Despite growing use of mechanical circulatory support, limitations remain related to hemocompatibility. Here, we performed a head-to-head comparison of the hemocompatibility of a centrifugal cardiac assist system—the Centrimag, with that of the latest generation of an intravascular microaxial system—the Impella 5.5. Specifically, hemolysis, platelet activation, microparticle (MP) generation, and von Willebrand factor (vWF) degradation were evaluated for both devices. Freshly obtained porcine blood was recirculated within device propelled mock loops for 4 hours, and alteration of the hemocompatibility parameters was monitored over time. We found that the Impella 5.5 and Centrimag exhibited low levels of hemolysis, as indicated by minor increase in plasma free hemoglobin. Both devices did not induce platelet degranulation, as no alteration of β-thromboglobulin and P-selectin in plasma occurred, rather minor downregulation of platelet surface P-selectin was detected. Furthermore, blood exposure to shear stress via both Centrimag and Impella 5.5 resulted in a minor decrease of platelet count with associated ejection of procoagulant MPs, and a decrease of vWF functional activity (but not plasma level of vWF-antigen). Greater MP generation was observed with the Centrimag relative to the Impella 5.5. Thus, the Impella 5.5 despite having a lower profile and higher impeller rotational speed demonstrated good and equivalent hemocompatibility, in comparison with the predicate Centrimag, with the advantage of lower generation of MPs.

High power density, good controllability and low cost are the most appealing characteristics that make hydraulic systems the best choice for many applications. Current state of the art hydraulic variable displacement pumps show high efficiency at high displacement while they have poor efficiencies at low displacement. This paper proposes a novel alternating flow (AF) variable displacement hydraulic pump to 1) eliminate metering losses by acting as a high-bandwidth pump for displacement control, 2) achieve high efficiency across a wide range of operating conditions and displacements, and 3) allow multiple units to be easily common-shaft mounted for a compact multi-actuator displacement control system from a single prime-mover. A dynamic model using first principles describes the cylinder pressure, flows between pairs of cylinders, and net inlet and outlet flows as a function of the pump's phase shift angle. The model captures hydraulic check valve dynamics, the effective bulk modulus, leakage flows, and viscous friction. Piston kinematics and dynamics are discussed and energy loss models are presented. A first prototype of the AF pump was constructed from two inline triplex pumps that were modified so that three piston pairs were created. Experiment tests were conducted and used to validate the model. After model validation, simulation results from the model can offer an initial evaluation of this novel pump concept and potential applications and can be used to guide the design for future prototype of the AF hydraulic pump.

Human-object interaction (HOI) detection aims to interpret the interactions of human-object pairs. Existing methods adopt a one-step reasoning paradigm that simultaneously outputs multi-label results for all HOI pairs without distinguishing difficulties. However, there are significant variations among HOI pairs in the same image, making their performance degrade in challenging situations. In this paper, we argue that the model should prioritize hard samples after inferring easy ones, and hard samples can benefit from easy ones. To this end, we propose a novel Multi-step Reasoning Network that progressively learns from easy to hard samples. In particular, an Easy-to-Hard Learning Block is introduced to enhance the representation of hard HOI pairs by prior associations. Additionally, we propose a Multi-step Reasoning Probability Transfer mechanism to enhance multi-label interaction classifications, which leverages cognitive associations and semantic dependencies. Extensive experiments demonstrate that our method outperforms other state-of-the-art on two challenging benchmark datasets.

Quadrotor unmanned aerial vehicles (UAVs) have emerged as ubiquitous and agile robots and data carriers within the framework of the future Internet of Things (IoT) and mobile wireless networks. Yet, the insufficient onboard battery necessitates the optimization of energy consumption for both the UAV and IoT devices while ensuring that communication requirements are met. This paper therefore proposes a more accurate and mathematically tractable model for characterizing a UAV’s energy consumption concerning desired trajectories. This nonlinear model takes into account the UAV’s dynamics, brushless direct current (BLDC) motor dynamics, and aerodynamics. To optimize the communication time between IoT devices and the UAV, IoT devices are clustered using a modified GAK-means algorithm, with dynamically optimized communication coverage radii. Subsequently, a fly–circle–communicate (FCC) trajectory design algorithm is introduced and derived to conserve energy and save mission time. Under the FCC approach, the UAV sequentially visits the cluster centers and performs circular flight and communication. Transitions between cluster centers are smoothed via 3D Dubins curves, which provide physically achievable trajectories. Comprehensive numerical studies indicate that the proposed trajectory planning method reduces overall communication time and preserves UAV battery energy compared to other benchmark schemes.