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  • Open Access

    ARTICLE

    Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

    Jie Lin*, Hongchi Shen, Tingting Pei, Yan Wu

    Energy Engineering, Vol.122, No.1, pp. 331-347, 2025, DOI:10.32604/ee.2024.055611 - 27 December 2024

    Abstract Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unit power generation costs. The service life of these modules directly affects these costs. Over time, the performance of PV modules gradually declines due to internal degradation and external environmental factors. This cumulative degradation impacts the overall reliability of photovoltaic power generation. This study addresses the complex degradation process of PV modules by developing a two-stage Wiener process model. This approach accounts for the distinct phases of degradation resulting from module aging and environmental influences. A power degradation model based on the More > Graphic Abstract

    Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

  • Open Access

    ARTICLE

    Enhancing Solar Photovoltaic Efficiency: A Computational Fluid Dynamics Analysis

    Rahool Rai1,2,3,*, Fareed Hussain Mangi4, Kashif Ahmed2, Sudhakar Kumaramsay1,5,6,*

    Energy Engineering, Vol.122, No.1, pp. 153-166, 2025, DOI:10.32604/ee.2024.051789 - 27 December 2024

    Abstract The growing need for sustainable energy solutions, driven by rising energy shortages, environmental concerns, and the depletion of conventional energy sources, has led to a significant focus on renewable energy. Solar energy, among the various renewable sources, is particularly appealing due to its abundant availability. However, the efficiency of commercial solar photovoltaic (PV) modules is hindered by several factors, notably their conversion efficiency, which averages around 19%. This efficiency can further decline to 10%–16% due to temperature increases during peak sunlight hours. This study investigates the cooling of PV modules by applying water to their… More >

  • Open Access

    ARTICLE

    Deep learning identification of novel autophagic protein-protein interactions and experimental validation of Beclin 2-Ubiquilin 1 axis in triple-negative breast cancer

    XIANG LI1,#, WENKE JIN2,#, LIFENG WU2, HUAN WANG1, XIN XIE1, WEI HUANG1,*, BO LIU2,*

    Oncology Research, Vol.33, No.1, pp. 67-81, 2025, DOI:10.32604/or.2024.055921 - 20 December 2024

    Abstract Background: Triple-negative breast cancer (TNBC), characterized by its lack of traditional hormone receptors and HER2, presents a significant challenge in oncology due to its poor response to conventional therapies. Autophagy is an important process for maintaining cellular homeostasis, and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors. In contrast to targeting protein activity, intervention with protein-protein interaction (PPI) can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways. Methods: Here, we employed Naive Bayes, Decision Tree, and k-Nearest Neighbors to elucidate the complex PPI… More >

  • Open Access

    ARTICLE

    SBL-JP-0004: A promising dual inhibitor of JAK2 and PI3KCD against gastric cancer

    HASSAN M. OTIFI*

    Oncology Research, Vol.33, No.1, pp. 235-243, 2025, DOI:10.32604/or.2024.055677 - 20 December 2024

    Abstract Background: Gastric cancer (GC) remains a global health burden and is often characterized by heterogeneous molecular profiles and resistance to conventional therapies. The phosphoinositide 3-kinase and PI3K and Janus kinase (JAK) signal transducer and activator of transcription (JAK-STAT) pathways play pivotal roles in GC progression, making them attractive targets for therapeutic interventions. Methods: This study applied a computational and molecular dynamics simulation approach to identify and characterize SBL-JP-0004 as a potential dual inhibitor of JAK2 and PI3KCD kinases. KATOIII and SNU-5 GC cells were used for in vitro evaluation. Results: SBL-JP-0004 exhibited a robust binding affinity for… More >

  • Open Access

    REVIEW

    Engendered nanoparticles for treatment of brain tumors

    SOROUSH SOLEYMANI1, MOHAMMAD DOROUDIAN2,*, MAHDIEH SOEZI3,4, ALI BELADI5, KIARASH ASGARI2, ASO MOBARAKSHAHI2, ARYANA AGHAEIPOUR2, RONAN MACLOUGHLIN6,7,8,*

    Oncology Research, Vol.33, No.1, pp. 15-26, 2025, DOI:10.32604/or.2024.053069 - 20 December 2024

    Abstract Brain metastasis and primary glioblastoma multiforme represent the most common and lethal malignant brain tumors. Its median survival time is typically less than a year after diagnosis. One of the major challenges in treating these cancers is the efficiency of the transport of drugs to the central nervous system. The blood-brain barrier is cooperating with advanced stages of malignancy. The blood-brain barrier poses a significant challenge to delivering systemic medications to brain tumors. Nanodrug delivery systems have emerged as promising tools for effectively crossing this barrier. Additionally, the development of smart nanoparticles brings new hope More >

  • Open Access

    ARTICLE

    Genetic signatures of ERCC1 and ERCC2 expression, along with SNPs variants, unveil favorable prognosis in SCLC patients undergoing platinum-based chemotherapy

    ENRICO CALIMAN1,2, SARA FANCELLI1,2, FEDERICO SCOLARI3, ADRIANO PASQUI4, CLARA MANNESCHI4, DANIELE LAVACCHI1, FRANCESCA MAZZONI4, FRANCESCA GENSINI5, VALERIA PASINI6, CAMILLA EVA COMIN2,7, LUCA VOLTOLINI2,8, SERENA PILLOZZI1,2,*, LORENZO ANTONUZZO1,2,4

    Oncology Research, Vol.33, No.1, pp. 45-55, 2025, DOI:10.32604/or.2024.050161 - 20 December 2024

    Abstract Background: Platinum chemotherapy (CT) remains the backbone of systemic therapy for patients with small-cell lung cancer (SCLC). The nucleotide excision repair (NER) pathway plays a central role in the repair of the DNA damage exerted by platinum agents. Alteration in this repair mechanism may affect patients’ survival. Materials and Methods: We conducted a retrospective analysis of data from 38 patients with extensive disease (ED)-SCLC who underwent platinum-CT at the Clinical Oncology Unit, Careggi University Hospital, Florence (Italy), from 2015 to 2020. mRNA expression analysis and single nucleotide polymorphism (SNP) characterization of three NER pathway genes—namely ERCC1, ERCC2,… More >

  • Open Access

    ARTICLE

    Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets, Aggregation Operators and Basic Uncertainty Information Granule

    Anastasios Dounis*, Ioannis Palaiothodoros, Anna Panagiotou

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 759-811, 2025, DOI:10.32604/cmes.2024.057888 - 17 December 2024

    Abstract Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and retrieval. Advanced fuzzy set theories have emerged as effective tools to address these challenges. In this paper, new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets (q-ROFS) and interval-valued q-rung orthopair fuzzy sets (IVq-ROFS). Three aggregation operators are proposed in our methodologies: the q-ROF weighted averaging (q-ROFWA), the q-ROF weighted geometric (q-ROFWG), and the q-ROF weighted neutrality averaging (q-ROFWNA), which enhance decision-making under uncertainty. These operators are paired More > Graphic Abstract

    Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets, Aggregation Operators and Basic Uncertainty Information Granule

  • Open Access

    ARTICLE

    A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

    Khuram Ali Khan1, Saba Mubeen Ishfaq1, Atiqe Ur Rahman2, Salwa El-Morsy3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 501-530, 2025, DOI:10.32604/cmes.2024.057865 - 17 December 2024

    Abstract Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty, evaluating educational institutions can be difficult. The concept of a possibility Pythagorean fuzzy hypersoft set (pPyFHSS) is more flexible in this regard than other theoretical fuzzy set-like models, even though some attempts have been made in the literature to address such uncertainties. This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union, intersection, complement, OR- and AND-operations. Some results related to these operations are also modified for pPyFHSS. Additionally, the similarity measures between pPyFHSSs are More >

  • Open Access

    ARTICLE

    Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net (MU-Net) on Spine Magnetic Resonance Images

    Lakshmi S V V1, Shiloah Elizabeth Darmanayagam1,*, Sunil Retmin Raj Cyril2

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 733-757, 2025, DOI:10.32604/cmes.2024.056424 - 17 December 2024

    Abstract Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people everywhere. Due to its ability to produce a detailed view of the soft tissues, including the spinal cord, nerves, intervertebral discs, and vertebrae, Magnetic Resonance Imaging is thought to be the most effective method for imaging the spine. The semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar diseases. It is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of… More >

  • Open Access

    ARTICLE

    A Novel Model for Describing Rail Weld Irregularities and Predicting Wheel-Rail Forces Using a Machine Learning Approach

    Linlin Sun1,2, Zihui Wang3, Shukun Cui1,2, Ziquan Yan1,2,*, Weiping Hu3, Qingchun Meng3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 555-577, 2025, DOI:10.32604/cmes.2024.056023 - 17 December 2024

    Abstract Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed railways. They can cause significant wheel-rail dynamic interactions, leading to wheel-rail noise, component damage, and deterioration. Few researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry irregularities. However, the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric shape. In this study, novel theoretical models were developed for three categories of rail weld irregularities, based… More >

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