose several challenges. To overcome these challenges, recent approaches have used encryption techniques with well-known key infrastructures. However, these methods are inefficient due to the increasing number of data breaches in their localization approaches. This proposed research efficiently integrates authentication and localization processes in such a way that they complement each… More >

Cheng Wan¹, Jiani Zhao¹, Xiangqian Hong², Weihua Yang^2,*, Shaochong Zhang^2,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 391-407, 2024, DOI:10.32604/cmc.2024.048307

Abstract Age-related macular degeneration (AMD) ranks third among the most common causes of blindness. As the most conventional and direct method for identifying AMD, color fundus photography has become prominent owing to its consistency, ease of use, and good quality in extensive clinical practice. In this study, a convolutional neural network (CSPDarknet53) was combined with a transformer to construct a new hybrid model, HCSP-Net. This hybrid model was employed to tri-classify color fundus photography into the normal macula (NM), dry macular degeneration (DMD), and wet macular degeneration (WMD) based on clinical classification manifestations, thus identifying and resolving AMD as early as… More >