Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect on enhancing output power. It revealed that a small compact design with the use of magnetic, gravity, and centrifugal forces as excitation elements and a fixed piezoelectric to avoid a slip ring had a good influence on output power optimisation. One of the interesting designs that future works should focus on is using gear for frequency up-conversion to enhance output power density and keep the design simple and compact.
Large language models (LLMs) are a rapidly evolving class of artificial intelligence with significant potential in clinical healthcare. Despite accelerating adoption, rigorous systematic evidence on clinical utility, patient safety, and implementation feasibility remains fragmented. To systematically review LLM applications across clinical domains, evaluate performance with appropriate contextual caveats, characterize implementation barriers, and identify ethical and regulatory considerations. Scientific databases were searched from January 2020 to January 2025. Studies evaluating transformer-based LLMs (≥10M parameters) in clinical settings were eligible. Data were independently double-extracted; quality was assessed using QUADAS-2, RE-A
... Show MoreAbstract Background Deep learning (DL) has attracted increasing attention in orthodontics, with many studies reporting high diagnostic and predictive accuracy. However, despite these promising results, routine clinical adoption remains limited. Objectives This scoping review aimed to explore the main barriers that restrict the translation of DL systems from research environments into everyday orthodontic practice. Methodology The review was conducted in accordance with PRISMA-ScR guidelines. Electronic searches were performed in PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published between 2015 and June 2025. Studies reporting quantitative performance of DL-based orthodontic applications were included. Dat
... Show MoreThis study examines strategies of cultural domestication in Muravyov and Kistyakovsky’s Russian translation of (The Fellowship of the Ring). It documents transformations of character names, toponyms, dialogues, and cultural references, highlighting systematic Russification and the infusion of Soviet political commentary that reshape the text into cultural rewriting.
The orogenic gold deposit of Tamilouw – Haya is hosted by slate and metapelitic rocks within Tehoru metamorphic complex. Gold and polymetallic sulfides mineralization at study area is predominantly formed in the form of veins, stockwork and breccia although minor dissemination is slightly appeared in the rock float samples. They are trapped and controlled by NE-SW and NNE-SSW trending geologic structure occurred during orogeny process from Late Miocene to Pliocene. The common ore minerals assemblage at Tamilouw – Haya deposit are dominated by native gold, chalcopyrite, pyrite, sphalerite, galena, pyrrhotite, tetrahedrite-tennantite (sulphosalt), marcasite,realgar, kalininite and arsenopyrite as hypogene minerals and accompanied by co
... Show MoreAbstract Portable communication devices such as WLAN, WiMAX, LTE, ISM, and 5G utilize one or more of the triple bands at (2.32.7 GHz,3.4–3.6GHz,and5–6GHz)andsufferfromtheeffectofmultipathproblemsbecausetheyareusedinurbanregions.To date, no one has performed a review of the antennas used for these types of wireless communications. This study reviewed two types of microstrip antennas (slot and fractal) that have been reported by researchers (as a single element) using a survey that included the evaluation of several important specifications of the antennas in previous research, such as operating bandwidth, gain, efficiency, axial ratio bandwidth (ARBW), and size. The weaknesses in the design of all antennas were carefully identified to de
... Show MoreAmid the growing demand for multifunctional and environmentally benign materials, lead-free double perovskites have emerged as a strategically important development in advanced functional materials research. This study presents the synthesis of Ba2PrMnO6 (BPMO) double perovskite nanocrystals for the first time via a hydrothermal method, and a comprehensive evaluation has been conducted using the density functional theory (DFT) framework. Structural, thermodynamic, electronic, optical, and mechanical properties were investigated through X-ray diffraction (XRD), ultraviolet-visible (UV-vis) spectroscopy, FESEM/EDX, FTIR, and density functional theory (DFT) calculations. XRD confirms a stable tetragonal I4/m phase with experimental lattice con
... Show MoreErosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the
... Show MoreThis review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.
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