Search Results (736)

The rapid progress of sensing technologies, artificial intelligence, and embedded computing has significantly accelerated the development of autonomous vehicles. Among the core challenges of higher-level driving automation, reliable environmental perception remains one of the most critical. This review presents a systematic PRISMA-based analysis of multimodal sensor technologies and fusion architectures applied in autonomous driving, based on 66 peer-reviewed studies published between 2014 and 2025. The study examines the operational characteristics, advantages, and limitations of major sensing modalities, including cameras, LiDAR, radar, ultrasonic sensors, and GNSS/IMU-based localization systems. Particular attention is given to multimodal fusion strategies, covering early, mid-level, high-level, and transformer-based architectures that combine complementary sensor information to improve perception robustness and decision reliability. The review further synthesizes current evidence on performance under adverse environmental conditions, benchmark validation practices, real-time computational constraints, and the growing role of functional safety frameworks such as ISO 26262 and SOTIF. Emerging research directions, including 4D radar, self-supervised long-range fusion, foundation models, and cooperative V2X perception, are also discussed. The findings indicate that multimodal sensor fusion is a highly effective architectural strategy for improving scalability, fail-operational robustness, and certifiable safety in autonomous driving systems, particularly in higher-level automation scenarios. Future research should focus on uncertainty-aware fusion, explainable cross-modal reasoning, large-scale real-world validation, and efficient hardware–software co-design to support robust Level 4–5 vehicle autonomy. Full article

Vehicle-to-grid (V2G) can provide flexibility and storage for low-carbon power systems while supporting sustainable mobility, yet real-world deployment remains largely confined to pilots despite substantial technical progress. This article presents a PRISMA-guided systematic review of 974 V2G/V2X studies published between 2009 and 2025 to explain why implementation lags and how it can be accelerated. Within this corpus, a total of 162 implementation-critical articles are identified and, within these, 95 studies that primarily address non-technical dimensions such as policy, markets, user behavior, and ecosystem coordination. Drawing on full-text coding, a four-domain socio-technical framework is developed that clusters recurring non-technical barriers and enablers into business–economic, governance–policy, social, and infrastructure and ecosystem domains. The analysis reveals (i) a temporal shift from technical dominance to multidisciplinary acceleration after 2021; (ii) distinct regional priorities in which Europe emphasizes regulation and business models, Asia focuses on infrastructure scaling, and the Americas on frequency services and resilience; and (iii) persistent revenue uncertainty, regulatory gaps, user resistance, and grid unreadiness as cross-cutting obstacles. For each domain, concrete transition levers and indicative deployment key performance indicators (KPIs) are derived, such as multi-actor revenue-sharing mechanisms, aggregator recognition in market rules, privacy-by-design user participation models, and targeted bidirectional charging deployment in constrained grids. Synthesizing these insights, three archetypal V2G transition pathways are proposed—regulation-led, infrastructure-first, and service-driven—that reflect regional conditions and offer alternative routes to large-scale adoption. The framework and roadmap provide researchers, policymakers, system operators, and mobility providers with an integrated basis for designing, monitoring, and evaluating V2G policies, business models, and pilots in line with energy system decarbonization goals. Full article

Localized surface plasmon resonance (LSPR) is an optical phenomenon that occurs when light interacts with free electrons on the surface of metallic thin films, producing intensified electromagnetic fields at specific sites, often called “hot spots”. LSPR-based sensing technologies respond to chemical and associated optical interfacial changes. Inherent advantages include enhanced sensitivity, compact size, low production cost, and strong potential for integration into portable, point-of-care diagnostic systems. This study focuses on a detailed investigation into the surface functionalization of localized surface plasmon resonance (LSPR)-based nanohole array (NHA) sensors for biomedical applications. Gold-coated NHA surfaces were functionalized using polyethylene glycol (PEG) self-assembled monolayers (SAMs), enabling specific attachment of biomolecular species. As a proof-of-concept, bovine serum albumin (BSA) and SARS-CoV-2 nanobody proteins were successfully immobilized on the PEGylated surfaces. Individual steps of surface modification including PEGylation, protein immobilization and nanobody immobilization were validated through a dual-method approach which combined measurement of LSPR optical spectral shifts and x-ray photoelectron spectroscopy (XPS) chemical analyses. Reproducibility was assessed across multiple sensors and repeated trials, confirming the repeatability of each functionalization and binding process. The sensor system, consisting of NHA-based plasmonic platform, microfluidics, and a portable optical spectrometer, exhibits the capability for reliable and sensitive, label-free detection of biomolecular targets, including viral antigens, in liquid-phase environments. Full article

The gelation property is one of the core functional characteristics of konjac glucomannan (KGM). KGM mainly forms gels through ionic crosslinking, deacetylation and compounding with other colloids. Exploring novel gelation technologies for the precise regulation of KGM gel properties is the research focus in this field. In this work, an alternating current (AC) electric field was applied to trigger KGM gelation in the presence of calcium chloride (CaCl₂). The structure and viscoelastic properties (including storage modulus G′, loss modulus G″ and loss factor tanδ) of the gels were analyzed by Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy (RS), scanning electron microscopy (SEM), X-ray diffraction (XRD), simultaneous differential scanning calorimetry/thermo-gravimetric analyzer (DSC/TGA) and rheometer. FTIR and RS revealed that KGM underwent partial degradation and deacetylation under the AC electric field. Calcium ions and chloride ions dissociated from CaCl₂ are adsorbed onto the hydroxyl groups of KGM molecules. KGM molecules constituting the gels still retain partial original acetyl groups. SEM images showed that the gels had a porous structure with a coarse surface. XRD patterns showed the gels contained complex CaCl₂ hydrates. Simultaneous DSC/TGA analysis indicated that the gel with excellent thermal stability exhibited distinct melting endothermic peaks corresponding to CaCl₂ hydrates. Rheological data showed that, apart from KGM concentration, G′ and G″ of the gels gradually increased with the elevation of CaCl₂ concentration, applied voltage and electric treatment duration. However, when CaCl₂ concentrations, voltage, and electric treatment time exceeded their respective critical values, both started to decrease. Taking G′ as the evaluation index, the optimal preparation conditions for KGM-CaCl₂ electrogel were determined as follows: KGM 0.5%, CaCl₂ 1.2%, electric treatment duration 45 min, and voltage 24 V. Full article

K-ion batteries (KIB) are considered the future energy storage and conversion technology due to their remarkable performance. In this work, a high-temperature solid-state process was used to effectively synthesize KMnO₂, a promising cathode material for KIBs. The materials were examined using X-ray powder diffraction (XRPD), Raman and infrared spectroscopies, electron microscopy analysis, optical, and impedance spectroscopies. Rietveld refinement of X-ray diffraction data confirmed that the compound crystallizes in the monoclinic system with the P-2₁/m space group. Fourier transform infrared and Raman spectroscopies revealed the vibrational modes of the KMnO₂ compound and proved the existence of the octahedral environment MO₆ (M = Mn, K), which affirms structural configuration. The morphological distribution and grain size of the titled compound were examined using SEM studies. A direct band gap of around 3.12 eV was found by optical studies using UV–Vis spectroscopy, confirming the semiconducting nature of KMnO₂ and indicating its applicability for optoelectronic and energy-related applications. The characteristics of this material were further examined using impedance spectroscopy at temperatures between 343 and 443 K and a frequency range of 10⁻¹ Hz to 10⁶ Hz. The DC conductivity and relaxation time exhibited Arrhenius behavior, with a significant shift in activation energy at 373 K, suggesting a change in the conduction mechanism. The frequency behavior of AC conductivity, σ_ac, was analyzed using the universal Jonscher law. The findings of the charge transportation study on KMnO₂ indicate that this material follows a non-overlapping small polaron tunneling (NSPT) for T < 383 K and correlated barrier hopping (CBH) above for T > 383 K. A correlation between the ionic conductivity and the crystal structure was established and discussed. Full article

X-band copper resonating cavities are key components of future pulsed GHz normal-conductive multi-TeV accelerators. High electric field gradients are required for emerging applications; however, as gradients increase, components’ lifetime decreases, primarily due to radiofrequency (RF) breakdown. Coating technologies are being investigated in several laboratories to improve RF structure, performance and lifetime. To this end, we investigated the feasibility of fabricating nanometer-periodic Cu/Mo metallic multilayers on three-dimensional (3D) aluminum mandrels designed to replicate X-band copper resonating cavities. These nanometer-period multilayers are proposed to mitigate surface degradation due to electric breakdown at high accelerating gradients by stabilizing inner cavity surfaces against dislocation evolution and roughening caused by thermo-mechanical fatigue. High-Power Impulse Magnetron Sputtering (HiPIMS) in a bias-controlled dual closed-field magnetron configuration was employed to deposit alternating Mo and Cu nano-layers onto the 3D geometries. Given the complexity of HiPIMS technology, plasma pulse evolution was studied by combining time-resolved optical emission spectroscopy with electrical measurements of the pulse discharge. The influence of the process parameters, particularly the applied DC bias, on film growth was studied using non-destructive microprobe α-particle elastic backscattering spectrometry (µEBS) and scanning transmission electron microscopy (STEM). STEM and µEBS analyses confirmed that Mo layers with thicknesses of approximately 5–35 nm were successfully deposited repeatedly on thicker Cu layers (30–150 nm), preserving individual layer properties with minimal interdiffusion and alloying. The layers were deposited inside trenches with an aspect ratio of 5:1 representative of X-band irises. This technology, coupled with the replica process, could be applied to highly engineered nanostructured coatings for X-band cavity treatment in compact particle accelerator prototypes, as it may improve electrical breakdown lifetime under high accelerating fields, at least for degradation processes driven by the high mobility of copper dislocations. Full article

Background: By integrating an MRI scanner and a linear accelerator, MR-linac systems provide superior soft tissue imaging and allow to perform adaptive radiotherapy adjusted on daily anatomical changes. The advent of this technology represents a revolution in radiation oncology and could improve treatment accuracy and clinical outcomes. We performed a comprehensive bibliometric analysis with the aim of displaying the available scientific literature and trends regarding MR-linac. Methods: Scopus database was investigated, considering documents published up to 6 April 2025. Keywords encompassed terms related to “MR-linac” or “MRI-linac” and possible combinations and acronyms. BibTeX data file was imported into Biblioshiny (Bibliometrix package—v. 4.1.4) and analysis was conducted using R code (R version 4.3.2) and the Bibliometrix package (version 4.1.4). Results: A total of 1624 articles on MR-linac were identified. The number of annual publications gradually increased from 21 in 2008, peaking at 211 in 2022 and then remaining substantially stable in subsequent years. Most of the papers were original articles (79.2%) and the majority was published by the 10 journals with the largest output. Remarkably, of 6385 identified authors, over 85% were from one of the 10 most represented countries (including European, North American and Asian nations). Consistently, the 10 institutions with the larger output were North American, Australian or European and provided over 60% of the articles. International co-authorship was found in only 23.6% of the articles. Keyword and co-occurrence analyses identified MR-guided radiotherapy, SBRT, dosimetry, and adaptive strategies as core themes, with emerging trends in radiomics, diffusion metrics, and deep learning. Conclusions: Bibliometric analysis identified trends and patterns of scientific publications regarding MR-linac, highlighting a growing interest in the topic. Nonetheless, it should be considered that the majority of the papers were published by a few journals and over 85% of authors were from 10 countries, demonstrating an evident disparity across nations. Multicentric international research protocols and common frameworks could foster the transition towards collaborative practice-changing studies. Full article

This study reports a straightforward and controllable two-step hydrothermal synthesis of novel Ni₉S₈@NiMoO₄/NF nanospherical catalysts supported on nickel foam (NF), accompanied by a systematic evaluation of their performance in the electrochemical hydrogen evolution reaction (HER). Structural characterization revealed a well-defined Ni₉S₈–NiMoO₄ interfacial region, whose synergistic interaction, combined with the distinctive nanospherical morphology, substantially increased the electrochemically active surface area and the density of reactive sites, thereby optimizing HER kinetics. In alkaline media, the Ni₉S₈@NiMoO₄/NF catalyst demonstrated outstanding electrocatalytic performance, delivering an overpotential of only 64.2 mV at a current density of 20 mA cm⁻². The catalyst also exhibited a high double-layer capacitance of 22.2 mF cm⁻², reflecting a substantial active interfacial area. Long-term durability tests showed negligible performance degradation after 165 h of continuous operation at 10 mA cm⁻², underscoring the catalyst’s robust structural stability and durability. X-ray photoelectron spectroscopy confirmed a uniform distribution of Ni, Mo, and S across the NF framework and revealed optimized chemical states, providing material-level evidence for the enhanced performance. Collectively, this work proposes a viable strategy for designing efficient and stable HER catalysts, contributing to the advancement of green hydrogen production and clean energy technologies. Full article

Animal-vehicle collisions (AVCs) pose a significant threat to road safety, wildlife conservation, and transportation systems worldwide. Advances in artificial intelligence (AI) and computer vision have enabled intelligent detection and mitigation systems aimed at reducing such collisions. This review synthesizes the current state of AI-powered AVC prevention systems, examining deep learning architectures, multimodal sensor technologies, real-time processing frameworks, and system-level integration strategies. We analyze the transition from traditional computer vision methods to modern deep neural networks, evaluate sensor fusion approaches, and assess existing wildlife detection datasets and benchmarking practices. Key technical challenges are identified, including environmental variability, long-range detection constraints, dataset scarcity, cross-species generalization limitations, and real-time safety requirements. Rather than framing AVC prevention solely as an object detection task, this review conceptualizes it as a safety-critical perception and risk assessment pipeline operating under strict latency and deployment constraints. Persistent gaps in wildlife-specific detection, standardized evaluation protocols, and scalable edge deployment are discussed. To organize these insights, we present WildSafe-Edge as a conceptual reference architecture derived from the literature, synthesizing system-level design considerations and highlighting open research directions. Future research directions include transfer learning, synthetic data augmentation, vehicle-to-everything (V2X) integration, and edge-centric architectures to enable robust, real-world collision mitigation systems. Full article

FAEST is a National Institute of Standards and Technology post-quantum signature candidate based on the Vector Oblivious Linear Evaluation-in-the-Head paradigm, whose signing performance is dominated by repeated Advanced Encryption Standard Counter-based Pseudorandom Generator calls. The reference implementation provides no FAEST-specialized acceleration for Advanced RISC Machine platforms. This paper proposes a three-layer Advanced Reduced Instruction Set Computer Machine NEON Single Instruction Multiple Data optimization: a register-resident 256-byte S-box with Table Lookup/Table Lookup with Extension-based SubBytes and four-way/eight-way parallel Advanced Encryption Standard processing; a fixed-length Pseudorandom Generator specialized for the FAEST tree structure; and Portable Operating System Interface for Unix thread-based parallelization of independent Vector Oblivious Linear Evaluation instances. Evaluated on all 12 parameter sets of FAEST v2 on Raspberry Pi 4 (without Advanced Reduced Instruction Set Computer Machine version 8 crypto-extensions) and Apple M2 (with hardware Advanced Encryption Standard support), the proposed method achieves signing speedups of up to 136.9x on Raspberry Pi 4 and 330.1x on Apple M2 over the pure-C reference. On Raspberry Pi 4, the NEON implementation outperforms OpenSSL; on Apple M2, the NEON-plus-Portable Operating System Interface for Unix thread configuration outperforms hardware-accelerated OpenSSL across all parameters, confirming that NEON SIMD combined with task-level parallelization can exceed hardware-accelerated single-thread throughput on Advanced Reduced Instruction Set Computer Machine-based platforms. Full article

This paper presents a low-noise analog front-end (AFE) integrated circuit (IC) circuit for capacitive micro-electromechanical system (MEMS) accelerometers that can be used for optical image stabilization (OIS) in various optical imaging systems. The AFE circuit design features a fully differential chopper stabilization technique that efficiently minimizes low-frequency 1/f noise and parasitic coupling. The AFE circuit chip is fabricated in a 0.18 $\mathsf{\mu }$m complementary metal-oxide-semiconductor (CMOS) technology and co-packaged with an x-axis capacitive MEMS accelerometer based on a silicon-on-glass (SOG) process. The SOG accelerometer has a footprint of 1000 $\mathsf{\mu }\mathrm{m}$ $\times$ 950 $\mathsf{\mu }\mathrm{m}$. The packaged system demonstrates a sensitivity of 342 mV/g and a nonlinearity of 1.1% between −1 g and +1 g, a dynamic range of 88 dB, and an equivalent noise floor of 14 $\mathsf{\mu }\mathrm{g}/\sqrt{\mathrm{H}\mathrm{z}}$. Full article

Traditional mechanized chestnut harvesting is too costly for small producers, non-selective, and prone to damaging nuts. Accurate, reliable detection of chestnuts on the orchard floor is crucial for developing low-cost, vision-guided automated harvesting technology. However, developing a reliable chestnut detection system faces challenges in complex environments with shading, varying natural light conditions, and interference from weeds, fallen leaves, stones, and other foreign on-ground objects, which have remained unaddressed. This study collected 319 images of chestnuts on the orchard floor, containing 6524 annotated chestnuts. A comprehensive set of 29 state-of-the-art real-time object detectors, including 14 in the YOLO (v11–v13) and 15 in the RT-DETR (v1–v4) families at various model scales, was systematically evaluated through replicated modeling experiments for chestnut detection. Experimental results show that the YOLOv12m model achieved the best mAP@0.5 of 95.1% among all the evaluated models, while RT-DETRv2-R101 was the most accurate variant among the RT-DETR models, with mAP@0.5 of 91.1%. In terms of mAP@[0.5:0.95], the YOLOv11x model achieved the best accuracy of 80.1%. All models demonstrated significant potential for real-time chestnut detection, and YOLO models outperformed RT-DETR models in terms of both detection accuracy and inference, making them better suited for on-board deployment. This work lays a foundation for developing AI-based, vision-guided intelligent chestnut harvest systems. Full article

The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events. Full article

Background: Gefitinib (Gef) is a first-line epidermal growth factor receptor (EGFR) inhibitor for NSCLC, but its clinical application is limited by poor aqueous solubility and low oral bioavailability. Methods: A self-assembled gefitinib nanosuspension (GG-NS) incorporating genistein (Gen) was rapidly developed and optimized via hammer acoustic resonance (HAR) technology. Systematic optimization was conducted using a high-throughput HAR-based process, with particle size, PDI, and zeta potential as key evaluation parameters. Structural and morphological characteristics were analyzed using powder X-ray diffraction (PXRD), thermal analysis, transmission electron microscopy (TEM), and Fourier-transform infrared (FT-IR) spectroscopy. In vitro dissolution behavior and cytotoxicity against A549 lung cancer cells were evaluated. Results: Optimal GG-NS with Z-Ave = 223.50 ± 1.53 nm, PDI = 0.239 ± 0.031 and zeta potential = −24.10 ± 0.47 mV was successfully prepared. The nanosuspension remained physically stable for up to five months at both 4 °C and 25 °C. Compared with the raw drugs, GG-NS enhanced the dissolution of gefitinib and genistein in water by 3.76-fold and 13-fold, respectively. In addition, GG-NS showed significantly enhanced cytotoxicity against A549 cells, with a 33.8% higher inhibition rate than the physical mixture after 72 h. Conclusions: This study demonstrates, for the first time, that HAR technology enables the rapid fabrication of a self-assembled GG-NS with improved dissolution performance, physicochemical stability, and in vitro anticancer activity, highlighting its promise as an efficient and scalable formulation strategy for poorly soluble anticancer drugs. Full article

Background: Phantoms are essential in medical imaging, providing reproducible and quantitative means for system and protocol evaluation, image quality assessment, and dosimetry without patient exposure. Additive manufacturing enables rapid, accurate fabrication of phantoms ranging from simple geometries to complex anthropomorphic models. Ongoing developments in 3D printing technologies and polymer formulations have enhanced mechanical properties and printability, but also affect X-ray attenuation behaviour, necessitating an update with current materials to facilitate the choice of appropriate materials mimicking body tissues in radiographic phantoms. Methods: Attenuation properties of 27 photopolymer resins and 22 thermoplastic filaments (based on PLA, ABS, HIPS, PETG/PCTG, and PVB) were quantified using a clinical CT scanner at 70–140 kV to establish reference data for material selection. Results: At 120 kV, resins exhibited attenuation values between 124 and 384 Hounsfield Units (HU), and filaments ranged from −69 to 308 HU (PLA-based filaments: 160 to 241 HU, ABS: −32 to 43 HU, PETG/PCTG: 151 to 308 HU, and HIPS: −69 to −22 HU). Energy dependence of HU values is presented from 70 to 140 kV tube potential. Compared to the 2021 study, a wider selection of X-ray opacities is available. Regarding SLA/DLP printing, resins with higher attenuation were identified, and flexible resins that had provided a choice of low attenuation printing materials in the range of 60 to 90 HU at 120 kV tended to replicate attenuation properties closer to rigid photopolymers; i.e., HU values were slightly higher. In FDM filaments, a wide variation in different PLA-, ABS-, and HIPS-based filaments is found. In copolymers from the PET/PCTG/PETG family, very inhomogeneous X-ray attenuations are still found, as anticipated. Conclusions: The range of X-ray attenuation observed demonstrates that commercially available 3D printing materials can replicate clinically relevant tissues and tissue-equivalent contrasts. Furthermore, the available range of attenuations has increased, as has the finer gradation of these materials. These findings support the design of patient- and task-specific imaging phantoms for optimization of acquisition protocols, image quality evaluation, and radiation dose studies, as well as facilitate the selection of appropriate phantom materials. Full article