Permeability-selectivity trade-off for a universal leaky channel inspired by mobula filters.

Mobula rays have evolved leaf-shaped filter structures to separate food particles from seawater, which function similarly to industrial cross-flow filters. Unlike cross-flow filtration, where permeability and selectivity are rationally designed following trade-off analyses, the driving forces underlying the evolution of mobula filter geometry have remained elusive. To bridge the principles of cross-flow and mobula filtration, we establish a universal framework for the permeability-selectivity trade-off in a leaky channel inspired by mobula filters, where permeability and selectivity are characterized by the pore-scale leaking rate and the cut-off particle size, respectively.

Fatigue life prediction of composite materials using strain distribution images and a deep convolution neural network.

The damage process of composite materials, such as short fiber-reinforced plastics (SFRP), is complex. Therefore, it is necessary to accurately represent the damage process in fatigue life prediction. Herein, fatigue life prediction was conducted by combining the digital image correlation method, which is a non-destructive testing technique, with a convolutional neural network (CNN), using Xception as the network architecture.

Involvement of G-protein alpha subunit in soybean cyst nematode chemotaxis.

The soybean cyst nematode (SCN; Heterodera glycines Ichinohe) is a significant agricultural pest that causes extensive damage to soybean production worldwide. Second-stage juveniles (J2s) of the SCN migrate through the soil and infest the roots of host plants in response to certain chemical substances secreted from the host roots. Therefore, controlling SCN chemotaxis could be an effective strategy for its management.

Modeling Running via Optimal Control for Shoe Design.

Shoe manufacturing technology is advancing faster than new shoe designs can viably be evaluated in human subject trials. To aid in the design process, this paper presents a model for estimating how new shoe properties will affect runner performance. This model assumes runners choose their gaits to optimize an intrinsic, unknown objective function.

MOS4-associated complex contributes to proper splicing and suppression of ER stress under long-term heat stress in Arabidopsis.

Plants are often exposed not only to short-term (S-) but also to long-term (L-)heat stress over several consecutive days. A few Arabidopsis mutants defective in L-heat tolerance have been identified, but the molecular mechanisms are less understood for this tolerance than for S-heat stress tolerance. To elucidate the mechanisms of the former, we used a forward genetic screen for () mutants and isolated and .