Jinyou Qiu^1,2, Jiale Liu^1,2, Yubing Li^1,2,*, Shaogeng Zhong³, Guilong Dai^1,2, Wenhua Liu⁴

Frontiers in Heat and Mass Transfer, Vol.23, No.6, pp. 2025-2049, 2025, DOI:10.32604/fhmt.2025.072260 - 31 December 2025

Abstract The growing demand for energy-saving and renewable heating solutions has made photovoltaic/thermal (PV/T) heat pump systems a promising technology. However, their thermal and electrical performance, as well as the overall utilization of solar energy, strongly depend on capacity configuration and operating parameters. To address this issue, this study proposes a PV/T heat pump system featuring a novel rhombic flow channel structure that functions as the collector-evaporator. An experimental test bench was established to evaluate system performance, and a one-dimensional numerical model was developed to investigate the effects of environmental and operating parameters. The simulation results… More > Graphic Abstract

K. Kannan^a,*, B. Manjunatha^b, T. Marimuthu^c, P. Sangeetha^d

Chalcogenide Letters, Vol.22, No.2, pp. 167-175, 2025, DOI:10.15251/CL.2025.222.167

Abstract Cadmium sulfide (CdS) thin films are extensively utilized as a window layer in photovoltaic (PV) devices due to their high transmittance, suitable bandgap, and favorable electrical properties. This work presents a comprehensive performance analysis of CdS based thin films in PV applications, examining key factors such as optical, electrical, and structural properties. The bandgap (approximately 2.42 eV) allows effective photon transmission, reducing energy losses. Critical performance metrics, including film thickness, grain size, crystallinity, and interface quality with the absorber layer, are optimized to enhance charge separation and minimize recombination losses. The study highlights the balance More >

S. Srinivasa senthil, K. Vijayakumar^*

Energy Engineering, Vol.122, No.12, pp. 5149-5173, 2025, DOI:10.32604/ee.2025.070889 - 27 November 2025

Abstract Heating, ventilation, and air conditioning (HVAC) systems contribute substantially to global energy consumption, while rejecting significant amounts of low-grade heat into the environment. This paper presents a non-intrusive spiral-coil heat exchanger designed to recover waste heat from the outdoor condenser of a split-type air conditioner. The system operates externally without altering the existing HVAC configuration, thereby rendering it suitable for retrofitting. Water was circulated as the working fluid at flow rates of 0.028–0.052 kg/s to assess thermal performance. Performance indicators, including the outlet water temperature, heat transfer rate, convective coefficient, and efficiency, were systematically evaluated.… More >

Feng Zhou^1,2, Qifei Li^1,*, Lu Xin¹, Shiang Zhang³, Yang Liu¹, Ming Guo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 411-429, 2025, DOI:10.32604/cmes.2025.069639 - 30 October 2025

Abstract Bulb-type hydro turbines are commonly used in small- to medium-scale hydropower stations due to their compact design and adaptability to low-head conditions. However, long-term operation often results in wear at the runner rim, increasing tip clearance and triggering leakage flow and cavitation. These effects reduce hydraulic efficiency and accelerate blade surface erosion, posing serious risks to unit safety and operational stability. This study investigates the influence of tip clearance on cavitation performance in a 24 MW prototype bulb turbine. A three-dimensional numerical model is developed to simulate various operating conditions with different tip clearance values… More >

Kadriye Simsek Alan^*, Ayca Durgut, Helin Doga Demirel

Journal on Artificial Intelligence, Vol.7, pp. 397-415, 2025, DOI:10.32604/jai.2025.071133 - 20 October 2025

Abstract Efficient utilization of processor and memory resources is essential for sustaining performance and energy efficiency in modern computing infrastructures. While earlier research has emphasized CPU utilization forecasting, joint prediction of CPU and memory usage under real workload conditions remains underexplored. This study introduces a machine learning–based framework for real-time prediction of CPU and RAM utilization using the Google Cluster Trace 2019 v3 dataset. The framework combines Extreme Gradient Boosting (XGBoost) with a MultiOutputRegressor (MOR) to capture nonlinear interactions across multiple resource dimensions, supported by a leakage-safe imputation strategy that prevents bias from missing values. Nested… More >

Zhenhui Cai, Kaiqing Zhou^*, Zhouhua Liao

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2255-2303, 2025, DOI:10.32604/cmc.2025.067994 - 23 September 2025

Abstract The YOLO (You Only Look Once) series, a leading single-stage object detection framework, has gained significant prominence in medical-image analysis due to its real-time efficiency and robust performance. Recent iterations of YOLO have further enhanced its accuracy and reliability in critical clinical tasks such as tumor detection, lesion segmentation, and microscopic image analysis, thereby accelerating the development of clinical decision support systems. This paper systematically reviews advances in YOLO-based medical object detection from 2018 to 2024. It compares YOLO’s performance with other models (e.g., Faster R-CNN, RetinaNet) in medical contexts, summarizes standard evaluation metrics (e.g.,… More >

Jiangbo Wu¹, Siyi Sun¹, Xiaoze Du^1,2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.8, pp. 1789-1807, 2025, DOI:10.32604/fdmp.2025.064254 - 12 September 2025

Abstract This study explores the aerodynamic performance and flow field characteristics of supercritical carbon dioxide (sCO₂) centrifugal compressors under varying operating conditions. In particular, the Sandia main compressor impeller model is used as a reference system. Through three-dimensional numerical simulations, we examine the Mach number distribution, temperature field, blade pressure pulsation spectra, and velocity field evolution, and identify accordingly the operating boundaries ensuring stability and the mechanisms responsible for performance degradation. Findings indicate a stable operating range for mass flow rate between 0.74 and 3.74 kg/s. At the lower limit (0.74 kg/s), the maximum Mach number within… More >

Vina Eka Aristya¹, Sri Minarsih¹, Kristamtini¹, I Gusti Komang Dana Arsana¹, Samijan¹, Setyorini Widyayanti¹, Sodiq Jauhari¹, Arif Susila¹, Ni Wayan Trisnawati¹, I Ketut Mahaputra¹, I Nyoman Suyasa¹, Opik Mahendra², Supriyanta³, Gilang Wirakusuma³, Taufan Alam³, Taryono^3,*

Phyton-International Journal of Experimental Botany, Vol.94, No.7, pp. 2055-2073, 2025, DOI:10.32604/phyton.2025.065227 - 31 July 2025

Abstract Rice, as a primary commodity, needs to be increased in production while facing the sustainability challenges of limited land, water resources, and climate change. The demand for rice productivity was not enough to rely only on the fertile fields’ ability; it is necessary to consider the rainfed land potential. Cultivation in rainfed land involves biophysical pressure, low production, and limited access to superior varieties. Participatory rice breeding aimed to identify farmers’ trait preferences and develop acceptable lines. A bottom-up approach involved 203 farmers from four rainfed fields in Indonesia, i.e., Semarang-Central Java, Kulon Progo-Yogyakarta, Tabanan-Bali,… More >

Baishun Zhou^1,2, Haijiao Zhao³, Yuxin Wen², Gangyi Ding¹, Ying Xing^3,*, Xinyang Lin⁴, Lei Xiao⁵

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5201-5221, 2025, DOI:10.32604/cmc.2025.065726 - 30 July 2025

Abstract In recent years, with the rapid development of software systems, the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics. Defect prediction methods based on software metric elements highly rely on software metric data. However, redundant software metric data is not conducive to efficient defect prediction, posing severe challenges to current software defect prediction tasks. To address these issues, this paper focuses on the rational clustering of software metric data. Firstly, multiple software projects are evaluated to determine the preset number… More >

Manoharan Madhiarasan^*

Energy Engineering, Vol.122, No.8, pp. 2993-3011, 2025, DOI:10.32604/ee.2025.068358 - 24 July 2025

Abstract Accurate Global Horizontal Irradiance (GHI) forecasting has become vital for successfully integrating solar energy into the electrical grid because of the expanding demand for green power and the worldwide shift favouring green energy resources. Particularly considering the implications of the aggressive GHG emission targets, accurate GHI forecasting has become vital for developing, designing, and operational managing solar energy systems. This research presented the core concepts of modelling and performance analysis of the application of various forecasting models such as ARIMA (Autoregressive Integrated Moving Average), Elaman NN (Elman Neural Network), RBFN (Radial Basis Function Neural Network),… More >