Fenglan Zhao^1,2,#, Shuwen Wu^1,#, Xue Meng¹, Jianping Xue^1,2, Yongbo Duan^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1705-1716, 2024, DOI:10.32604/phyton.2024.052287

Abstract Dōng líng căo, the dried aboveground parts of Isodon rubescens (Hemls.) Hara., is commonly consumed as a medicinal decoction or tea beverage. Natural beverages can be an important source of human dietary selenium (Se). However, how I. rubescens plants respond to exogenous Se remains unknown. In this study, a pot cultivation experiment was employed to investigate the phenotypic and physiological responses of I. rubescens plants exposed to Se. Fifteen days after applying different concentrations of sodium selenate to the soil, the Se enrichment capacity, growth indices, antioxidant capacities, and the content of flavonoids and diterpenoids were measured in… More >

Yang Hua^#, Jinyu Sun^#, Yuxuan Lou, Hao Zhang, Jing Shi^*, Wei Sun^*

Congenital Heart Disease, Vol.19, No.3, pp. 279-291, 2024, DOI:10.32604/chd.2024.051190

Abstract Background: White matter lesion (WML) is common in aging brain and is associated with cognitive impairment and dementia. However, recent studies reported an association between patent foramen ovale (PFO) and WML in migraineurs, especially in young, middle-aged migraineurs. Our retrospective, case-control study aims to describe the clinical characteristics of WML in this population and to explore potential risk factors. Methods: 226 patients with migraine and PFO were consecutively initially screened. Relevant factors were selected by the least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression model. A Nomogram was employed to visualize… More >

Chunhong Zeng, Kang Lu, Zhiqin He^*, Qinmu Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1441-1456, 2024, DOI:10.32604/cmc.2024.051551

Abstract Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients. The article utilizes the random forest algorithm to construct a gait parameter model, which maps the relationship between parameters such as height, weight, age, gender, and gait speed, achieving prediction of key points on the gait curve. To enhance prediction accuracy, an attention mechanism is introduced into the algorithm to focus more on the main features. Meanwhile, to ensure high similarity between the reconstructed gait curve and the normal one, More >

Xialin Liu^1,2,3,*, Junsheng Wu⁴, Lijun Chen^2,3, Jiyuan Hu⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1601-1631, 2024, DOI:10.32604/cmc.2024.050626

Abstract Virtual machine (VM) consolidation aims to run VMs on the least number of physical machines (PMs). The optimal consolidation significantly reduces energy consumption (EC), quality of service (QoS) in applications, and resource utilization. This paper proposes a prediction-based multi-objective VM consolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value. We use a hybrid model based on Auto-Regressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) (HPAS) as a prediction model and consolidate VMs to PMs based on prediction results by HPAS, aiming at minimizing the More >

Nidhi Parashar¹, Prashant Johri¹, Arfat Ahmad Khan⁵, Nitin Gaur¹, Seifedine Kadry^2,3,4,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 389-425, 2024, DOI:10.32604/cmc.2024.050240

Abstract The growing global requirement for food and the need for sustainable farming in an era of a changing climate and scarce resources have inspired substantial crop yield prediction research. Deep learning (DL) and machine learning (ML) models effectively deal with such challenges. This research paper comprehensively analyses recent advancements in crop yield prediction from January 2016 to March 2024. In addition, it analyses the effectiveness of various input parameters considered in crop yield prediction models. We conducted an in-depth search and gathered studies that employed crop modeling and AI-based methods to predict crop yield. The… More >

Bo Yang^1,*, Yucun Qian¹, Jianzhong Xu², Yaxing Ren³, Yixuan Chen⁴

Energy Engineering, Vol.121, No.8, pp. 2085-2091, 2024, DOI:10.32604/ee.2024.050083

Abstract This article has no abstract. More >

Hao Bai¹, Beiyuan Liu^2,*, Hongwen Liu³, Jupeng Zeng², Jian Ouyang⁴, Yipeng Liu¹

Energy Engineering, Vol.121, No.8, pp. 2191-2211, 2024, DOI:10.32604/ee.2024.049848

Abstract Most ground faults in distribution network are caused by insulation deterioration of power equipment. It is difficult to find the insulation deterioration of the distribution network in time, and the development trend of the initial insulation fault is unknown, which brings difficulties to the distribution inspection. In order to solve the above problems, a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed. Firstly, the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network, and the… More >

Qin Qian¹, Mingjing Lu^1,2,*, Anhai Zhong¹, Feng Yang¹, Wenjun He¹, Min Li¹

Energy Engineering, Vol.121, No.8, pp. 2167-2190, 2024, DOI:10.32604/ee.2024.049430

Abstract The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics, engineering quality, and well conditions. These relationships, nonlinear in nature, pose challenges for accurate description through physical models. While field data provides insights into real-world effects, its limited volume and quality restrict its utility. Complementing this, numerical simulation models offer effective support. To harness the strengths of both data-driven and model-driven approaches, this study established a shale oil production capacity prediction model based on a machine learning combination model. Leveraging fracturing development data from 236 wells… More >

Xujing Zhang¹, Hatem Abushammala², Debora Puglia³, Binbao Lu¹, Pengwu Xu¹, Weijun Yang^1,*, Piming Ma¹

Journal of Renewable Materials, Vol.12, No.5, pp. 895-908, 2024, DOI:10.32604/jrm.2024.049810

Abstract Fluorescent nanomaterials have attracted much attention, due to their unique luminescent properties and promising applications in biomedical areas. In this study, lignin based fluorescent nanoparticles (LFNP) with high yield (up to 32.4%) were prepared from lignin nanoparticles (LNP) by one-pot hydrothermal method with ethylenediamine (EDA) and citric acid. Morphology and chemical structure of LFNP were investigated by SEM, FT-IR, and zeta potential, and it was found that the structure of LFNP changed with the increase of citric acid addition. LFNP showed the highest fluorescence intensity under UV excitation at wavelengths of 375–385 nm, with emission More > Graphic Abstract

Tahir Abbas^1,*, Ali Haider Khan², Khadija Kanwal³, Ali Daud^4,*, Muhammad Irfan⁵, Amal Bukhari⁶, Riad Alharbey⁶

Computer Systems Science and Engineering, Vol.48, No.4, pp. 871-895, 2024, DOI:10.32604/csse.2024.049026

Abstract The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The More >