Abdul Momin¹, Amana Khatoon^1,*, Wajahat Khan¹, Dilsat Bozdoğan Konuşkan², Muhammad Mudasar Aslam³, Muhammad Jamil⁴, Shafiq Ur Rehman⁵, Baber Ali⁶, Alevcan Kaplan⁷, Sana Wahab⁸, Muhammad Nauman Khan^9,*, Sezai Ercisli^10,11, Mohammad Khalid Al-Sadoon¹²

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1117-1128, 2024, DOI:10.32604/phyton.2024.048994

Abstract Sprouts are ready-to-eat and are recognized worldwide as functional components of the human diet. Recent advances in innovative agricultural techniques could enable an increase in the production of healthy food. The use of light-emitting diode (LED) in indoor agricultural production could alter the biological feedback loop, increasing the functional benefits of plant foods such as wheat and lentil sprouts and promoting the bioavailability of nutrients. The effects of white (W), red (R), and blue (B) light were investigated on the growth parameters and nutritional value of wheat and lentil sprouts. In the laboratory, seeds were… More >

Chen Zhang¹, Liming Liu¹, Yufei Yang¹, Yu Sun¹, Jiaxu Ning², Yu Zhang³, Changsheng Zhang^1,4,*, Ying Guo⁴

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5201-5223, 2024, DOI:10.32604/cmc.2024.050863

Abstract The flying foxes optimization (FFO) algorithm, as a newly introduced metaheuristic algorithm, is inspired by the survival tactics of flying foxes in heat wave environments. FFO preferentially selects the best-performing individuals. This tendency will cause the newly generated solution to remain closely tied to the candidate optimal in the search area. To address this issue, the paper introduces an opposition-based learning-based search mechanism for FFO algorithm (IFFO). Firstly, this paper introduces niching techniques to improve the survival list method, which not only focuses on the adaptability of individuals but also considers the population’s crowding degree More >

Guangfei Jia^*, Yanchao Meng, Zhiying Qin

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 445-463, 2024, DOI:10.32604/sdhm.2024.049298

Abstract The vibration signals of rolling bearings exhibit nonlinear and non-stationary characteristics under the influence of noise. In intelligent fault diagnosis, unprocessed signals will lead to weak fault characteristics and low diagnostic accuracy. To solve the above problem, a fault diagnosis method based on parameter optimization feature mode decomposition and improved deep belief networks is proposed. The feature mode decomposition is used to decompose the vibration signals. The parameter adaptation of feature mode decomposition is implemented by improved whale optimization algorithm including Levy flight strategy and adaptive weight. The selection of activation function and parameters is More > Graphic Abstract

Dongwei Wang^1,*, Lijian Cao¹, Weidong Wang², Jiajun Hu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1103-1122, 2024, DOI:10.32604/fdmp.2023.042654

Abstract A self-priming pump is a centrifugal pump that has the ability to prime itself. Typically, its performance depends on the configuration of its reflux hole. In this study, the ANSYS FLUENT software is used to investigate the effects of three different radial positions of the reflux hole on gas-liquid two-phase distribution, pressure pulsation, and imp during self-priming. The research results indicate that: (1) The effective channel size for the reflux liquid to enter the volute varies depending on the location of the reflux hole. The effect of the impeller rotation on the reflux liquid becomes… More >

Zhang Zhi¹, Haiyu Huang², Wei Xiong², Yijia Zhou³, Mingyu Yan^3,*, Shaolian Xia², Baofeng Jiang², Renbin Su², Xichen Tian⁴

Energy Engineering, Vol.121, No.6, pp. 1557-1576, 2024, DOI:10.32604/ee.2024.047401

Abstract Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existing scenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios, which threatens the robustness of stochastic unit commitment and hinders its application. This paper provides a stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming and Benders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouples the primal problem into the master problem and two types of subproblems. In the master problem, the committed generator is determined, while the feasibility and… More >

Camden L. Hebson^1,*, Kyle Bliton², Amr Y. Hammouda¹, Kaitlyn Barr³, W. Hampton Gray⁴, Mohini Gunnett², Waldemar F. Carlo¹

Congenital Heart Disease, Vol.19, No.2, pp. 185-195, 2024, DOI:10.32604/chd.2024.048871

Abstract D-transposition of the great arteries (d-TGA) is surgically repaired with the arterial switch operation (ASO) with excellent results, however short and long-term morbidities still develop including neurocognitive delay. Clinically significant central sleep apnea is uncommon in non-premature infants, but when present indicates immature autonomic control of respiration likely due to a neurologic disorder. We report the unanticipated finding of central sleep apnea in four-term neonates with d-TGA after uncomplicated ASO, with the short-term complication of delayed hospital discharge and long-term concerns regarding this early marker of brain immaturity and its hindrance to normal development. Within More >

Jianfeng He^1,2, Haowei Ye¹, Jie Ning¹, Hui Zhou^1,2,*, Bo She^3,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3355-3372, 2024, DOI:10.32604/cmc.2024.048706

Abstract In addressing the challenge of motion artifacts in Positron Emission Tomography (PET) lung scans, our study introduces the Triple Equivariant Motion Transformer (TEMT), an innovative, unsupervised, deep-learning-based framework for efficient respiratory motion correction in PET imaging. Unlike traditional techniques, which segment PET data into bins throughout a respiratory cycle and often face issues such as inefficiency and overemphasis on certain artifacts, TEMT employs Convolutional Neural Networks (CNNs) for effective feature extraction and motion decomposition.TEMT’s unique approach involves transforming motion sequences into Lie group domains to highlight fundamental motion patterns, coupled with employing competitive weighting for 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 More >

Yingli Zhu^1,*, Jiachi Xie¹, Mingwei Zhu¹, Jun Zhang², Miaomiao Li³

Energy Engineering, Vol.121, No.5, pp. 1161-1172, 2024, DOI:10.32604/ee.2024.041205

Abstract The open ratio of a current collector has a great impact on direct methanol fuel cell (DMFC) performance. Although a number of studies have investigated the influence of the open ratio of DMFC current collectors, far too little attention has been given to how geometry (including the shape and feature size of the flow field) affects a current collector with an equal open ratio. In this paper, perforated and parallel current collectors with an equal open ratio of 50% and different feature sizes are designed, and the corresponding experimental results are shown to explain the… 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… More >