Search Results (800)

The rapid and precise detection of biomarkers and pathogens remains a critical challenge in clinical diagnostics. Traditional methodologies are frequently hindered by protracted workflows, complex sample preparation, and reliance on resource-intensive instrumentation. Acoustofluidics—the synergistic integration of acoustics and microfluidics—has emerged as a transformative solution for point-of-care testing (POCT). Bulk acoustic wave (BAW) and surface acoustic wave (SAW) technologies enable the contactless, label-free, and biocompatible manipulation of bioparticles across micro- and nanometer scales. This review critically examines recent advancements in BAW- and SAW-based acoustofluidic biosensors. We elucidate the fundamental principles governing distinct acoustic modes—including Quartz Crystal Microbalance (QCM), film bulk acoustic resonator (FBAR), and Solidly Mounted Resonator (SMR) for BAW and Rayleigh and Love waves for SAW—and evaluate their specific roles in liquid-phase sensing, particle sorting, and cellular focusing. Results show that integrating on-chip sample preparation accelerates diagnostic workflows, reducing assay times to under 10 min. Coupling acoustic manipulation with optical, mass-based, or electrochemical modalities effectively overcomes fundamental diffusion limits, achieving ultrasensitive, multimodal detection. We address translational challenges—acoustothermal heating, biofouling, and scalable integration. Following a discussion of clinical applications in oncology and infectious diseases, we map emerging trajectories, emphasizing AI-driven intelligent microfluidics, modular architectures, and flexible wearable platforms that will ultimately democratize continuous precision diagnostics. Full article

False data injection (FDI) cyberattacks pose a growing threat to modern power distribution systems in smart cities by manipulating state-estimation processes and provoking covert voltage violations that traditional defense mechanisms fail to detect. Recent industry data indicate that coordinated FDI attacks can distort measurement sets by as little as 3–7%, yet trigger voltage deviations exceeding 10% in vulnerable feeders, resulting in operational instability, unnecessary load curtailments, and elevated outage risk. To address these challenges, this paper proposes a quantum-accelerated digital twin (QDT) framework that integrates quantum optimization algorithms with a high-fidelity digital twin (DT) of the distribution system to detect, localize, and remediate FDI-induced cyberattacks in real time. The rationale behind the approach lies in the superior combinatorial search capability of quantum solvers, which accelerates the identification of falsified measurement vectors and optimal corrective control actions compared with classical methods. In addition, the framework introduces an innovative Bitcoin-mining-oriented virtual energy storage (BMOVES) mechanism that treats mining facilities as dynamically controllable, fast-response electrical loads within smart city demand–response programs. By modulating mining power consumption with sub-second granularity, the proposed BMOVES resource provides up to 18–45% flexible capacity during attack scenarios, enabling voltage restoration without relying on conventional energy storage assets. The unified QDT + BMOVES architecture is validated using the 136-bus Brazilian distribution system, a realistic benchmark for cyber–physical resilience studies. Simulation results demonstrate over 99% FDI detection accuracy, up to an 82% reduction in peak voltage violations, and restoration of operational limits 11 times faster than state-of-the-art classical methods. These findings highlight the transformative potential of integrating quantum computing, digital twins, and nontraditional flexible assets to enhance cyber-resilient power infrastructure in future smart cities. Full article

Precision alignment and target contact are critical tasks for mobile manipulators in industrial inspection and flexible manufacturing. However, achieving high accuracy after navigation remains challenging due to accumulated errors from mobile base localization, perception noise, and calibration uncertainty. This paper proposes a vision-guided precision alignment framework for mobile manipulators using a single front-facing RGB-D camera. The method integrates YOLO-based target detection, AR marker-assisted plane depth estimation, and depth-based 3D localization within a coarse-to-fine alignment strategy. After navigation, the manipulator first moves to a predefined pre-alignment pose, followed by visual localization and iterative refinement to compensate for residual errors before executing precise target contact. The proposed system is implemented and evaluated in a Gazebo-based simulation environment using a mobile manipulator platform model. In a static touch panel experiment with 50 trials, the system achieves a success rate of 98%, with positioning errors maintained within a millimeter-level range. Simulation results demonstrate that the proposed method provides stable alignment performance in the simulation environment without relying on external sensing devices such as force sensors or multi-camera systems. The proposed approach shows promising potential for precision contact tasks in mobile manipulation. Full article

Background: This study examined condition-dependent electroencephalography (EEG) changes under progressive degradation of visual and tactile information. Methods: Using a controlled visual–tactile paradigm, we systematically manipulated visual degradation and tactile impairment at multiple levels and analyzed time–frequency activity and P300 responses. Results: The results showed condition-dependent changes in oscillatory activity and P300 amplitude across graded visual–tactile degradation conditions. In several conditions, degradation in one modality was accompanied by increased neural responses in the other modality. However, this pattern was not monotonic: stronger responses were observed under some moderate degradation combinations, whereas responses were reduced under severe dual-modal degradation. Conclusions: In addition, the relative balance between visual-task and tactile-task responses varied across conditions, suggesting flexible but condition-dependent changes in modality weighting rather than a fixed hierarchy between modalities. Overall, these findings are consistent with graded neural adaptation under visual–tactile uncertainty, but they do not by themselves establish a specific causal mechanism of sensory reallocation. Full article

Neuronal activity and cerebral blood flow are tightly coupled to support the high metabolic demands of the brain. Disruption of neurovascular coupling is a defining feature of many neurodegenerative disorders such as Alzheimer’s disease, stroke, small vessel disease, Parkinson’s disease, and aging. Progress in understanding the mechanisms underlying neurovascular coupling requires experimental approaches that can simultaneously measure neuronal activity and vascular dynamics with high spatial and temporal resolution, while also enabling targeted perturbations of the system. Here, we present a methodological framework that combines chronic electrophysiological recordings with two-photon imaging of cerebral blood flow and optogenetic manipulation of the vasculature in vivo. Using a chronically implanted flexible electrode array, we obtain measurements of the single- and multi-unit spiking activity, as well as local field potentials. Concurrently, two-photon microscopy enables high-resolution measurements of vessel diameter and blood flow within individual vascular segments. In addition, optogenetic control of vascular smooth muscle cells allows for rapid and reversible manipulation of the vessel diameter through the same cranial window while simultaneously recording the neural and vascular activity. We provide detailed protocols for surgical implantation, data acquisition, and analysis, and discuss experimental considerations and limitations. This combined platform offers a powerful tool for mechanistic studies of neurovascular coupling and its dysfunction in disease models. Full article

When a rigid object is manipulated by dual arms to form a closed chain, the dual-arm motion must satisfy closed-chain constraints. Although synchronized motion can be achieved by strictly tracking predefined global trajectories, the presence of dynamic obstacles necessitates reactive local planning. However, existing local planning methods designed for single-arm manipulators cannot guarantee synchronization between dual arms. To address this limitation, we propose a dual-arm reactive synchronized motion controller (SMC) by incorporating closed-chain constraints on dual-arm slack velocities based on spherical geometric velocity constraints, and by implementing a flexible master-slave arm switching strategy. As a result, the proposed controller achieves synchronized dual-arm control while preserving excellent motion performance, including manipulability enhancement, obstacle avoidance, and compliance with joint angle and velocity constraints. Simulations and experiments on a humanoid upper-body robot validate the effectiveness of the proposed approach. Full article

The precise fabrication and controllable actuation of magnetic microspheres hold significant application value in biomedicine, microfluidic chips and other fields. Based on femtosecond laser two-photon polymerization technology (FLTPP), two methods are adopted to prepare magnetic microspheres in this study. Magnetic microspheres are fabricated via photoresist modification and post-treatment processes. Meanwhile, a 3D magnetic actuation system composed of a three-axis movable magnetic drive module and a real-time imaging system is constructed, enabling the flexible 3D actuation and real-time dynamic monitoring and visualized observation of magnetic microspheres. The results demonstrate that the magnetic microspheres exhibit sensitive magnetic response characteristics. The constructed magnetic actuation system features large travel range (XY: ±6.5 mm, Z: 10 mm), high precision (20 μm) and flexible manipulation, enabling stable locomotion of the microrobots in straight channels, L-shaped channels, and square channels. This study provides a technical reference for the fabrication and manipulation of magnetic micro/nano devices, and lays a foundation for their subsequent integrated applications in microfluidic systems. Full article

In flexible manufacturing systems, the composite mobile manipulator (CMM) is subject to nonlinear inertial disturbances arising from the dynamic coupling between the mobile platform and the robotic arm. These disturbances significantly impair positioning precision during grasping tasks. This paper addresses the dynamic decoupling of multi-body nonlinear inertial disturbances within CMM systems. Departing from the conventional “stop-then-plan” serial execution paradigm, we propose a full-cycle spatiotemporally coupled trajectory optimization method. The operation cycle is bifurcated into two synergistic stages: “dynamic calibration” and “static execution.” The dynamic calibration trajectory is pre-planned and executed synchronously during platform movement to actively compensate for inertial-induced pose deviations. Concurrently, the static execution trajectory is optimized and then triggered immediately upon platform standstill, ensuring a seamless and precise transition to the “Grasping Pose”. It is worth noting that the temporal characteristic central to this framework lies in the concurrent execution of static trajectory optimization and platform transit: by the time the platform reaches its destination, the pre-planned trajectory is already available for immediate triggering, achieving zero task-switching wait time at the planning layer. The term “zero-latency” here does not imply a fixed-cycle real-time response at the control layer, but rather the complete elimination of decision latency afforded by the parallel planning architecture. This framework eliminates computational latency, markedly enhancing operational efficiency. Key innovations include two novel constraints. First, the Adaptive Task-space Bounded Search Constraint (ATBSC) framework restricts optimization to a geometry-inspired search region, thereby enhancing search efficiency and ensuring controllable deviations. Second, the Multi-Rigid-Body Coupling Constraint (MRBCC) system explicitly models inertial transmission across motion phases to suppress pose fluctuations. The proposed framework is developed and validated within an obstacle-free workspace. In simulation-based validation on a UR10 6 degree-of-freedom manipulator model, experimental results indicate that ATBSC increases valid solution density to 84.7% and reduces average deviation by 72.8%. Furthermore, under the tested conditions, MRBCC mitigates end-effector position errors by 79.7–81.0% with a 97.5% constraint satisfaction rate. The improved Cuckoo Search algorithm (ICSA), serving as the solver component of the proposed framework, achieves an 11.9% lower fitness value and a 13.1% faster convergence rate compared to the standard Cuckoo Search algorithm in the tested scenarios, suggesting its effectiveness as a reliable solver for the constrained multi-objective trajectory optimisation problem. Full article

Magnetically driven microrobots operating in intestinal environments face two major challenges: difficulty in traversing low-height confined spaces and limited local visibility caused by mucosal obstruction. To address these issues, this study proposes a gradient-field-based force-driven control method for a mudskipper-inspired magnetic microrobot. By establishing the mapping among coil current, magnetic field, and magnetic force at the robot working point, and by solving the control input through singular value decomposition and linear programming, effective magnetic-force output along a desired direction was achieved. On this basis, two representative force-driven motions were designed. The first was a translational mode based on pulsed magnetic-force actuation for stable navigation in low-height confined spaces. The second was a lifting mode based on continuous loading and gradual adjustment of the magnetic-force upper bound to locally lift a flexible “mucosa-like” membrane, thereby simulating intestinal mucosal elevation and local visual field expansion. Experimental results showed that the robot could stably pass through narrow tunnels and effectively lift an overlying flexible membrane under vertical magnetic-force actuation. The proposed method extends both the locomotion capability and the local interaction capability of the mudskipper-inspired magnetic microrobot, and demonstrates a feasible proof-of-concept approach for confined-space navigation and localized manipulation in intestinal applications. Full article

Rectangular waveguides, serving as a standardized versatile platform for manipulating terahertz radiation within controlled environments, have been extensively employed across a broad range of terahertz systems. However, conventional fabrication methods encounter significant challenges in realizing such submillimeter-scale structures within a monolithic integration, particularly when subwavelength features or intricate geometries are incorporated for advanced functionalities. In this work, we propose a fabrication route integrating stereolithography 3D printing and electroless plating, and demonstrate its broad applicability, intrinsic benefits and limitations through the realization of various high-performance D-band terahertz rectangular waveguides and antennas. The resulting rectangular waveguides achieve an insertion loss below 0.3 dB and a return loss above 15 dB across the D-band, while remaining stable across extreme temperatures (−50 °C to 150 °C) and offering a weight reduction of over 60%. A monolithically fabricated smooth-walled conical horn antenna exhibits beam-shaping characteristics that closely align with theoretical expectations. Attempts on corrugated horn antennas in conventional design reveal degraded performance, primarily arising from the inherent staircase effect associated with 3D printing. A novel design featuring obliquely oriented corrugations is developed, effectively mitigating uncontrolled deformation in periodic subwavelength features. Compared with the classical corrugated design (θ = 90°), the proposed obliquely oriented corrugations (θ = 30°) improve the agreement between experimental and theoretical radiation patterns, reducing the gain deviation from 1.45 dB to less than 0.5 Db—a quantitative improvement of over 60% in pattern fidelity. We believe that this fabrication route together with the process-adaptive design paradigm establishes a robust technical foundation for realizing high-performance, lightweight, and design-flexible terahertz waveguide components and holds significant promise for advancing the development of next-generation integrated terahertz systems. Full article

Many hands-on tasks remain difficult to fully automate because they require human dexterity and flexible object handling. Data gloves offer a promising interface for sensing hand–object interactions, but most prior systems focus on gesture recognition or object classification rather than closed-loop, step-by-step task guidance. In this work, we develop and evaluate a tactile-sensing operation support system using an e-textile data glove with 88 pressure sensors, a tactile pressure sheet for placement verification, and a GUI that provides step-by-step instructions. As a core component, a CNN classifies the grasped state as bare hand or one of four discs with 93.3% accuracy using 16,175 training samples collected from five participants. In a user study on the Tower of Hanoi task as a controlled proxy for multi-step manipulation, the system reduced mean solving time by 51.5% (from 242.6 s to 117.8 s), reduced the number of disc movements (35.4 to 15, about 20 fewer moves on average), and lowered perceived workload (NASA-TLX) by 53.1% (from 68.5 to 32.1), while achieving a SUS score of 75. These results demonstrate the feasibility of tactile-based step verification and guidance in a controlled multi-step task; broader generalization requires evaluation with larger and more diverse participant groups and tasks. Full article

Children are often underserved by adult-oriented oral medicines, leading to off-label use and dosage-form manipulation that may compromise dosing accuracy. This review summarises recent advances in paediatric orodispersible tablets (ODTs), focusing on manufacturing technologies, superdisintegrants, taste masking, and in vitro disintegration testing. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidance and a protocol registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (registration number INPLASY2025110022), we searched PubMed, EMBASE, MEDLINE, Scopus, and Google Scholar for experimental studies on paediatric-relevant ODT formulation and evaluation. Two reviewers screened studies and extracted data on manufacturing methods, excipients, disintegration/dissolution testing, and key outcomes. Risk of bias was assessed using a six-domain framework. Overall, 65 studies met the inclusion criteria for this review. Direct compression was the dominant method, with freeze-drying, sublimation, spray-drying, nanoparticle-in-tablet systems, and semi-solid extrusion/3D printing also reported. Crospovidone, croscarmellose sodium, and sodium starch glycolate were the most common superdisintegrants, while natural and co-processed disintegrants showed promise as cost-effective alternatives. Disintegration was usually assessed using pharmacopoeial methods, with some modified set-ups to better simulate oral conditions. Paediatric ODT development is advancing rapidly. Broader translation requires harmonised disintegration testing, age-stratified acceptability reporting, and GMP-ready workflows, alongside benchmarking of superdisintegrants and attention to dose flexibility, packaging, and affordability. Full article

This paper details the development of an autonomous robotic solution for the long-term surveillance of low-level radiation in nuclear facilities. Implementing such a system mitigates personnel health risks by minimizing radiation exposure and automating a mundane, repetitive task. To address the inherent challenges of deploying robots in highly unstructured environments, the core contribution of this work is a novel, error-tolerant behavioral architecture. Specifically, a custom behavior tree is designed to absorb execution imperfections and tolerate environmental uncertainties. This allows the robot to adapt and continue its mission rather than experiencing a hard failure. Bayesian optimization is utilized to perform adaptive mapping via a manipulator-equipped Spot quadruped robot, which features a Kromek Sigma50 gamma spectrometer attached to its end effector. Experiments were conducted in an obstacle-rich testbed using a Cesium-137 source. The results demonstrate the feasibility of the proposed system and its behavioral design approach, as the robot successfully performed adaptive mapping and correctly identified the location and approximate intensity of the radiation source. Full article

Digital Twin (DT) systems combining physics-based simulation with hardware execution are critical for Industry 4.0 manufacturing, yet proprietary software solutions remain expensive and platform-dependent. This work addresses three technical challenges: maintaining geometric and kinematic fidelity across CAD-to-simulation conversion pipelines, synchronizing dual physics engines (Unity and ROS middleware) under hardware latency constraints, and optimizing motion planning while preserving trajectory quality and interactive responsiveness. We developed an integrated framework for a 7-Degree-of-Freedom manipulator using CAD modeling, URDF/SRDF semantic representation, and bidirectional Unity-ROS (Robot Operating System) communication via WebSocket connectors. Motion planning uses RRTConnect from OMPL with collision-aware optimization through the Flexible Collision Library. Validation across 12 manipulation trials demonstrated positional synchronization accuracy of ±2.0 degrees, motion planning performance of 0.064 ± 0.020 s. Latency analysis reveals that hardware execution is the dominant system bottleneck, significantly exceeding network communication delays. The system achieves performance metrics comparable to proprietary industrial solutions. This work establishes a replicable, cost-effective Industry 4.0 framework, demonstrating that modern game engine technology combined with open-source robotics middleware can deliver DT systems matching proprietary solutions. The architecture and validated implementation enable adaptation to alternative robotic platforms and support broader adoption of simulation-validated automation in manufacturing contexts. Full article

Speckle patterns generated by coherent illumination of random media are ubiquitous in optical imaging and information processing. However, most existing studies have primarily focused on isotropic or homogeneous speckle fields, while controlled manipulation of speckle patterns with customized geometric morphologies has received comparatively little attention. Here, we propose a random phase-coded array (RPA) as a general framework for generating geometrically reshaped speckle, enabling the formation of nonconventional random light fields whose ensemble-averaged intensity distributions follow prescribed geometric shapes. In this framework, the speckle geometry is determined by the unit-cell structure of the RPA, the unit-cell size governs the overall spatial extent of the speckle pattern, and the illuminating beam size sets the characteristic speckle grain size. These relationships are rigorously validated through theoretical derivations and numerical simulations. As a result, the global statistical envelope of the random light field can be intuitively and flexibly controlled without compromising the fully developed speckle characteristics. Our experimental framework offers a straightforward, scalable, and versatile approach for generating customized random light fields, with potential applications in optical information processing, secure optical communication, computational imaging, and speckle-based metrology. Full article