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Nowadays, metamaterial absorbers still suffer from limited bandwidth, poor bandwidth scalability, and insufficient modulation depth. In order to solve this series of problems, we propose a metamaterial absorber based on graphene, VO2, gallium silver sulfide, and gold-silver alloy composites with dual-control modulation of temperature and electric field. Then we further investigate the optical switching performance of this absorber in this work. Our proposed metamaterial absorber has the advantages of broad absorption bandwidth, sufficient modulation depth, and good bandwidth scalability all together. Unlike the single inspired layer of previous designs, we innovatively adopted a multi-layer excitation structure, which can realize the purpose of absorption and bandwidth width regulation by a variety of means. Combined with the finite element analysis method, our proposed metamaterial absorber has excellent bandwidth scalability, which can be tuned from 2.7 THz bandwidth to 12.1 THz bandwidth by external electrothermal excitation. Meanwhile, the metamaterial absorber can also dynamically modulate the absorption from 3.8% to 99.8% at a wide incidence angle over the entire range of polarization angles, suggesting important potential applications in the field of optical switching in the terahertz range.

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This paper introduces an approach to select the bandwidth or smoothing parameter in multiresolution (MR) density estimation and nonparametric density estimation. It is based on the evolution of the second, third and fourth central moments and the shape of the estimated densities for different bandwidths and resolution levels. The proposed method has been applied to density estimation by means of multiresolution densities as well as kernel density estimation (MRDE and KDE respectively). The results of the simulations and the empirical application demonstrate that the level of resolution resulting from the moments method performs better with multimodal densities than the Bayesian Information Criterion (BIC) for multiresolution densities estimation and the plug-in for kernel densities estimation.

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The time-varying kernel density estimation relies on two free parameters: the bandwidth and the discount factor. We propose to select these parameters so as to minimize a criterion consistent with the traditional requirements of the validation of a probability density forecast. These requirements are both the uniformity and the independence of the so-called probability integral transforms, which are the forecast time-varying cumulated distributions applied to the observations. We thus build a new numerical criterion incorporating both the uniformity and independence properties by the mean of an adapted Kolmogorov-Smirnov statistic. We apply this method to financial markets during the onset of the COVID-19 crisis. We determine the time-varying density of daily price returns of several stock indices and, using various divergence statistics, we are able to describe the chronology of the crisis as well as regional disparities. For instance, we observe a more limited impact of COVID-19 on financial markets in China, a strong impact in the US, and a slow recovery in Europe.

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High-temperature ultrasonic transducer (HTUT) is essential for non-destructive testing (NDT) in harsh environments. In this paper, a HTUT based on BiScO3-PbTiO3 (BS-PT) piezoelectric ceramics was developed, and the effect of different backing layers on its bandwidth were analyzed. The HTUT demonstrates a broad bandwidth and excellent thermal stability with operation temperature up to 400 °C. By using a 10 mm thick porous alumina backing layer, the HTUT achieves a broad -6 dB bandwidth of 100 %, which is about 4 times superior to the transducer with an air backing layer. The center frequency (fc) of the HTUT remains stable with fluctuations of less than 10 % across the temperature range from room temperature to 400 °C. The HTUT successfully detected simulated defects in pulse-echo mode for NDT over 200 °C. This research not only advances high-temperature ultrasonic transducer technology but also expands the NDT applications in harsh environmental conditions.

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Federated Learning (FL) is a decentralized machine learning method in which individual devices compute local models based on their data. In FL, devices periodically share newly trained updates with the central server, rather than submitting their raw data. The key characteristics of FL, including on-device training and aggregation, make it interesting for many communication domains. Moreover, the potential of new systems facilitating FL in sixth generation (6G) enabled Passive Optical Networks (PON), presents a promising opportunity for integration within this domain. This article focuses on the interaction between FL and PON, exploring approaches for effective bandwidth management, particularly in addressing the complexity introduced by FL traffic. In the PON standard, advanced bandwidth management is proposed by allocating multiple upstream grants utilizing the Dynamic Bandwidth Allocation (DBA) algorithm to be allocated for an Optical Network Unit (ONU). However, there is a lack of research on studying the utilization of multiple grant allocation. In this paper, we address this limitation by introducing a novel DBA approach that efficiently allocates PON bandwidth for FL traffic generation and demonstrates how multiple grants can benefit from the enhanced capacity of implementing PON in carrying out FL flows. Simulations conducted in this study show that the proposed solution outperforms state-of-the-art solutions in several network performance metrics, particularly in reducing upstream delay. This improvement holds great promise for enabling real-time data-intensive services that will be key components of 6G environments. Furthermore, our discussion outlines the potential for the integration of FL and PON as an operational reality capable of supporting 6G networking.

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Advancements in assisted driving technologies are expected to enable future passengers to use a wide range of multimedia applications in electric vehicles (EVs). To address the bandwidth demands for high-resolution and immersive videos during peak traffic, this study introduces a bandwidth-management algorithm to support differentiated streaming services in heterogeneous vehicle-to-everything (V2X) networks. By leveraging cellular 6G base stations, along with Cell-Free (CF) Massive Multi-Input Multi-Output (mMIMO) Wi-Fi 7 access points, the algorithm aims to provide a high-coverage, high-speed, and low-interference V2X network environment. Additionally, Li-Fi technology is employed to supply extra bandwidth to vehicles with limited connectivity via V2V communication. Importantly, the study addresses the urgency and prioritization of different applications to ensure the smooth execution of emergency applications and introduces a pre-downloading mechanism specifically for non-real-time applications. Through simulations, the algorithm's effectiveness in meeting EV users' bandwidth needs for various multimedia streaming applications is demonstrated. During peak-bandwidth-demand periods, users experienced an average increase in bandwidth of 47%. Furthermore, bandwidth utilization across the V2X landscape is significantly improved.

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The rapid advancement of technology has greatly expanded the capabilities of unmanned aerial vehicles (UAVs) in wireless communication and edge computing domains. The primary objective of UAVs is the seamless transfer of video data streams to emergency responders. However, live video data streaming is inherently latency dependent, wherein the value of the video frames diminishes with any delay in the stream. This becomes particularly critical during emergencies, where live video streaming provides vital information about the current conditions. Edge computing seeks to address this latency issue in live video streaming by bringing computing resources closer to users. Nonetheless, the mobile nature of UAVs necessitates additional trajectory supervision alongside the management of computation and networking resources. Consequently, efficient system optimization is required to maximize the overall effectiveness of the collaborative system with limited UAV resources. This study explores a scenario where multiple UAVs collaborate with end users and edge servers to establish an emergency response system. The proposed idea takes a comprehensive approach by considering the entire emergency response system from the incident site to video distribution at the user level. It includes an adaptive resource management strategy, leveraging deep reinforcement learning by simultaneously addressing video streaming latency, UAV and user mobility factors, and varied bandwidth resources.

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Shuffling-type gradient method is a popular machine learning algorithm that solves finite-sum optimization problems by randomly shuffling samples during iterations. In this paper, we explore the convergence properties of shuffling-type gradient method under mild assumptions. Specifically, we employ the bandwidth-based step size strategy that covers both monotonic and non-monotonic step sizes, thereby providing a unified convergence guarantee in terms of step size. Additionally, we replace the lower bound assumption of the objective function with that of the loss function, thereby eliminating the restrictions on the variance and the second-order moment of stochastic gradient that are difficult to verify in practice. For non-convex objectives, we recover the last iteration convergence of shuffling-type gradient algorithm with a less cumbersome proof. Meanwhile, we also establish the convergence rate for the minimum iteration of gradient norms. Under the Polyak-Lojasiewicz (PL) condition, we prove that the function value of last iteration converges to the lower bound of the objective function. By selecting appropriate boundary functions, we further improve the previous sublinear convergence rate results. Overall, this paper contributes to the understanding of shuffling-type gradient method and its convergence properties, providing insights for optimizing finite-sum problems in machine learning. Finally, numerical experiments demonstrate the efficiency of shuffling-type gradient method with bandwidth-based step size and validate our theoretical results.

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Communication systems need antennas with wide bandwidths to provide large throughput, while imaging radars benefit from high gain for increased range and wide bandwidths for high-resolution imaging. This paper presents the design and evaluation of a wideband, high-gain antenna that achieves an average gain of 9.7 dBi over a bandwidth of 1.49 GHz to 3.92 GHz by using multiple in-phase radiating apertures. The antenna has a unique structure with a central rectangular short-circuited patch sandwiched between two back-to-back U-shaped radiating patches and two flanking H-shaped short-circuited patches. Each of the U-shaped patches employs a coplanar waveguide as feeding to achieve ultra-wideband impedance matching. Benefiting from design arrangement, in-phase electrical field distributions appear at the gaps between the patches that result in equivalent radiating magnetic currents in the same direction. Theory analysis shows that the close-spaced, same-direction magnetic currents created by the radiating apertures intensify the radiation and increase antenna gain within its impedance bandwidth. Simulated data show that the use of the coplanar waveguide feeding and short-circuited patches increase the bandwidth from 65 MHz to 2.43 GHz. Moreover, the short-circuited patches increase the gain by 3.45 dB at 2.4 GHz. Simulation and measurement results validate the design and show that the antenna features a maximum gain of 11.3 dBi and an average gain of 9.7 dBi in a fractional bandwidth of 89.8%. Because of the high gain values and the wide bandwidth, the antenna is particularly suited for long-range communication systems and high-resolution radar applications.

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GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. However, edge devices present severe computing power and energy limitations. In this context, the use of remote GPU virtualization solutions is an efficient way to address these concerns. Nevertheless, the limited network bandwidth might be an issue. This limitation can be alleviated by leveraging on-the-fly compression within the communication layer of remote GPU virtualization solutions. In this way, data exchanged with the remote GPU is transparently compressed before being transmitted, thus increasing network bandwidth in practice. In this paper, we present the implementation of a parallel compression pipeline designed to be used within remote GPU virtualization solutions. A thorough performance analysis shows that network bandwidth can be increased by a factor of up to 2×.

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Delving into the intricate interplay between spin-orbit coupling and Coulomb correlations in strongly correlated oxides, particularly perovskite compounds, has unveiled a rich landscape of exotic phenomena ranging from unconventional superconductivity to the emergence of topological phases. In this study, we have employed pulsed laser deposition technique to grow SrIrO3(SIO) thin films on SrTiO3substrates, systematically varying the oxygen content during the post-deposition annealing. X-ray photoelectron spectroscopy (XPS) provided insights into the stoichiometry and spin-orbit splitting energy of Iridium within the SIO film, while high-resolution x-ray studies meticulously examined the structural integrity of the thin films. Remarkably, our findings indicate a decrease in the metallicity of SIO thin films with reduced annealing O2partial pressure. Furthermore, we carried out magneto-transport studies on the SIO thin films, the results revealed intriguing insights into spin transport as a function of oxygen content. The tunability of the electronic band structure of SIO films with varying oxygen vacancy is correlated with the density functional theory calculations. Our findings elucidate the intricate mechanisms dictating spin transport properties in SIO thin films, offering invaluable guidance for the design and optimization of spintronic devices based on complex oxide materials. Notably, the ability to tune bandwidth by varying post-annealing oxygen partial pressure in iridate-based spintronic materials holds significant promise for advancing technological applications in the spintronics domain.

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I-III-VI type semiconductor nanocrystals (NCs) have attracted considerable attention due to their environmental friendly nature and large-scale tunable emission. Herein, we report the successful synthesis of full-spectrum (470 to 614 nm) Ag-In-Ga-Zn-S (AIGZS) NCs by precisely regulating the In/Ga ratios using a facile one-pot method. Intriguingly, the photoluminescence (PL) peak width exhibits a continuous narrowing trend with extended reaction time, ultimately reaching a full width at half-maximum (fwhm) of 34 nm for green AIGZS NCs. Furthermore, the exciton relaxation dynamics of AIGZS NCs were systematically investigated using time-resolved photoluminescence and femtosecond transient absorption spectroscopy. Remarkably, we successfully fabricated blue, green, and red quantum-dot light-emitting diodes (QLEDs), forecasting the potential of AIGZS NCs with high color purity for applications in full-spectrum QLEDs.

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A broadband absorber based on metamaterials of graphene and vanadium dioxide (VO2) is proposed and investigated in the terahertz (THz) regime, which can be used for switch applications with a dynamically variable bandwidth by electrically and thermally controlling the Fermi energy level of graphene and the conductivity of VO2, respectively. The proposed absorber turns 'on' from 1.5 to 5.4 THz, with the modulation depth reaching 97.1% and the absorptance exceeding 90% when the Fermi energy levels of graphene are set as 0.7 eV, and VO2 is in the metallic phase. On the contrary, the absorptance is close to zero and the absorber turns 'off' with the Fermi energy level setting at 0 eV and VO2 in the insulating phase. Furthermore, other four broadband absorption modes can be achieved utilizing the active materials graphene and VO2. The proposed terahertz absorber may benefit the areas of broadband switch, cloaking objects, THz communications and other applications.

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The acoustically actuated nanomechanical magnetoelectric (ME) antennas represent a promising new technology that can significantly reduce antenna size by 1-2 orders of magnitude compared to traditional antennas. However, current ME antennas face challenges such as low antenna gain and narrow operating bandwidth, limiting their engineering applications. In this paper, we enhance the bandwidth and radiation performance of ME antennas through structural optimization, leveraging theoretical analysis and numerical simulations. Our findings indicate that optimizing the inner diameter of the ring-shaped ME antenna can elevate the average stress of the magnetic layer, leading to improved radiation performance and bandwidth compared to circular ME antennas. We establish an optimization model for the radiation performance of the ME antenna and conduct shape optimization simulations using COMSOL Multiphysics. The results of the Multiphysics field optimization align with the stress concentration theory, demonstrating a strong correlation between the radiation performance and bandwidth of the ME antenna with the average stress of the magnetic film. The resonant frequency in the thickness vibration mode is determined to be 170 MHz. Furthermore, shape optimization can enhance the bandwidth by up to 104% compared to circular ME antenna structures of the same size.

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A dual-polarized compact Vivaldi antenna with high gain performance is proposed for tree radar applications. The proposed design introduces an array configuration consisting of two pairs of two Vivaldi elements to optimize the operating bandwidth and gain while providing dual-polarization capability. To enhance the gain of the proposed antenna over a certain frequency range of interest, directors and edge slots are incorporated into each Vivaldi element. To further enhance the overall antenna gain, a metal back reflector is used. The measurement results of the fabricated antenna show that the proposed antenna achieves a high gain of 5.5 to 14.8 dBi over broadband from 0.5 GHz to 3 GHz. Moreover, it achieves cross-polarization discrimination larger than 20 dB, ensuring high polarization purity. The fabricated antenna is used to detect and image the defects inside tree trunks. The results show that the proposed antenna yields a better-migrated image with a clear defect region compared to that obtained by a commercial Horn antenna.

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The integration of microfluidics with electric field control, commonly referred to as electrofluidics, has led to new opportunities for biomedical analysis. The requirement for closed microcapillary channels in microfluidics, typically formed via complex microlithographic fabrication approaches, limits the direct accessibility to the separation processes during conventional electrofluidic devices. Textile structures provide an alternative and low-cost approach to overcome these limitations via providing open and surface-accessible capillary channels. Herein, we investigate the potential of different 3D textile structures for electrofluidics. In this study, 12 polyester yarns were braided around nylon monofilament cores of different diameters to produce functional 3D core-shell textile structures. Capillary electrophoresis performances of these 3D core-shell textile structures both before and after removing the nylon core were evaluated in terms of mobility and bandwidth of a fluorescence marker compound. It was shown that the fibre arrangement and density govern the inherent capillary formation within these textile structures which also impacts upon the solute analyte mobility and separation bandwidth during electrophoretic studies. Core-shell textile structures with a 0.47 mm nylon core exhibited the highest fluorescein mobility and presented a narrower separation bandwidth. This optimal textile structure was readily converted to different geometries via a simple heat-setting of the central nylon core. This approach can be used to fabricate an array of miniaturized devices that possess many of the basic functionalities required in electrofluidics while maintaining open surface access that is otherwise impractical in classical approaches.

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This paper presents the design of a 60 GHz millimeter-wave (MMW) slot array horn antenna based on the substrate-integrated waveguide (SIW) structure. The novelty of this device resides in the achievement of a broad impedance bandwidth and high gain performance by meticulously engineering the radiation band structure and slot array. The antenna demonstrates an impressive impedance bandwidth of 14.96 GHz (24.93%), accompanied by a remarkable maximum reflection coefficient of -39.47 dB. Furthermore, the antenna boasts a gain of 10.01 dBi, showcasing its outstanding performance as a high-frequency antenna with a wide bandwidth and high gain. To validate its capabilities, we fabricated and experimentally characterized a prototype of the antenna using a probe test structure. The measurement results closely align with the simulation results, affirming the suitability of the designed antenna for radar sensing applications in future global industrial scenarios.

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In this paper, we investigate a scenario in which protected and unprotected services coexist in an elastic optical network under dynamic traffic. In the investigated scenario, unprotected services can reuse the reserved idle bandwidth to provide protection to the protected services. Under this scenario, we propose a new heuristic algorithm that enables such reuse as well as define and introduce a new assignment problem in elastic optical networks, named a Transmission Spectrum Assignment (T-SA) problem. In this paper, we consider a scenario in which services may be routed using the multipath routing approach. Additionally, protection using bandwidth squeezing is also considered. We assess our proposal through simulations on three different network topologies and compare our proposal against the classical protection approach, in which bandwidth reuse is not allowed. For the simulated range of network loads, the maximum (minimum) blocking probability reduction obtained by our proposal is approximately 48% (10%) in the European topology, 46% (7%) in the NSFNET topology, and 32% (6%) in the German topology.

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Polarization-insensitive semiconductor optical amplifiers (SOAs) in all-optical networks can improve the signal-light quality and transmission rate. Herein, to reduce the gain sensitivity to polarization, a multi-quantum-well SOA in the 1550 nm band is designed, simulated, and developed. The active region mainly comprises the quaternary compound InGaAlAs, as differences in the potential barriers and wells of the components cause lattice mismatch. Consequently, a strained quantum well is generated, providing the SOA with gain insensitivity to the polarization state of light. In simulations, the SOA with ridge widths of 4 µm, 5 µm, and 6 µm is investigated. A 3 dB gain bandwidth of >140 nm is achieved with a 4 µm ridge width, whereas a 6 µm ridge width provides more output power and gain. The saturated output power is 150 mW (21.76 dB gain) at an input power of 0 dBm but increases to 233 mW (13.67 dB gain) at an input power of 10 dBm. The polarization sensitivity is <3 dBm at -20 dBm. This design, which achieves low polarization sensitivity, a wide gain bandwidth, and high gain, will be applicable in a wide range of fields following further optimization.

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The paper presents a wide-bandwidth, low-polarization semiconductor optical amplifier (SOA) based on strained quantum wells. By enhancing the material gain of quantum wells for TM modes, we have extended the gain bandwidth of the SOA while reducing its polarization sensitivity. Through a combination of tilted waveguide design and cavity surface optical thin film design, we have effectively reduced the cavity surface reflectance of the SOA, thus decreasing device transmission losses and noise figure. At a wavelength of 1550 nm and a drive current of 1.4 A, the output power can reach 188 mW, with a small signal gain of 36.4 dB and a 3 dB gain bandwidth of 128 nm. The linewidth broadening is only 1.032 times. The polarization-dependent gain of the SOA is below 1.4 dB, and the noise figure is below 5.5 dB. The device employs only I-line lithography technology, offering simple fabrication processes and low costs yet delivering outstanding and stable performance. The designed SOA achieves wide gain bandwidth, high gain, low polarization sensitivity, low linewidth broadening, and low noise, promising significant applications in the wide-bandwidth optical communication field across the S + C + L bands.