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  • Open Access

    ARTICLE

    Application of Plant Growth-Promoting Bacteria as an Eco-Friendly Strategy for Mitigating the Harmful Effects of Abiotic Stress on Plants

    Ahmed Hassan Abdou1,*, Omar Abdullah Alkhateeb2, Hossam Eldin Hamed Mansour3, Hesham S. Ghazzawy4, Muayad Saud Albadrani5, Nadi Awad Al-harbi6, Wasimah B. Al-Shammari7, Khaled Abdelaal8,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3305-3321, 2023, DOI:10.32604/phyton.2023.044780

    Abstract Plant growth-promoting bacteria (PGPB) play an important role in improving agricultural production under several abiotic stress factors. PGPB can be used to increase crop growth and development through hormonal balance and increase nutrient uptake. The positive effect of PGPB may be due to its pivotal role in morphophysiological and biochemical characteristics like leaf number, leaf area, and stem length. Furthermore, relative water content, chlorophyll content, carotenoids, antioxidant enzymes, and plant hormones were improved with PGPB treatment. Crop yield and yield components were also increased with PGPB treatment in numerous crops. The anatomical structure of plant organs was increased such as… More >

  • Open Access

    ARTICLE

    Research on ECMS Based on Segmented Path Braking Energy Recovery in a Fuel Cell Vehicle

    Wen Sun1, Meijing Li2, Guoxiang Li1, Ke Sun1,*, Shuzhan Bai1,*

    Energy Engineering, Vol.121, No.1, pp. 95-110, 2024, DOI:10.32604/ee.2023.042096

    Abstract Proton exchange membrane fuel cells are widely regarded as having the potential to replace internal combustion engines in vehicles. Since fuel cells cannot recover energy and have a slow dynamic response, they need to be used with different power sources. Developing efficient energy management strategies to achieve excellent fuel economy is the goal of research. This paper proposes an adaptive equivalent fuel minimum consumption strategy (AECMS) to solve the problem of the poor economy of the whole vehicle caused by the wrong selection of equivalent factors (EF) in traditional ECMS. In this method, the kinematics interval is used to update… More >

  • Open Access

    REVIEW

    Exosomes in viral infection: Effects for pathogenesis and treatment strategies

    FATEMEH HEIDARI1,2, REIHANEH SEYEDEBRAHIMI1,2, PIAO YANG3, MOHSEN ESLAMI FARSANI1,2, SHIMA ABABZADEH2,4, NASER KALHOR5, HAMED MANOOCHEHRI6, MOHSEN SHEYKHHASAN7,*, MARYAM AZIMZADEH8,9,*

    BIOCELL, Vol.47, No.12, pp. 2597-2608, 2023, DOI:10.32604/biocell.2023.043351

    Abstract Exosomes are small vesicles that carry molecules from one cell to another. They have many features that make them interesting for research, such as their stability, low immunogenicity, size of the nanoscale, toxicity, and selective delivery. Exosomes can also interact with viruses in diverse ways. Emerging research highlights the significant role of exosomes in viral infections, particularly in the context of diseases like COVID-19, HIV, HBV and HCV. Understanding the intricate interplay between exosomes and the human immune system holds great promise for the development of effective antiviral therapies. An important aspect is gaining clarity on how exosomes influence the… More >

  • Open Access

    ARTICLE

    Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

    Othman S. Al-Heety1,*, Zahriladha Zakaria1,*, Ahmed Abu-Khadrah2, Mahamod Ismail3, Sarmad Nozad Mahmood4, Mohammed Mudhafar Shakir5, Sameer Alani6, Hussein Alsariera1

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2103-2127, 2024, DOI:10.32604/cmes.2023.029509

    Abstract Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision. In this article, these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data. The framework integrates Kalman filtering and Q-learning. Unlike smoothing Kalman filtering, our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error. Unlike traditional Q-learning, our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road… More >

  • Open Access

    ARTICLE

    ENHANCEMENT OF THERMOELECTRIC DEVICE PERFORMANCE THROUGH INTEGRATED FLOW CHANNELS

    B. V. K. Reddy, Matthew Barry, John Li, Minking K. Chyu*

    Frontiers in Heat and Mass Transfer, Vol.4, No.2, pp. 1-7, 2013, DOI:10.5098/hmt.v4.2.3001

    Abstract In this study, the thermoelectric performance of an integrated thermoelectric device (iTED) with rectangular, round end slots, and circular flow channel designs applied to waste heat recovery for several hot stream flow rates has been investigated using numerical methods. An iTED is constructed with p- and n-type semiconductor materials bonded to the surfaces of an interconnector with flow channels drilled through it. This interconnector acts as an internal heat exchanger directing waste heat from the hot stream to thermoelectric elements. The quantity of heat extracted from the waste heat source and the subsequent amount of electrical power generated P0 from… More >

  • Open Access

    ARTICLE

    Effects of T-Factor on Quantum Annealing Algorithms for Integer Factoring Problem

    Zhiqi Liu1, Shihui Zheng1, Xingyu Yan1, Ping Pan1,2, Licheng Wang1,3,*

    Journal of Quantum Computing, Vol.5, pp. 41-54, 2023, DOI:10.32604/jqc.2023.045572

    Abstract The hardness of the integer factoring problem (IFP) plays a core role in the security of RSA-like cryptosystems that are widely used today. Besides Shor’s quantum algorithm that can solve IFP within polynomial time, quantum annealing algorithms (QAA) also manifest certain advantages in factoring integers. In experimental aspects, the reported integers that were successfully factored by using the D-wave QAA platform are much larger than those being factored by using Shor-like quantum algorithms. In this paper, we report some interesting observations about the effects of QAA for solving IFP. More specifically, we introduce a metric, called T-factor that measures the… More >

  • Open Access

    ARTICLE

    Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

    Kanhua Su, Jian Wei*, Meng Li, Hao Li, Wenghao Da, Lang Zhang

    Sound & Vibration, Vol.57, pp. 97-117, 2023, DOI:10.32604/sv.2023.043734

    Abstract During the drilling process, stick-slip vibration of the drill string is mainly caused by the nonlinear friction generated by the contact between the drill bit and the rock. To eliminate the fatigue wear of downhole drilling tools caused by stick-slip vibrations, the Fractional-Order Proportional-Integral-Derivative (FOPID) controller is used to suppress stick-slip vibrations in the drill string. Although the FOPID controller can effectively suppress the drill string stick-slip vibration, its structure is flexible and parameter setting is complicated, so it needs to use the corresponding machine learning algorithm for parameter optimization. Based on the principle of torsional vibration, a simplified model… More > Graphic Abstract

    Research on Stick-Slip Vibration Suppression Method of Drill String Based on Machine Learning Optimization

  • Open Access

    ARTICLE

    Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture

    Medhat A. Tawfeek1,2, Nacim Yanes3,4, Leila Jamel5,*, Ghadah Aldehim5, Mahmood A. Mahmood1,6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2545-2564, 2023, DOI:10.32604/cmc.2023.042179

    Abstract The trend towards smart greenhouses stems from various factors, including a lack of agricultural land area owing to population concentration and housing construction on agricultural land, as well as water shortages. This study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research centers. The proposed model uses a one-dimensional convolutional neural network (CNN) deep learning model to control the growth of strategic crops, including cucumber, pepper, tomato, and bean. The proposed model uses the Internet of Things (IoT) to collect data on agricultural operations and then uses this data… More >

  • Open Access

    REVIEW

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

    PRIYADHARSHINI THANJAVUR SRIRAMAMOORTHI1,2, GAYATHRI GOPAL1,2, SHIBI MURALIDAR1,2, SAI RAMANAN ESWARAN1,2, DANUSH NARAYAN PANNEERSELVAM1,2, BHUVANESWARAN MEIYANATHAN1,2, SRICHANDRASEKAR THUTHIKKADU INDHUPRAKASH1,2, SENTHIL VISAGA AMBI1,2,*

    BIOCELL, Vol.47, No.11, pp. 2335-2350, 2023, DOI:10.32604/biocell.2023.029379

    Abstract The novel coronavirus pneumonia (COVID-19) is spreading worldwide and threatening people greatly. The routes by which SARS-CoV-2 causes lung injury have grown to be a major concern in the scientific community since patients with new Coronavirus, severe acute respiratory syndrome coronavirus (SARS-CoV-2) have a high likelihood of developing acute respiratory distress syndrome (ARDS) in severe cases. The mortality rate of COVID-19 has increased over the period due to rapid spread, and it becomes crucial to understand the disease epidemiology, pathogenic mechanisms, and suitable treatment strategies. ARDS is a respiratory disorder and is one of the clinical manifestations observed in patients… More > Graphic Abstract

    Molecular basis of COVID-19, ARDS and COVID-19-associated ARDS: Diagnosis pathogenesis and therapeutic strategies

  • Open Access

    ARTICLE

    Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

    Shaocheng Wu1, Honghao Liang1, Xiaowei Chen1, Tao Liu1, Junpeng Ru2,3, Qianhong Gong2,3, Jin Li2,3,*

    Journal on Big Data, Vol.5, pp. 57-67, 2023, DOI:10.32604/jbd.2023.044257

    Abstract Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model’s evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of the scheme proposed in this… More >

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