Excess heat significantly reduces the efficiency and lifespan of electrical and optoelectronic devices. While passive radiative cooling is becoming more common, achieving active thermal control without physical reconfiguration remains challenging. Unlike conventional static absorbers, we propose a broadband plasmonic solar absorber designed to regulate energy absorption in the near-infrared (NIR) region without modifying the geometrical parameters. The design utilizes a coaxial cylindrical metal-insulator-metal (MIM) configuration, combining refractory copper (Cu), silicon dioxide (SiO2), and a trilayer graphene (Gr) that allows electrical tuning in a broadband solar absorber. Simulation results show a maximum broadband absorption efficienc

Background: Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity. Objective: This study aimed to assess thyroid function profiles in critically ill neonates in the neonatal intensive care unit (NICU) compared with healthy controls. Additionally, we aimed to detect the presence of TD and its possible association with critical illness. Methods: A case-control study was performed in 100 neonates, comprising 50 sick neonates and 50 healthy controls. We measured thyroid functio

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

Unter Exilliteratur versteht man „die literarische Produktion von Autoren, die wegen politischer, religiöser oder rassistischer Verfolgung gezwungen sind, sich an einem anderen als dem von ihnen gewünschten Lebens- und Arbeitsort aufzuhalten.“[1] Deswegen unterscheidet sich „Migration“ von „Exil“ dadurch, dass sie freiwillige Auswanderung ist. Bereits in der Antike und auch im Mittelalter gab es Schriftsteller, die vor Zensur oder politischer Verfolgung ins Exil geflohen sind, wie zum Beispiel der griechische Satiriker des 

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

The using of recycled aggregates from construction and demolition waste (CDW) can preserve natural aggregate resources, reduce the demand for landfill, and contribute to a sustainable built environment. Concrete demolition waste has been proven to be an excellent source of aggregates for new concrete production. At a technical, economic, and environmental level, roller compacted concrete (RCC) applications benefit various civil construction projects. Roller Compacted Concrete (RCC) is a homogenous mixture that is best described as a zero-slump concrete placed with compacting equipment, uses in storage areas, dams, and most often as a basis for rigid pavements. The mix must be sufficiently dry to support

Objectives: To assess the qualifications and performance of newly graduated pharmacists and explore factors that affect their performance in public hospitals. Methods: This qualitative study included face-to-face, semi-structured interviews with hospital practitioner pharmacists. It was conducted between March and May 2023 in Kerbala province, Iraq. The participating pharmacists were selected purposefully because they had three or more years of work experience at governmental hospitals. The audio-recording interviews were transcribed. Thematic analyses were used to generate themes and subthemes from the interviews. Results: Twenty-seven hospital pharmacists participated in this study. The study found that there are several factors t

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

Experimental programs based test results has been used as a means to find out the response of individual elements of structure. In the present study involves investigated behavior of five reinforced concrete deep beams of dimension (length 1200 x height 300 x width150mm) under two points concentrated load with shear span to depth ratio of (1.52), four of these beams with hallow core and
retrofit with carbon fiber reinforced polymer CFRP (with single or double or sides Strips). Two shapes of hallow are investigated (circle and square section) to evaluated the response of beams in case experimental behavior. Test on simply supported beam was performed in the laboratory & loaddeflection, strain of concrete data and crack pattern of

This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions.