Search Results (1,294)

Three-dimensional object detection based on the fusion of millimeter-wave radar and cameras is increasingly gaining attention due to characteristics of low cost, high accuracy, and strong robustness. Recently, the bird’s eye view (BEV) fusion paradigm has dominated radar–camera fusion-based 3D object detection methods. In the BEV fusion paradigm, the detection accuracy is jointly determined by the precision of both image BEV features and radar BEV features. The precision of image BEV features is significantly influenced by depth estimation accuracy, whereas estimating depth from a monocular image is naturally a challenging, ill-posed problem. In this article, we propose a novel approach to enhance depth estimation accuracy by fusing camera perspective view (PV) features and radar perspective view features, thereby improving the precision of image BEV features. The refined image BEV features are then fused with radar BEV features to achieve more accurate 3D object detection results. To realize PV fusion, we designed a radar image generation module based on radar cross-section (RCS) and depth information, accurately projecting radar data into the camera view to generate radar images. The radar images are used to extract radar PV features. We present a cross-modal feature fusion module using the attention mechanism to dynamically fuse radar PV features with camera PV features. Comprehensive evaluations on the nuScenes 3D object detection dataset demonstrate that the proposed dual-view fusion paradigm outperforms the BEV fusion paradigm, achieving state-of-the-art performance with 64.2 NDS and 56.3 mAP. Full article

This research aims to actively suppress vibrations at the end-effector of a flexible manipulator. When configured in a locked state, the system behaves as a two-link manipulator subjected to disturbances on the first link. To analyze its behavior, Finite Element Analysis (FEA) is employed to extract the natural frequencies (eigenvalues) and corresponding mode shapes (eigenvectors) of a two-link, two-joint flexible manipulator (2L2JM). The obtained eigenvectors are transformed into uncoupled state-space equations using balanced realization and the Match-DC-Gain model reduction algorithm. An H-infinity controller is then designed and applied to both the full-order and reduced-order models of the manipulator. The objective of this study is to validate an analytical framework through FEA, demonstrating its applicability to complex manipulators with multiple joints and flexible links. Given that the full state-space representation typically results in high-dimensional matrices, model reduction enables effective vibration control with a minimal number of states. The derivation of the 2L2JM state space, its model reduction, and a subsequent control strategy have not been previously addressed in this manner. Simulation results showcasing vibration suppression of a cantilever beam are presented and benchmarked against two alternative modeling approaches. Full article

Gallium nitride high electron mobility transistors (GaN HEMTs), characterized by their extremely high switching speeds and superior high-frequency performance, have demonstrated significant advantages, and gained extensive applications in fields such as aerospace and high-power-density power supplies. However, their unique internal architecture renders these devices highly sensitive to circuit parasitic parameters. Conventional circuit design methodologies often induce severe issues such as overshoot and high-frequency oscillations, which significantly constrain the realization of their high-frequency performance. To solve this problem, this paper investigates the nonlinear dynamic behavior of GaN HEMTs during switching transients by establishing an equivalent impedance model. Based on this model, a detailed analysis is implemented to elucidate the mechanism by which RC Snubber circuits influence the system’s resonance frequency and the amplitude at the resonant frequency. Through this analysis, an optimal RC Snubber circuit parameter is derived, enabling effective suppression of high-frequency oscillations during the switching transient of GaN HEMT. Experimental results demonstrate that the proposed design achieves a maximum reduction of 40% in voltage overshoot, shortens the ringing time to one-twentieth of the original value, and suppresses noise by 20 dB in the high-frequency range of 20 MHz to 30 MHz, thereby significantly enhancing the stability and reliability of circuit operation. Additionally, considering the heat dissipation requirements in high power density scenarios, this work optimizes the layout of devices, and heat sinks to maintain operational temperatures within safe limits, further mitigating the impact of parasitic parameters on overall system performance. Full article

Future wireless networks are expected to deliver enhanced spectral efficiency while being energy efficient. MIMO and other non-orthogonal transmission schemes, such as non-orthogonal multiple access (NOMA), offer substantial theoretical spectral efficiency gains. However, these gains have yet to translate into practical deployments, largely due to limitations in current signal processing methods. Linear transceiver processing, though widely adopted, fails to fully exploit non-orthogonal transmissions, forcing massive MIMO systems to use a disproportionately large number of RF chains for relatively few streams, increasing power consumption. Non-linear processing can unlock the full potential of non-orthogonal schemes but is hindered by high computational complexity and integration challenges. Moreover, existing message-passing receivers for NOMA depend on specially designed sparse signals, limiting resource allocation flexibility and efficiency. This work presents NL-COMM, an efficient non-linear processing framework that translates the theoretical gains of non-orthogonal transmissions into practical benefits for both the uplink and downlink. NL-COMM delivers over 200% spectral efficiency gains, enables 50% reductions in antennas and RF chains (and thus base station power consumption), and increases concurrently supported users by 450%. In distributed MIMO deployments, the antenna reduction halves fronthaul bandwidth requirements, mitigating a key system bottleneck. Furthermore, NL-COMM offers the flexibility to unlock new NOMA schemes. Finally, we present both hardware and software architectures for NL-COMM that support massively parallel execution, demonstrating how advanced non-linear processing can be realized in practice to meet the demands of next-generation networks. Full article

The growing complexity of distribution-level virtual power plants (VPPs) demands a rethinking of how flexible demand is modeled, aggregated, and dispatched under uncertainty. Traditional optimization frameworks often rely on deterministic or homogeneous assumptions about end-user behavior, thereby overestimating controllability and underestimating risk. In this paper, we propose a behavior-aware, two-stage stochastic dispatch framework for VPPs that explicitly models heterogeneous user participation via integrated behavioral economics and social interaction structures. At the behavioral layer, user responses to demand response (DR) incentives are captured using a Prospect Theory-based utility function, parameterized by loss aversion, nonlinear gain perception, and subjective probability weighting. In parallel, social influence dynamics are modeled using a peer interaction network that modulates individual participation probabilities through local contagion effects. These two mechanisms are combined to produce a high-dimensional, time-varying participation map across user classes, including residential, commercial, and industrial actors. This probabilistic behavioral landscape is embedded within a scenario-based two-stage stochastic optimization model. The first stage determines pre-committed dispatch quantities across flexible loads, electric vehicles, and distributed storage systems, while the second stage executes real-time recourse based on realized participation trajectories. The dispatch model includes physical constraints (e.g., energy balance, network limits), behavioral fatigue, and the intertemporal coupling of flexible resources. A scenario reduction technique and the Conditional Value-at-Risk (CVaR) metric are used to ensure computational tractability and robustness against extreme behavior deviations. Full article

There is a strong coupling between two arms in cooperative operations of dual-arm robots. To enhance the coordination and cooperation ability of dual-arm robots, a force-closure-based weighted hybrid force/position fuzzy coordination control method is proposed. Firstly, to improve the grasping stability of dual-arm robots, the force-closure dynamic constraints are established by combining the friction cone constraints with the force and torque balance constraints. Then the optimal distribution of contact force is performed according to the minimum energy consumption principle. Secondly, to enhance the coordination of dual-arm robots, the weighted hybrid force/position control method is modified by adding the synchronization error between two arms. Then the Lyapunov method is adopted to prove the stability of the proposed coordination control method. Thirdly, the fuzzy self-tuning technique is adopted to adjust the control gains automatically. Lastly, a simulation and experiment are performed for collaborative transport. The results show that, compared with the position coordination control and the traditional hybrid force/position control, the weighted hybrid force/position fuzzy coordination control can improve control accuracy and has good cooperation ability and strong robustness. Therefore, the proposed method can effectively realize the coordination control of dual-arm robots. Full article

Underwater wireless communication (UWC) is an emerging technology crucial for automating marine industries, such as offshore aquaculture and energy production, and military applications. It is a key part of the 6G vision of creating a hyperconnected world for extending connectivity to the underwater environment. Of the three main practicable UWC technologies (acoustic, optical, and radiofrequency), acoustic methods are best for far-reaching links, while optical is best for high-bandwidth communication. Recently, utilizing reconfigurable intelligent surfaces (RISs) has become a hot topic in terrestrial applications, underscoring significant benefits for extending coverage, providing connectivity to blind spots, wireless power transmission, and more. However, the potential for further research works in underwater RIS is vast. Here, for the first time, we conduct an extensive survey of state-of-the-art of RIS and metasurfaces with a focus on underwater applications. Within a holistic perspective, this survey systematically evaluates acoustic, optical, and hybrid RIS, showing that environment-aware channel switching and joint communication architectures could deliver holistic gains over single-domain RIS in the distance–bandwidth trade-off, congestion mitigation, security, and energy efficiency. Additional focus is placed on the current challenges from research and realization perspectives. We discuss recent advances and suggest design considerations for coupling hybrid RIS with optical energy and piezoelectric acoustic energy harvesting, which along with distributed relaying, could realize self-sustainable underwater networks that are highly reliable, long-range, and high throughput. The most impactful future directions seem to be in applying RIS for enhancing underwater links in inhomogeneous environments and overcoming time-varying effects, realizing RIS hardware suitable for the underwater conditions, and achieving simultaneous transmission and reflection (STAR-RIS), and, particularly, in optical links—integrating the latest developments in metasurfaces. Full article

A ceramic-based wideband capacitive-fed patch-loaded multi-layered rectangular dielectric resonator antenna (CFPL-ML-RDRA) with a compact form factor is proposed in this paper. The proposed antenna is composed of two ceramic substrates and a polymer as an adhesive. A capacitive-fed metallic patch structure is located on the top side of the bottom ceramic substrate. This novel structure generates two distinct resonant modes: the fundamental resonant mode of the RDRA and a hybrid resonant mode, which was confirmed through electric field (E-field) analysis and parametric studies. By merging these two resonant modes, the proposed antenna achieves a wide impedance bandwidth of 5.5 GHz, sufficient to cover the fifth-generation (5G) millimeter-wave (mmWave) frequency bands n257, n258, and n261 (5.25 GHz), while reducing the height of the DRA by 38.5% compared to the conventional probe-fed RDRA (PF-RDRA). Additionally, the 4 dBi realized gain bandwidth of the proposed CFPL-ML-RDRA is 5.4 GHz, which is 28.6% broader than that of the conventional PF-RDRA. To experimentally verify the antenna’s performance, the CFPL-ML-RDRA mounted on a test printed circuit board with a small ground size of 3.2 × 3.2 mm² was fabricated and characterized. The measured data align well with the simulated data. Furthermore, excellent antenna array performance was achieved based on array simulations. Therefore, the proposed antenna structure is well-suited for 5G mmWave mobile applications. Full article

The objectives were to assess the efficacy of genomic selection in pure line breeding, using a simulated dataset, the significance of several factors, including model updating, selection intensity, early generation (F₂) selection, dominance, and the presence of major-effect genes (QTLs). The simulated genome included 1000 biallelic genes and 49,825 SNPs, distributed on 10 chromosomes of 100 cM. We used genomic selection with partial phenotyping over generations and other scenarios. The efficacy of genomic selection was based on total realized genetic gain and probability of selecting superior pure lines. The results showed that genomic selection with model updating maximized the probability of selecting superior F₈ progeny and provided the highest total genetic gain, comparable to selection based on the true genotypic value. Larger training sets (achieved through model updating) and higher selection intensity were key factors affecting the development of elite pure lines. Dominance did not significantly affect genomic selection efficiency. Including QTLs increased genomic selection efficiency. Direct selection imposed within the F₂ generation was no more effective than selection started in F₃. All selection methods provided a high decrease in the genotypic variance at F₈. The realized genetic gains per cycle were positively correlated with the prediction accuracies. Full article

This paper presents a new compact and efficient first-order all-pass filter in voltage mode based on a second-generation voltage conveyor, along with two resistors, and a capacitor. This circuit delivers an all-pass response from the low-impedance node and eliminates the need for a voltage buffer in cascading configurations. A thorough non-ideal analysis, accounting for parasitic impedances and the non-ideal gains of the active module, shows negligible effects on the filter performance. Furthermore, a sensitivity analysis with respect to both active and passive components further validates the robustness of the design. The proposed all-pass filter is validated by Cadence PSPICE simulations, utilizing 0.18 µm TSMC CMOS process parameter and ±0.9 V power supply, including Monte Carlo analysis and temperature variations. Additionally, experimental validation is carried out using commercially available IC AD844, showing great consistency between theoretical and experimental results. Resistor-less realization of the proposed filter provides tunability feature. A quadrature sinusoidal oscillator is presented to validate the proposed structure. The introduced circuit provides a simple and effective solution for low-power and compact analog signal processing applications. Full article

Neurogranin (NRGN), a synaptic protein essential for plasticity and memory function, is gaining recognition as a promising biomarker for mild traumatic brain injury (mTBI). This systematic review brings together findings from six studies that measured neurogranin levels in biofluids—including serum, cerebrospinal fluid (CSF), plasma, and exosomes—during both the acute and chronic phases following injury. In the acute phase of mTBI, elevated levels of neurogranin were consistently observed in serum samples, suggesting its potential as a diagnostic marker. These increases appear to reflect immediate synaptic disturbances caused by injury. In contrast, studies focusing on the chronic phase reported a decrease in exosomal neurogranin levels, pointing to ongoing synaptic dysfunction well after the initial trauma. This temporal shift in neurogranin expression highlights its dual utility—both as an early indicator of injury and as a longer-term marker of synaptic integrity. However, interpreting these findings is not straightforward. The studies varied considerably in terms of sample type, timing of measurements, and control for potential confounding factors such as physical activity. Such variability makes direct comparisons difficult and may influence the outcomes observed. Additionally, none of the studies included proteoform-specific analyses of neurogranin, an omission that limits our understanding of the molecular changes underlying mTBI-related synaptic alterations. Due to heterogeneity across study designs and outcome measures, a meta-analysis could not be performed. Instead, a narrative synthesis was conducted, revealing consistent patterns in neurogranin dynamics over time and underscoring the influence of biofluid selection on measured outcomes. Overall, the current evidence supports neurogranin’s potential as both a diagnostic and mechanistic biomarker for mTBI. Yet, to fully realize its clinical utility, future research must prioritize standardized protocols, the inclusion of proteoform profiling, and rigorous longitudinal validation studies. Full article

Brazil leads tropical agriculture, yet annual yield losses from insect pests and concerns over water contamination, non-target impacts, and resistance sustain demand for safer, more efficient control tools. This review synthesizes advances in nanopesticides for Brazil’s major crops (soybean, sugarcane, coffee, and citrus) and is organized into five parts, comprising concepts and definitions; formulation families; modes of action; efficacy evidence from laboratory, greenhouse, and field studies; and environmental and human health risk considerations. Evidence indicates that nano-enabled delivery can increase on-target deposition, prolong residual activity, and match or exceed control at reduced active ingredient loads by improving foliar adhesion, transcuticular transport, plant uptake, and spatiotemporal targeting with pheromone-releasing nanofibers and other dispensers. Because nanoformulations can alter exposure pathways and environmental fate, this review emphasizes nano-specific physicochemical characterization under use conditions, fate and transport in Oxisols and Ultisols, and tropical waters, ecotoxicity panels that include pollinators, aquatic invertebrates, soil biota, and vertebrate surrogates, and scenario-based exposure assessment for applicators, residents, and consumers. The review closes with practical guidance for Brazil: head-to-head efficacy benchmarks against commercial standards, the standardized reporting of release and characterization data, and a nano-specific environmental risk assessment checklist to help realize efficacy gains while protecting environmental and human health. Full article

This article investigates the bipartite consensus control problem of general linear multiagent systems over an antagonistic interaction topology using a dynamic event-triggered mechanism. Primarily, for each agent, a distributed dynamic event-triggered control scheme is proposed based on a signed cooperative–competitive communication graph. Controller updates and triggering condition monitoring are executed only when a specified event is triggered, thereby reducing communication overhead. Subsequently, by integrating the time-varying control gain into the presented control strategy, a fully distributed bipartite controller architecture is defined without using global topology information. As a result, the influence of coupling weights on each agent can be restrained, enabling the realization of bipartite consensus for multiagent systems. Moreover, the proposed dynamic event-triggered control protocol is rigorously proven to exclude Zeno behavior over the entire time horizon. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed method. Full article

With the rapid growth of unmanned aerial vehicles (UAVs) and IoT users, spectrum resources are becoming increasingly scarce, making cognitive radio (CR) technology a key approach to improving spectrum utilization. However, traditional antennas are difficult to meet the lightweight, compact, and low-drag requirements of small UAVs due to spatial constraints. This paper proposes a tri-mode frequency reconfigurable flexible antenna that can be conformally integrated onto UAV wing arms to enable CR dynamic frequency communication. The antenna uses a polyimide (PI) substrate and has compact dimensions of 31.4 × 58 × 0.05 mm³. A microstrip line-based frequency-selective network is designed, incorporating PIN and varactor diodes to realize three operation modes, dual-band (2.25~3.55 GHz, 5.6~6.75 GHz), single-band (3.35~5.3 GHz), and continuous tuning (4.3~6.1 GHz), covering WLAN, WiMAX, and 5G NR bands. Test results show that the antenna maintains stable performance under conformal conditions, with frequency shifts less than 4%, gain (3.65~4.77 dBi), and radiation efficiency between 67.2% and 82.9%. The tuning ratio reaches 38.8% in the continuous mode. This design offers a new solution for CR communication in compact UAV platforms and shows promising application potential. Full article

Chamomile (Matricaria chamomilla L.) is a popular herb of great economic and medicinal value. Despite its significant potential, there are currently no commercially available varieties specifically adapted to Mediterranean low-input farming systems. The present study aimed to develop a genetically improved breeding population derived from indigenous Greek chamomile germplasm, following a multi-year strategy, based on pedigree selection under low-input conditions. This selection process constituted the first phase of the breeding program, during which selection focused on improving inflorescence dry weight and essential oil quality, particularly with respect to α-bisabolol and chamazulene content. After three cycles of selection, considerable genetic gains were achieved. The realized heritability values exceeded 0.5 for all assessed traits, confirming strong genetic control. In the fourth year, representing the second phase of the breeding program, the breeding population—developed through selection during the first phase—was evaluated alongside the initial population and commercial diploid and tetraploid varieties. The breeding population exhibited significant observed gains compared to the initial population: inflorescence dry weight increased by 12.17%, α-bisabolol content by 71.45%, and chamazulene content by 6.57%. Additionally, the breeding population not only surpassed all evaluated diploid genotypes in essential oil composition, but also displayed a chemotypic shift, indicating successful alignment with tetraploid varieties characterized by high-value chemical profiles. Furthermore, this selection process targeting specific commercial chamomile traits indirectly contributed to improvement in plant height and inflorescence morphology. Overall, these results demonstrate that conventional breeding, when applied effectively to native resources, can enhance both agronomic performance and essential oil profile. The newly developed breeding population provides a strong foundation for future cultivar development tailored to Mediterranean low-input sustainable farming systems. Full article