M. Vander Haegen, A.-M. Etienne

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

Abstract Introduction: Les études sur les inquiétudes et la détresse des parents d’un enfant en rémission de cancer sont moins développées dans la littérature. L’objectif de l’étude est d’examiner l’intensité des inquiétudes ainsi que ses associations avec le facteur d’intolérance à l’incertitude (II) et les symptômes anxiodépressifs.
Méthodes: Soixante et un parents d’enfants en rémission de cancer (de quatre à six ans de rémission) ont participé à l’étude. Les parents ont rempli plusieurs questionnaires évaluant les inquiétudes, l’II et les symptômes anxiodépressifs.
Résultats: Les parents présentent majoritairement des symptômes anxieux et des inquiétudes intenses relatives à l’évolution de la santé… More >

Haein Lee¹, Seon Hong Lee¹, Kyeo Re Lee², Jang Hyun Kim^3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6023-6037, 2023, DOI:10.32604/cmc.2023.039104

Abstract Environmental, social, and governance (ESG) factors are critical in achieving sustainability in business management and are used as values aiming to enhance corporate value. Recently, non-financial indicators have been considered as important for the actual valuation of corporations, thus analyzing natural language data related to ESG is essential. Several previous studies limited their focus to specific countries or have not used big data. Past methodologies are insufficient for obtaining potential insights into the best practices to leverage ESG. To address this problem, in this study, the authors used data from two platforms: LexisNexis, a platform that provides media monitoring, and… More >

Yigang Wang¹, Hong Li¹, Wanbin Pan^1,*, Weijuan Cao¹, Jie Miao¹, Xiaofei Ai¹, Enya Shen²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 859-878, 2023, DOI:10.32604/cmes.2023.027320

Abstract Kinematic semantics is often an important content of a CAD model (it refers to a single part/solid model in this work) in many applications, but it is usually not the belonging of the model, especially for the one retrieved from a common database. Especially, the effective and automatic method to reconstruct the above information for a CAD model is still rare. To address this issue, this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics. First, as the geometry of an… More >

Mohammad Reza Boorboori, Husen Qiu, Jieyun Liu, Haiyang Zhang^*

Phyton-International Journal of Experimental Botany, Vol.92, No.6, pp. 1873-1886, 2023, DOI:10.32604/phyton.2023.027924

Abstract Rice is an essential part of the human diet in most parts of the world; On the other hand, the industrialization of societies has led to pollution of the environment, including heavy metal contamination of soil and water, which negatively affects rice production and quality. Therefore, finding ways to increase the yield and quality of this strategic crop seems essential. Several studies have been conducted in recent decades to find effective and inexpensive solutions to reduce the adverse effects of heavy metals in rice fields. Due to the negative effect of cadmium pollution on rice quality and yield, the current… More >

Ierin Babu^1,*, R. MathuSoothana², S. Kumar²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3621-3636, 2023, DOI:10.32604/iasc.2023.033791

Abstract Educational Data Mining (EDM) is an emergent discipline that concentrates on the design of self-learning and adaptive approaches. Higher education institutions have started to utilize analytical tools to improve students’ grades and retention. Prediction of students’ performance is a difficult process owing to the massive quantity of educational data. Therefore, Artificial Intelligence (AI) techniques can be used for educational data mining in a big data environment. At the same time, in EDM, the feature selection process becomes necessary in creation of feature subsets. Since the feature selection performance affects the predictive performance of any model, it is important to elaborately… More >

Jia An^#, Xiang Wang^#, Yajiang Jing, Jianping Huang, Qilong Wang, Gang Zhang, Jing Gao, Liang Peng, Wenli Huang^*, Yonggang Yan^*

Phyton-International Journal of Experimental Botany, Vol.92, No.5, pp. 1405-1420, 2023, DOI:10.32604/phyton.2023.026525

Abstract Although Platycodon grandiflorum (Jacq.) A.DC. is a renowned medicine food homology plant, reports of excessive cadmium (Cd) levels are common, which affects its safety for clinical use and food consumption. To enable its Cd levels to be regulated or reduced, it is necessary to first elucidate the mechanism of Cd uptake and accumulation in the plant, in addition to its detoxification mechanisms. This present study used inductively couple plasma-mass-spectrometry to analyze the subcellular distribution and chemical forms of Cd in different tissues of P. grandiflorum. The experimental results showed that Cd was mainly accumulated in the roots [predominantly in the… More >

Yuhan Liu, Yuqiao Zheng^*, Zhuang Ma, Cang Wu

Energy Engineering, Vol.120, No.5, pp. 1223-1237, 2023, DOI:10.32604/ee.2023.026329

Abstract An operating condition recognition approach of wind turbine spindle is proposed based on supervisory control and data acquisition (SCADA) normal data drive. Firstly, the SCADA raw data of wind turbine under full working conditions are cleaned and feature extracted. Then the spindle speed is employed as the output parameter, and the single and combined normal behavior model of the wind turbine spindle is constructed sequentially with the pre-processed data, with the evaluation indexes selected as the optimal model. Finally, calculating the spindle operation status index according to the sliding window principle, ascertaining the threshold value for identifying the abnormal spindle… More >

Wei Zhang¹, Mulian Zheng^1,*, Yifeng Li², Wuxi Zheng³

Journal of Renewable Materials, Vol.11, No.5, pp. 2513-2529, 2023, DOI:10.32604/jrm.2023.025275

Abstract Steel slag is characterized by high strength, good wear resistance and micro-expansion. This study aims at exploring the potential of steel slag in cement stabilized aggregates, mainly including mechanical properties, shrinkage and compensation mechanisms. For this purpose, the compressive strength and compressive resilient modulus of cement stabilized aggregates with different steel slag contents (CSMS) were initially investigated. Subsequently, the effects of steel slag and cement on dry shrinkage, temperature shrinkage, and total shrinkage were analyzed through a series of shrinkage test designs. Additionally, in combination with X-ray diffraction (XRD) and Scanning electron microscope (SEM), the characteristic peaks and microscopic images… More >

S. Hema^1,*, Y. Sukhi²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1503-1519, 2023, DOI:10.32604/csse.2023.036577

Abstract Smart grids and their technologies transform the traditional electric grids to assure safe, secure, cost-effective, and reliable power transmission. Non-linear phenomena in power systems, such as voltage collapse and oscillatory phenomena, can be investigated by chaos theory. Recently, renewable energy resources, such as wind turbines, and solar photovoltaic (PV) arrays, have been widely used for electric power generation. The design of the controller for the direct Current (DC) converter in a PV system is performed based on the linearized model at an appropriate operating point. However, these operating points are ever-changing in a PV system, and the design of the… More >

Geng Qin¹, Ping Luo¹, Kaiyuan Li¹, Yufeng Sun¹, Shiwei Wang¹, Xiaoting Li^1,2,3, Shuang Liu^1,2,3, Linyan Xue^1,2,3,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 999-1015, 2023, DOI:10.32604/cmc.2023.035777

Abstract Due to small size and high occult, metacarpophalangeal fracture diagnosis displays a low accuracy in terms of fracture detection and location in X-ray images. To efficiently detect metacarpophalangeal fractures on X-ray images as the second opinion for radiologists, we proposed a novel one-stage neural network named MPFracNet based on RetinaNet. In MPFracNet, a deformable bottleneck block (DBB) was integrated into the bottleneck to better adapt to the geometric variation of the fractures. Furthermore, an integrated feature fusion module (IFFM) was employed to obtain more in-depth semantic and shallow detail features. Specifically, Focal Loss and Balanced L1 Loss were introduced to… More >