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Search Results (10,208)

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Keywords = transformation design

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18 pages, 2905 KiB  
Article
Analysis of Mutual Inductance Characteristics of Rectangular Coils Based on Double-Sided Electromagnetic Shielding Technology and Study of the Effects of Positional Misalignment
by Yang Leng, Derong Luo, Zhongqi Li and Fei Yu
Electronics 2025, 14(1), 200; https://doi.org/10.3390/electronics14010200 (registering DOI) - 5 Jan 2025
Abstract
In wireless power transfer systems, the relative positional misalignment between transmitting and receiving coils significantly impacts the system’s mutual inductance characteristics, thereby constraining the system’s output power stability and transmission efficiency optimization potential. Hence, accurate formulas for calculating mutual inductance are crucial for [...] Read more.
In wireless power transfer systems, the relative positional misalignment between transmitting and receiving coils significantly impacts the system’s mutual inductance characteristics, thereby constraining the system’s output power stability and transmission efficiency optimization potential. Hence, accurate formulas for calculating mutual inductance are crucial for optimizing coil structures and achieving mutual inductance stability. This study focuses on the mutual inductance characteristics of rectangular coils under positional misalignment conditions in a dual-sided electromagnetic shielding environment. Initially, the research deduces the incident magnetic flux density induced by the current in rectangular coils through the dual Fourier transform and magnetic vector potential method. Subsequently, Maxwell’s equations and boundary conditions are employed to analytically examine the induced eddy currents within the shielding layer, allowing for the calculation of reflected magnetic flux density. Based on these analyses, the study derives a formula for mutual inductance using the magnetic flux density method. A prototype was built for experimental verification. The experiment results show that the maximum error between the measured mutual inductance and the calculated result is less than 3.8%, which verifies the feasibility and the accuracy of the proposed calculation method. Simulations and empirical validation demonstrate the superior accuracy and practicality of the proposed formula. This research not only offers an innovative technological pathway for enhancing the stability and efficiency of wireless power transfer systems but also provides a solid theoretical foundation and guiding framework for coil design and optimization. Full article
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21 pages, 2534 KiB  
Article
Research on Adhesion Characteristic Experiment of Carbon Particles in Transformer Oil on the Surface of Epoxy Resin Under DC Electric Field
by Jiarong Zhong, Zhanlong Zhang, Zijian Dong, Zhixuan Xue, Jiaqi Cheng, Jun Deng and Fan Wang
Appl. Sci. 2025, 15(1), 431; https://doi.org/10.3390/app15010431 (registering DOI) - 5 Jan 2025
Abstract
Transformer oil will inevitably be contaminated by impurity particles in the actual operation process; Carbon particles are the most abundant conductive particles in transformer oil. The adhesion behavior on the internal insulating surface will cause electric field distortion, which will pose a serious [...] Read more.
Transformer oil will inevitably be contaminated by impurity particles in the actual operation process; Carbon particles are the most abundant conductive particles in transformer oil. The adhesion behavior on the internal insulating surface will cause electric field distortion, which will pose a serious threat to the safe and stable operation of oil-immersed power equipment. To this end, this paper builds an experimental platform for simulating the adhesion behavior of carbon particles in transformer oil, studies the adhesion characteristics of carbon particles, and analyzes the influence of electric field, particle size, oil flow velocity, and other factors on the adhesion of carbon particles. The results show that: the DC electric field is the main factor driving the adhesion of carbon particles on the surface of epoxy resin (with the increase in electric field strength, the degree of adhesion of carbon particles firstly rises and then decreases); the smaller the size of the carbon particles, the easier it is to adhere, and the corresponding electric field strength is different for different sizes of carbon particles when the degree of adhesion is the largest; the velocity of the transformer oil will have a significant impact on the adhesion behavior of the carbon particles (with the increase in the flow velocity, the degree of adhesion of carbon particles firstly rises and then decreases). The research conclusion of this article is helpful in guiding the evaluation of insulation performance and the optimization of insulation structure design in the converter transformer valve-side bushing considering the phenomenon of particle adhesion. Full article
22 pages, 1185 KiB  
Article
Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks
by Hanjin Kim, Young-Jin Kim and Won-Tae Kim
Appl. Sci. 2025, 15(1), 428; https://doi.org/10.3390/app15010428 (registering DOI) - 5 Jan 2025
Abstract
The proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interference affects throughput, packet loss, and latency. This [...] Read more.
The proliferation of IoT using heterogeneous wireless technologies within the unlicensed spectrum has intensified cross-technology interference (CTI) in wireless local area networks (WLANs). As WLANs increasingly adopt time-triggered transmission methods to support real-time services, this interference affects throughput, packet loss, and latency. This paper presents a CTI-aware rate adaptation framework designed to mitigate interference in WLANs without direct coordination with heterogeneous wireless devices. The framework includes a CTI identification model and CTI-aware rate selection algorithms. Leveraging short-time Fourier transform, the identification model captures the time–frequency–power characteristics of CTI signals, enabling the estimation of the average power of various heterogeneous wireless technologies employed by interfering devices. The rate selection algorithms predict CTI occurrence times and adjust the transmission rate accordingly, enhancing the performance of existing explicit and implicit interference mitigation methods. Experimental results demonstrated that the lightweight CTI identification model accurately estimated the average power of each type with an error margin of ±1.414 dBm, achieving this in under 1 ms on the target hardware. Additionally, applying the proposed framework to explicit interference mitigation enhanced goodput by 20.67%, reduced packet error rate by 2.38%, and decreased the probability of packets exceeding 1 ms latency by 0.932% compared to conventional methods. Full article
(This article belongs to the Special Issue IoT and AI for Wireless Communications)
19 pages, 708 KiB  
Review
Menin Inhibitors: New Targeted Therapies for Specific Genetic Subtypes of Difficult-to-Treat Acute Leukemias
by Pasquale Niscola, Valentina Gianfelici, Marco Giovannini, Daniela Piccioni, Carla Mazzone and Paolo de Fabritiis
Cancers 2025, 17(1), 142; https://doi.org/10.3390/cancers17010142 (registering DOI) - 4 Jan 2025
Viewed by 283
Abstract
Menin (MEN1) is a well-recognized powerful tumor promoter in acute leukemias (AL) with KMT2A rearrangements (KMT2Ar, also known as MLL) and mutant nucleophosmin 1 (NPM1m) acute myeloid leukemia (AML). MEN1 is essential for sustaining leukemic transformation due to its interaction with wild-type KMT2A [...] Read more.
Menin (MEN1) is a well-recognized powerful tumor promoter in acute leukemias (AL) with KMT2A rearrangements (KMT2Ar, also known as MLL) and mutant nucleophosmin 1 (NPM1m) acute myeloid leukemia (AML). MEN1 is essential for sustaining leukemic transformation due to its interaction with wild-type KMT2A and KMT2A fusion proteins, leading to the dysregulation of KMT2A target genes. MEN1 inhibitors (MIs), such as revumenib, ziftomenib, and other active small molecules, represent a promising new class of therapies currently under clinical development. By disrupting the MEN1-KMT2Ar complex, a group of proteins involved in chromatin remodeling, MIs induce apoptosis and differentiation AL expressing KMT2Ar or NPM1m AML. Phase I and II clinical trials have evaluated MIs as standalone treatments and combined them with other synergistic drugs, yielding promising results. These trials have demonstrated notable response rates with manageable toxicities. Among MIs, ziftomenib received orphan drug and breakthrough therapy designations from the European Medicines Agency in January 2024 and the Food and Drug Administration (FDA) in April 2024, respectively, for treating R/R patients with NPM1m AML. Additionally, in November 2024, the FDA approved revumenib for treating R/R patients with KMT2Ar-AL. This review focuses on the pathophysiology of MI-sensitive AL, primarily AML. It illustrates data from clinical trials and discusses the emergence of resistance mechanisms. In addition, we outline future directions for the use of MIs and emphasize the need for further research to fully realize the potential of these novel compounds, especially in the context of specific genetic subtypes of challenging AL. Full article
(This article belongs to the Section Cancer Therapy)
22 pages, 12560 KiB  
Article
Resilient Waterfront Futures: Mapping Vulnerabilities and Designing Floating Urban Models for Flood Adaptation on the Tiber Delta
by Livia Calcagni, Adriano Ruggiero and Alessandra Battisti
Land 2025, 14(1), 87; https://doi.org/10.3390/land14010087 (registering DOI) - 4 Jan 2025
Viewed by 235
Abstract
This paper explores the feasibility of floating urban development in Italy, given its extensive coastline and inland hydrographic network. The key drivers for floating urban development, as an adaptive approach in low-lying waterfront areas, include the increasing threats posed by rising sea levels [...] Read more.
This paper explores the feasibility of floating urban development in Italy, given its extensive coastline and inland hydrographic network. The key drivers for floating urban development, as an adaptive approach in low-lying waterfront areas, include the increasing threats posed by rising sea levels and flooding and the shortage of land for urban expansion. However, as not all waterfront areas are suitable for floating urban development, a geographical analysis based on a thorough evaluation of multiple factors, including urban–economic parameters and climate-related variables, led to the identification of a specific area of the Lazio coast, the river Tiber Delta. A comprehensive urban mapping process provided a multifaceted geo-referenced information layer, including several climatic, urban, anthropic, and environmental parameters. Within the GIS environment, it is possible to extract and perform statistical analyses crucial for assessing the impact of flood and sea-level rise hazards, particularly regarding buildings and land cover. This process provides a robust framework for understanding the spatial dimensions of flood and sea-level rise impacts and supporting informed design-making. A research-by-design phase follows the simulation research and mapping process. Several design scenarios are developed aimed at regenerating this vulnerable area. These scenarios seek to transform its susceptibility to flooding into a resilient, adaptive, urban identity, offering climate-resilient housing solutions for a population currently residing in unauthorized, substandard housing within high flood-risk zones. This paper proposes a comprehensive analytical methodology for supporting the design process of floating urban development, given the highly determinant role of site-specificity in such a challenging and new urban development approach. Full article
(This article belongs to the Section Urban Contexts and Urban-Rural Interactions)
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15 pages, 4536 KiB  
Article
Research and Application of Interferogram Acquisition Method for Ground-Based Fourier-Transform Infrared Greenhouse Gas Spectrometer
by Yasong Deng, Liang Xu, Ling Jin, Yongfeng Sun, Lei Zhang, Jianguo Liu and Wenqing Liu
Photonics 2025, 12(1), 38; https://doi.org/10.3390/photonics12010038 (registering DOI) - 4 Jan 2025
Viewed by 218
Abstract
A high-performance data acquisition and processing system within a spectrometer provides a powerful guarantee for obtaining high-precision data in ground-based Fourier-transform infrared greenhouse-gas spectroscopy. Addressing the challenge of accurate interferogram sampling in Fourier-transform spectroscopy, a dual-channel interferogram acquisition method was designed. Dual-channel analog-to-digital [...] Read more.
A high-performance data acquisition and processing system within a spectrometer provides a powerful guarantee for obtaining high-precision data in ground-based Fourier-transform infrared greenhouse-gas spectroscopy. Addressing the challenge of accurate interferogram sampling in Fourier-transform spectroscopy, a dual-channel interferogram acquisition method was designed. Dual-channel analog-to-digital converters, acquiring interferograms at different gains, enable high dynamic range and high-resolution acquisition of infrared interferometric signals; the analog-to-digital converter channel of low-gain interferograms mainly captures data near the zero-optical-range-difference spike, and the analog-to-digital converter channel of high-gain interferograms mainly acquires the weak signals from the two flanks. The simulation results, circuit design, and correction method between the two channels of the method are given. Finally, in the ground-based Fourier-transform infrared greenhouse-gas spectrometer for experimental applications, the experiment shows that under the same measurement conditions, the carbon dioxide column concentration-measurement accuracy is improved by 2.096 times, and the dual-channel interferometric data acquisition method can significantly enhance the data retrieval accuracy. Full article
(This article belongs to the Special Issue Optical Sensing Technologies, Devices and Their Data Applications)
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27 pages, 1438 KiB  
Review
Metal-Based Catalysts in Biomass Transformation: From Plant Feedstocks to Renewable Fuels and Chemicals
by Muhammad Saeed Akhtar, Muhammad Tahir Naseem, Sajid Ali and Wajid Zaman
Catalysts 2025, 15(1), 40; https://doi.org/10.3390/catal15010040 (registering DOI) - 4 Jan 2025
Viewed by 270
Abstract
The transformation of biomass into renewable fuels and chemicals has gained remarkable attention as a sustainable alternative to fossil-based resources. Metal-based catalysts, encompassing transition and noble metals, are crucial in these transformations as they drive critical reactions, such as hydrodeoxygenation, hydrogenation, and reforming. [...] Read more.
The transformation of biomass into renewable fuels and chemicals has gained remarkable attention as a sustainable alternative to fossil-based resources. Metal-based catalysts, encompassing transition and noble metals, are crucial in these transformations as they drive critical reactions, such as hydrodeoxygenation, hydrogenation, and reforming. Transition metals, including nickel, cobalt, and iron, provide cost-effective solutions for large-scale processes, while noble metals, such as platinum and palladium, exhibit superior activity and selectivity for specific reactions. Catalytic advancements, including the development of hybrid and bimetallic systems, have further improved the efficiency, stability, and scalability of biomass transformation processes. This review highlights the catalytic upgrading of lignocellulosic, algal, and waste biomass into high-value platform chemicals, biofuels, and biopolymers, with a focus on processes, such as Fischer–Tropsch synthesis, aqueous-phase reforming, and catalytic cracking. Key challenges, including catalyst deactivation, economic feasibility, and environmental sustainability, are examined alongside emerging solutions, like AI-driven catalyst design and lifecycle analysis. By addressing these challenges and leveraging innovative technologies, metal-based catalysis can accelerate the transition to a circular bioeconomy, supporting global efforts to combat climate change and reduce fossil fuel dependence. Full article
(This article belongs to the Special Issue Catalytic Conversion of Biomass to Chemicals)
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23 pages, 26242 KiB  
Article
The Application of Fast Fourier Transform Filtering to High Spatial Resolution Digital Terrain Models Derived from LiDAR Sensors for the Objective Mapping of Surface Features and Digital Terrain Model Evaluations
by Alberto González-Díez, Ignacio Díaz-Martínez, Pablo Cruz-Hernández, Antonio Barreda-Argüeso and Matthew Doughty
Remote Sens. 2025, 17(1), 150; https://doi.org/10.3390/rs17010150 (registering DOI) - 4 Jan 2025
Viewed by 261
Abstract
In this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogenic landforms. The suitability [...] Read more.
In this paper, the application is investigated of fast Fourier transform filtering (FFT-FR) to high spatial resolution digital terrain models (HR-DTM) derived from LiDAR sensors, assessing its efficacy in identifying genuine relief elements, including both natural geological features and anthropogenic landforms. The suitability of the derived filtered geomorphic references (FGRs) is evaluated through spatial correlation with ground truths (GTs) extracted from the topographical and geological geodatabases of Santander Bay, Northern Spain. In this study, it is revealed that existing artefacts, derived from vegetation or human infrastructures, pose challenges in the units’ construction, and large physiographic units are better represented using low-pass filters, whereas detailed units are more accurately depicted with high-pass filters. The results indicate a propensity of high-frequency filters to detect anthropogenic elements within the DTM. The quality of GTs used for validation proves more critical than the geodatabase scale. Additionally, in this study, it is demonstrated that the footprint of buildings remains uneliminated, indicating that the model is a poorly refined digital surface model (DSM) rather than a true digital terrain model (DTM). Experiments validate the DTM’s capability to highlight contacts and constructions, with water detection showing high precision (≥60%) and varying precision for buildings. Large units are better captured with low filters, whilst high filters effectively detect anthropogenic elements and more detailed units. This facilitates the design of validation and correction procedures for DEMs derived from LiDAR point clouds, enhancing the potential for more accurate and objective Earth surface representation. Full article
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41 pages, 1344 KiB  
Article
Robust Position Control of a Knee-Joint Rehabilitation Exoskeleton Using a Linear Matrix Inequalities-Based Design Approach
by Sahar Jenhani, Hassène Gritli and Jyotindra Narayan
Appl. Sci. 2025, 15(1), 404; https://doi.org/10.3390/app15010404 (registering DOI) - 4 Jan 2025
Viewed by 327
Abstract
This study focuses on developing a control methodology for exoskeleton robots designed for lower limb rehabilitation, specifically addressing the needs of elderly individuals and pediatric therapy. The approach centers on implementing an affine state-feedback controller to effectively regulate and stabilize the knee-joint exoskeleton [...] Read more.
This study focuses on developing a control methodology for exoskeleton robots designed for lower limb rehabilitation, specifically addressing the needs of elderly individuals and pediatric therapy. The approach centers on implementing an affine state-feedback controller to effectively regulate and stabilize the knee-joint exoskeleton robot at a desired position. The robot’s dynamics are nonlinear, accounting for unknown parameters, solid and viscous frictions, and external disturbances. To ensure robust stabilization, the Lyapunov approach is utilized to derive a set of Linear Matrix Inequality (LMI) conditions, guaranteeing the stability of the position error. The derivation of these LMI conditions is grounded in a comprehensive theoretical framework that employs advanced mathematical tools, including the matrix inversion lemma, Young’s inequality, the Schur complement, the S-procedure, and specific congruence transformations. Simulation results are presented to validate the proposed LMI conditions, demonstrating the effectiveness of the control strategy in achieving robust and accurate positioning of the lower limb rehabilitation exoskeleton robotic system. Full article
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26 pages, 9098 KiB  
Article
Deep Learning-Based Pointer Meter Reading Recognition for Advancing Manufacturing Digital Transformation Research
by Xiang Li, Jun Zhao, Changchang Zeng, Yong Yao, Sen Zhang and Suixian Yang
Sensors 2025, 25(1), 244; https://doi.org/10.3390/s25010244 - 3 Jan 2025
Viewed by 223
Abstract
With the digital transformation of the manufacturing industry, data monitoring and collecting in the manufacturing process become essential. Pointer meter reading recognition (PMRR) is a key element in data monitoring throughout the manufacturing process. However, existing PMRR methods have low accuracy and insufficient [...] Read more.
With the digital transformation of the manufacturing industry, data monitoring and collecting in the manufacturing process become essential. Pointer meter reading recognition (PMRR) is a key element in data monitoring throughout the manufacturing process. However, existing PMRR methods have low accuracy and insufficient robustness due to issues such as blur, uneven illumination, tilt, and complex backgrounds in meter images. To address these challenges, we propose an end-to-end PMRR method based on a decoupled circle head detection algorithm (YOLOX-DC) and a Unet-like pure Transformer segmentation network (PM-SwinUnet). First, according to the characteristics of the pointer dial, the YOLOX-DC detection algorithm is designed based on the exceeding you only look once detector (YOLOX). The decoupled circle head of YOLOX-DC detects the pointer meter dial more accurately than the commonly used rectangular detection head. Second, the window multi-head attention of the PM-SwinUnet network enhances the feature extraction ability of pointer meter images and solves problems of missed scale detection and incomplete pointer segmentation. Additionally, the scale and pointer fitting module is introduced into the PM-SwinUnet to locate the accurate position of the scale and pointer. Finally, through the angle relationship between the pointer and the first two main scale lines, the pointer meter reading is accurately calculated by the improved angle method. Experimental results demonstrate the effectiveness and superiority of the proposed end-to-end method across three-pointer meter datasets. Furthermore, it provides a rapid and robust approach to the digital transformation of manufacturing systems. Full article
39 pages, 7214 KiB  
Article
A Deep Learning-Based Approach for the Detection of Various Internet of Things Intrusion Attacks Through Optical Networks
by Nouman Imtiaz, Abdul Wahid, Syed Zain Ul Abideen, Mian Muhammad Kamal, Nabila Sehito, Salahuddin Khan, Bal S. Virdee, Lida Kouhalvandi and Mohammad Alibakhshikenari
Photonics 2025, 12(1), 35; https://doi.org/10.3390/photonics12010035 - 3 Jan 2025
Viewed by 350
Abstract
The widespread use of the Internet of Things (IoT) has led to significant breakthroughs in various fields but has also exposed critical vulnerabilities to evolving cybersecurity threats. Current Intrusion Detection Systems (IDSs) often fail to provide real-time detection, scalability, and interpretability, particularly in [...] Read more.
The widespread use of the Internet of Things (IoT) has led to significant breakthroughs in various fields but has also exposed critical vulnerabilities to evolving cybersecurity threats. Current Intrusion Detection Systems (IDSs) often fail to provide real-time detection, scalability, and interpretability, particularly in high-speed optical network environments. This research introduces XIoT, which is a novel explainable IoT attack detection model designed to address these challenges. Leveraging advanced deep learning methods, specifically Convolutional Neural Networks (CNNs), XIoT analyzes spectrogram images transformed from IoT network traffic data to detect subtle and complex attack patterns. Unlike traditional approaches, XIoT emphasizes interpretability by integrating explainable AI mechanisms, enabling cybersecurity analysts to understand and trust its predictions. By offering actionable insights into the factors driving its decision making, XIoT supports informed responses to cyber threats. Furthermore, the model’s architecture leverages the high-speed, low-latency characteristics of optical networks, ensuring the efficient processing of large-scale IoT data streams and supporting real-time detection in diverse IoT ecosystems. Comprehensive experiments on benchmark datasets, including KDD CUP99, UNSW NB15, and Bot-IoT, demonstrate XIoT’s exceptional accuracy rates of 99.34%, 99.61%, and 99.21%, respectively, significantly surpassing existing methods in both accuracy and interpretability. These results highlight XIoT’s capability to enhance IoT security by addressing real-world challenges, ensuring robust, scalable, and interpretable protection for IoT networks against sophisticated cyber threats. Full article
(This article belongs to the Special Issue Optical Wireless Communication in 5G and Beyond)
57 pages, 3601 KiB  
Review
A Comprehensive Exploration of 6G Wireless Communication Technologies
by Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Shahriar Uzzal and H. M. Dipu Kabir
Computers 2025, 14(1), 15; https://doi.org/10.3390/computers14010015 - 3 Jan 2025
Viewed by 196
Abstract
As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, [...] Read more.
As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory toward 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts toward superconvergence, non-IP-based networking protocols, and information-centric networks, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into the core of 6G, we articulate a systematic exploration of the key technologies earmarked to revolutionize wireless communication including terahertz (THz) waves, optical wireless technology, and dynamic spectrum management while elucidating the intricate trade-offs necessitated by the integration of such innovations. This paper not only lays out a comprehensive 6G vision accentuated by high security, affordability, and intelligence but also charts the course for addressing the pivotal challenges of spectrum efficiency, energy consumption, and the seamless integration of emerging technologies. In this study, our goal is to enrich the existing discussions and research efforts by providing comprehensive insights into the development of 6G technology, ultimately supporting the creation of a thoroughly connected future world that meets evolving demands. Full article
34 pages, 2720 KiB  
Review
A Comprehensive Review and Analysis of the Design Aspects,Structure, and Applications of Flexible Wearable Antennas
by Sunaina Singh, Ranjan Mishra, Ankush Kapoor and Soni Singh
Telecom 2025, 6(1), 3; https://doi.org/10.3390/telecom6010003 - 3 Jan 2025
Viewed by 339
Abstract
This review provides a comprehensive analysis of the design, materials, fabrication techniques, and applications of flexible wearable antennas, with a primary focus on their roles in Wireless Body Area Networks (WBANs) and healthcare technologies. Wearable antennas are increasingly vital for applications that require [...] Read more.
This review provides a comprehensive analysis of the design, materials, fabrication techniques, and applications of flexible wearable antennas, with a primary focus on their roles in Wireless Body Area Networks (WBANs) and healthcare technologies. Wearable antennas are increasingly vital for applications that require seamless integration with the human body while maintaining optimal performance under deformation and environmental stress. Return loss, gain, bandwidth, efficiency, and the SAR are some of the most important parameters that define the performance of an antenna. Their interactions with human tissues are also studied in greater detail. Such studies are essential to ensure that wearable and body-centric communication systems perform optimally, remain safe, and are in compliance with regulatory standards. Advanced materials, including textiles, polymers, and conductive composites, are analyzed for their electromagnetic properties and mechanical resilience. This study also explores innovative fabrication techniques, such as inkjet printing, screen printing, and embroidery, which enable scalable and cost-effective production. Additionally, solutions for SAR optimization, including the use of metamaterials, electromagnetic band gap (EBG) structures, and frequency-selective surfaces (FSSs), are discussed. This review highlights the transformative potential of wearable antennas in healthcare, the IoT, and next-generation communication systems, emphasizing their adaptability for real-time monitoring and advanced wireless technologies, such as 5G and 6G. The integration of energy harvesting, biocompatible materials, and sustainable manufacturing processes is identified as a future direction, paving the way for wearable antennas to become integral to the evolution of smart healthcare and connected systems. Full article
27 pages, 1100 KiB  
Review
Use of Nicotinamide Mononucleotide as Non-Natural Cofactor
by Tahseena Naaz and Beom Soo Kim
Catalysts 2025, 15(1), 37; https://doi.org/10.3390/catal15010037 - 3 Jan 2025
Viewed by 291
Abstract
Nicotinamide mononucleotide (NMN) has emerged as a promising non-natural cofactor with significant potential to transform biocatalysis, synthetic biology, and therapeutic applications. By modulating NAD⁺ metabolism, NMN offers unique advantages in enzymatic reactions, metabolic engineering, and regenerative medicine. This review provides a comprehensive analysis [...] Read more.
Nicotinamide mononucleotide (NMN) has emerged as a promising non-natural cofactor with significant potential to transform biocatalysis, synthetic biology, and therapeutic applications. By modulating NAD⁺ metabolism, NMN offers unique advantages in enzymatic reactions, metabolic engineering, and regenerative medicine. This review provides a comprehensive analysis of NMN’s biochemical properties, mechanisms of action, and diverse applications. Emphasis is placed on its role in addressing challenges in multi-enzyme cascades, biofuel production, and the synthesis of high-value chemicals. The paper also highlights critical research gaps, including the need for scalable NMN synthesis methods, improved integration into enzymatic systems, and comprehensive toxicity studies for therapeutic use. Emerging technologies such as AI-driven enzyme design and CRISPR-based genome engineering are discussed as transformative tools for optimizing NMN-dependent pathways. Furthermore, the synergistic potential of NMN with synthetic biology innovations, such as cell-free systems and dynamic regulatory networks, is explored, paving the way for precise and modular biotechnological solutions. Looking forward, NMN’s versatility as a cofactor positions it as a pivotal tool in advancing sustainable bioprocessing and precision medicine. Addressing current limitations through interdisciplinary approaches will enable NMN to redefine the boundaries of metabolic engineering and therapeutic innovation. This review serves as a roadmap for leveraging NMN’s potential across diverse scientific and industrial domains. Full article
(This article belongs to the Special Issue Feature Review Papers in Biocatalysis and Enzyme Engineering)
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14 pages, 1654 KiB  
Article
Effect of Geometry on the Dissolution Behaviour of Complex Additively Manufactured Tablets
by Seyedebrahim Afkhami, Meisam Abdi and Reza Baserinia
J. Manuf. Mater. Process. 2025, 9(1), 11; https://doi.org/10.3390/jmmp9010011 - 3 Jan 2025
Viewed by 268
Abstract
Additive manufacturing (AM) processes, such as fused deposition modelling (FDM), have emerged as transformative technologies in pharmaceutical manufacturing, enabling the production of drug delivery systems with complex and customised geometries. These advancements provide precise control over drug release profiles and facilitate the development [...] Read more.
Additive manufacturing (AM) processes, such as fused deposition modelling (FDM), have emerged as transformative technologies in pharmaceutical manufacturing, enabling the production of drug delivery systems with complex and customised geometries. These advancements provide precise control over drug release profiles and facilitate the development of patient-specific medicines. This study investigates the dissolution behaviour of AM-fabricated tablets made from polyvinyl alcohol (PVA), a hydrophilic and biocompatible polymer widely used in drug delivery systems. The influence of the initial mass, surface area, and surface-area-to-volume ratio (S/V) on dissolution kinetics is evaluated for tablets with intricate geometries. Our findings demonstrate that these parameters, while critical for conventional tablet shapes, are insufficient to fully predict the dissolution behaviour of complex geometries. Furthermore, this study highlights how geometric modifications can enable the administration of the same drug dosage through sustained or immediate release profiles, offering enhanced versatility in drug delivery. By leveraging the geometric design freedom provided by AM technologies, this research underscores the potential for optimising drug delivery systems to improve therapeutic outcomes and patient compliance. Full article
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