Yuanyuan Yang¹, Xian Shi^1,2,*, Cheng Ji³, Yujie Yan³, Na An³, Teng Zhang⁴

Energy Engineering, Vol.121, No.12, pp. 3667-3688, 2024, DOI:10.32604/ee.2024.056266 - 22 November 2024

Abstract Based on a geology-engineering sweet spot evaluation, the high-quality reservoir zones and horizontal well landing points were determined. Subsequently, fracture propagation and production were simulated with a multilayer fracturing scenario. The optimal hydraulic fracturing strategy for the multilayer fracturing network was determined by introducing a vertical asymmetry factor. This strategy aimed to minimize stress shadowing effects in the vertical direction while maximizing the stimulated reservoir volume (SRV). The study found that the small vertical layer spacing of high-quality reservoirs and the presence of stress-masking layers (with a stress difference of approximately 3~8 MPa) indicate that… More > Graphic Abstract

Aws Al-Akam^1,*, Ahmed A. Abduljabbar², Ali Jaber Abdulhamed¹

Energy Engineering, Vol.121, No.12, pp. 3761-3777, 2024, DOI:10.32604/ee.2024.055198 - 22 November 2024

Abstract Photovoltaic (PV) panels are essential to the global transition towards sustainable energy, offering a clean, renewable source that reduces reliance on fossil fuels and mitigates climate change. High temperatures can significantly affect the performance of photovoltaic (PV) panels by reducing their efficiency and power output. This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic (PV) panels. It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels, considering the thermal performance and its implications for enhancing their overall performance and sustainability. The… More >

Farhad Mortezapour Shiri^*, Thinagaran Perumal, Norwati Mustapha, Raihani Mohamed

Journal on Artificial Intelligence, Vol.6, pp. 301-360, 2024, DOI:10.32604/jai.2024.054314 - 20 November 2024

Abstract Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and artificial intelligence (AI), outperforming traditional ML methods, especially in handling unstructured and large datasets. Its impact spans across various domains, including speech recognition, healthcare, autonomous vehicles, cybersecurity, predictive analytics, and more. However, the complexity and dynamic nature of real-world problems present challenges in designing effective deep learning models. Consequently, several deep learning models have been developed to address different problems and applications. In this article, we conduct a comprehensive survey of various deep learning models, including Convolutional Neural Network (CNN), Recurrent… More >

Mohana Priya Govindarajan^*, Sangeetha Subramaniam Karuppaiya Bharathi

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2967-2986, 2024, DOI:10.32604/cmc.2024.055536 - 18 November 2024

Abstract In the present research, we describe a computer-aided detection (CAD) method aimed at automatic fetal head circumference (HC) measurement in 2D ultrasonography pictures during all trimesters of pregnancy. The HC might be utilized toward determining gestational age and tracking fetal development. This automated approach is particularly valuable in low-resource settings where access to trained sonographers is limited. The CAD system is divided into two steps: to begin, Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal skull. We identified the HC using dynamic programming,… More >

Isha Sood^*, Varsha Sharma

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2791-2818, 2024, DOI:10.32604/cmc.2024.055463 - 18 November 2024

Abstract Ransomware has emerged as a critical cybersecurity threat, characterized by its ability to encrypt user data or lock devices, demanding ransom for their release. Traditional ransomware detection methods face limitations due to their assumption of similar data distributions between training and testing phases, rendering them less effective against evolving ransomware families. This paper introduces TLERAD (Transfer Learning for Enhanced Ransomware Attack Detection), a novel approach that leverages unsupervised transfer learning and co-clustering techniques to bridge the gap between source and target domains, enabling robust detection of both known and unknown ransomware variants. The proposed method More >

HUI ZHOU^#, ZHENGYU YU^#, JING XU, ZHONGWANG WANG, YALI TAO, JINJIN WANG, PEIPEI YANG, JINRONG YANG^*, TING NIU^*

Oncology Research, Vol.32, No.12, pp. 1903-1919, 2024, DOI:10.32604/or.2024.048138 - 13 November 2024

Abstract Background: Dihydrolipoamide S-acetyltransferase (DLAT) is a subunit of the pyruvate dehydrogenase complex (PDC), a rate-limiting enzyme complex, that can participate in either glycolysis or the tricarboxylic acid cycle (TCA). However, the pathogenesis is not fully understood. We aimed to perform a more systematic and comprehensive analysis of DLAT in the occurrence and progression of tumors, and to investigate its function in patients’ prognosis and immunotherapy. Methods: The differential expression, diagnosis, prognosis, genetic and epigenetic alterations, tumor microenvironment, stemness, immune infiltration cells, function enrichment, single-cell analysis, and drug response across cancers were conducted based on multiple computational… More > Graphic Abstract

YUAN YIN¹, ZHENGYIN WANG¹, YUJIE HU¹, JIA WANG¹, YI WANG^2,*, QUN LU^1,*

Oncology Research, Vol.32, No.12, pp. 1881-1890, 2024, DOI:10.32604/or.2024.048007 - 13 November 2024

Abstract Background: Caffeic acid (CA) is considered a promising phytochemical that has inhibited numerous cancer cell proliferation. Therefore, it is gaining increasing attention due to its safe and pharmacological applications. In this study, we investigated the role of CA in inhibiting the Interleukin-6 (IL-6)/Janus kinase (JAK)/Signal transducer and activator of transcription-3 (STAT-3) mediated suppression of the proliferation signaling in human prostate cancer cells. Materials and Methods: The role of CA in proliferation and colony formation abilities was studied using 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay and colony formation assays. Tumour cell death and cell cycle arrest were… More >

Priyanka¹, Damodarakurup Sajeev², Shaik Ahmed³, Shankar Pidishety³, Ram Soorat^3,*

Journal of Quantum Computing, Vol.6, pp. 53-66, 2024, DOI:10.32604/jqc.2024.054000 - 14 November 2024

Abstract The present study delves into the application of investigating quantum state behaviour, particularly focusing on coherent and superposition states. These states, characterized by their remarkable stability and precision, have found extensive utility in various domains of quantum mechanics and quantum information processing. Coherent states are valuable for manipulating quantum systems with accuracy. Superposition states allow quantum systems to exist in numerous configurations at the same time, which paves the way for quantum computing’s capacity for parallel processing. The research accentuates the crucial role of quantum error correction (QEC) in ensuring the stability and reliability of… More >

Wei Song^1,*, Xiaojian Shi², Shoupan Wei²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012236

Abstract Different post-welding treatments, such as TIG-Dressing, blinding, HFMI et.al are often used for steel welded joints in construction machinery manufacturing as an effective and reliable method for fatigue strength improvement. This paper investigates the fatigue performance of thick Q355D cruciform joints in heavy load-carrying steel structures under different treatments. Two TIG-Dressing treatments, blinding and HFMI for the full-penetration welded joints were used for fatigue tests. Experimental tests studied the fatigue strength of cruciform welded joints of Q355D structural steel under different treatments. The geometric parameters and relevant statistical analyses were performed by actual 3D optical More >

Jie Wang^1,*, Jingyu Gu¹, Shuai Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012184

Abstract The interaction between the particle and the bubble under the ultrasonic wave excitation plays a pivotal role in various applications such as targeted therapy, ultrasonic cleaning, ultrasonography, and microbubble motors. When the particle is in close proximity or even attached to the bubble, a strong fluid-structure interaction occurs, significantly influencing the particle propulsion. The attachment of the bubble to the particle results in distinct bubble pulsation patterns and particle acceleration mechanisms from the non-contact state. Thus, we propose a fluid-structure interaction model based on the boundary integral method (BIM) to comprehensively consider the distance between More >