Lateral migration is the motion of a particle perpendicular to the direction of the surrounding flow. One of the factors leading to the lateral migration of a deformable particle in Stokes flow is the presence of a nearby wall. We numerically investigate the lateral migration of a capsule in a near-wall simple shear flow using a boundary integral method coupled with a finite element method. We find that asymmetrical deformation of the capsule induced by the wall is correlated with a reduction in the lift velocity relative to the lift velocity predicted by a far-field analytical solution. A combination of this asymmetrical deformation, which decreases the lift velocity, and an increase in the value of the capsule stresslet near the wall, which works to increase the lift velocity, leads to a migration velocity that is nearly independent of capillary number and membrane constitutive law at large deformation near the wall.

This study was conducted using a drone with advanced mobility to develop a unified sensor and communication system as a new platform for in situ atmospheric measurements. As a major cause of air pollution, particulate matter (PM) has been attracting attention globally. We developed a small, lightweight, simple, and cost-effective multi-sensor system for multiple measurements of atmospheric phenomena and related environmental information. For in situ local area measurements, we used a long-range wireless communication module with real-time monitoring and visualizing software applications. Moreover, we developed four prototype brackets with optimal assignment of sensors, devices, and a camera for mounting on a drone as a unified system platform. Results of calibration experiments, when compared to data from two upper-grade PM2.5 sensors, demonstrated that our sensor system followed the overall tendencies and changes. We obtained original datasets after conducting flight measurement experiments at three sites with differing surrounding environments. The experimentally obtained prediction results matched regional PM2.5 trends obtained using long short-term memory (LSTM) networks trained using the respective datasets.

At the level of organ formation, tissue morphogenesis drives developmental processes in animals, often involving the rearrangement of two-dimensional (2D) structures into more complex three-dimensional (3D) tissues. These processes can be directed by growth factor signaling pathways. However, little is known about how such morphological changes affect the spatiotemporal distribution of growth factor signaling. Here, using theDrosophilapupal wing, we address how decapentaplegic (Dpp)/bone morphogenetic protein (BMP) signaling and 3D wing morphogenesis are coordinated. Dpp, expressed in the longitudinal veins (LVs) of the pupal wing, initially diffuses laterally within both dorsal and ventral wing epithelia during the inflation stage to regulate cell proliferation. Dpp localization is then refined to the LVs within each epithelial plane, but with active interplanar signaling for vein patterning/differentiation, as the two epithelia appose. Our data further suggest that the 3D architecture of the wing epithelia and the spatial distribution of BMP signaling are tightly coupled, revealing that 3D morphogenesis is an emergent property of the interactions between extracellular signaling and tissue shape changes.

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This study was conducted to develop robot prototypes of three models that navigate mallards to achieve high-efficiency rice-duck farming. We examined two robotics navigation approaches based on imprinting and feeding. As the first approach, we used imprinting applied to baby mallards. They exhibited follow behavior to our first prototype after imprinting. Experimentally obtained observation results revealed the importance of providing imprinting immediately up to one week after hatching. As another approach, we used feed placed on the top of our second prototype. Experimentally obtained results showed that adult mallards exhibited wariness not only against the robot, but also against the feeder. After relieving wariness with provision of more than one week time to become accustomed, adult mallards ate feed in the box on the robot. However, they ran away immediately at a slight movement. Based on this confirmation, we developed the third prototype as an autonomous mobile robot aimed for mallard navigation in a paddy field. The body width is less than the length between rice stalks. After checking the waterproof capability of a body waterproof box, we conducted an indoor driving test for manual operation. Moreover, we conducted outdoor evaluation tests to assess running on an actual paddy field. We developed indoor and outdoor image datasets using an onboard monocular camera. For the outdoor image datasets, our segmentation method based on SegNet achieved semantic segmentation for three semantic categories. For the indoor image datasets, our prediction method based on CNN and LSTM achieved visual prediction for three motion categories.

We developed a numerical model of the behavior of a red blood cell infected by Plasmodium falciparum malaria on a wall in shear flow. The fluid and solid mechanics of an infected red blood cell (Pf-IRBC) were coupled with the biochemical interaction of ligand-receptor bindings. We used the boundary element method for fluid mechanics, the finite element method for membrane mechanics, and the Monte Carlo method for ligand-receptor interactions. We simulated the behavior of a Pf-IRBC in shear flow, focusing on the effects of bond type. For slip bonds, the Pf-IRBC exhibited firm adhesion, tumbling motion, and tank-treading motion, depending on the applied shear rate. The behavior of catch bonds resembled that of slip bonds, except for a 'catch' state at high shear stress. When the reactive compliance decreased to a value in the order of 10 −2 nm, both the slip and catch bonds behaved like an ideal bond. Such bonds do not respond to the force applied to the bond, and the velocity is stabilized at a high shear rate. Finally, we compared the numerical results with previous experiments for A4-and ItG-infected cells. We found that the interaction between PfEMP1 and ICAM-1 could be a nearly ideal bond, with a dissociation rate ranging from 30 s −1 to 100 s −1 .

Drones equipped with a global navigation satellite system (GNSS) receiver for absolute localization provide high-precision autonomous flight and hovering. However, the GNSS signal reception sensitivity is considerably lower in areas such as those between high-rise buildings, under bridges, and in tunnels. This paper presents a drone localization method based on acoustic information using a microphone array in GNSS-denied areas. Our originally developed microphone array system comprised 32 microphones installed in a cross-shaped configuration. Using drones of two different sizes and weights, we obtained an original acoustic outdoor benchmark dataset at 24 points. The experimentally obtained results revealed that the localization error values were lower for 0∘ and ±45∘ than for ±90∘. Moreover, we demonstrated the relative accuracy for acceptable ranges of tolerance for the obtained localization error values.

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