Low-cost self-driving labs (SDLs) offer faster prototyping, low-risk hands-on experience, and a test bed for sophisticated experimental planning software which helps us develop state-of-the-art SDLs.
more » « less- PAR ID:
- 10500964
- Publisher / Repository:
- Digital Discovery
- Date Published:
- Journal Name:
- Digital Discovery
- ISSN:
- 2635-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract With the rise of self-driving labs (SDLs) and automated experimentation across chemical and materials sciences, there is a considerable challenge in designing the best autonomous lab for a given problem based on published studies alone. Determining what digital and physical features are germane to a specific study is a critical aspect of SDL design that needs to be approached quantitatively. Even when controlling for features such as dimensionality, every experimental space has unique requirements and challenges that influence the design of the optimal physical platform and algorithm. Metrics such as optimization rate are therefore not necessarily indicative of the capabilities of an SDL across different studies. In this perspective, we highlight some of the critical metrics for quantifying performance in SDLs to better guide researchers in implementing the most suitable strategies. We then provide a brief review of the existing literature under the lens of quantified performance as well as heuristic recommendations for platform and experimental space pairings.
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Abstract There exist linear relations among tensor entries of low rank tensors. These linear relations can be expressed by multi-linear polynomials, which are called generating polynomials. We use generating polynomials to compute tensor rank decompositions and low rank tensor approximations. We prove that this gives a quasi-optimal low rank tensor approximation if the given tensor is sufficiently close to a low rank one.
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SIGNIFICANCE Motion perception is an essential part of visual function. Understanding how people with low vision perceive motion can therefore inform rehabilitation strategies and assistive technology. Our study introduces the notion of Bayesian biases in motion perception and suggests that some people with low vision are susceptible to these systematic misperceptions.
PURPOSE We aimed to develop a paradigm that can efficiently characterize motion percepts in people with low vision and compare their responses with well-known misperceptions made by people with typical vision when targets are hard to see.
METHODS We recruited a small cohort of individuals with reduced acuity and contrast sensitivity (n = 5) as well as a comparison cohort with typical vision (n = 5) to complete a psychophysical study. Study participants were asked to judge the motion direction of a tilted rhombus that was either high or low contrast. In a series of trials, the rhombus oscillated vertically, horizontally, or diagonally. Participants indicated the perceived motion direction using a number wheel with 12 possible directions, and statistical tests were used to examine response biases.
RESULTS All participants with typical vision showed systematic misperceptions well predicted by a Bayesian inference model. Specifically, their perception of vertical or horizontal motion was biased toward directions orthogonal to the long axis of the rhombus. They had larger biases for hard-to-see (low contrast) stimuli. Two participants with low vision had a similar bias, but with no difference between high- and low-contrast stimuli. The other participants with low vision were unbiased in their percepts or biased in the opposite direction.
CONCLUSIONS Our results suggest that some people with low vision may misperceive motion in a systematic way similar to people with typical vision. However, we observed large individual differences. Future work will aim to uncover reasons for such differences and identify aspects of vision that predict susceptibility.
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Summary SUMOylation as one of the protein post‐translational modifications plays crucial roles in multiple biological processes of eukaryotic organisms.
Botrytis cinerea is a devastating fungal pathogen and capable of infecting plant hosts at low temperature. However, the molecular mechanisms of low‐temperature adaptation are largely unknown in fungi.Combining with biochemical methods and biological analyses, we report that SUMOylation regulates pathogen survival at low temperature and oxidative DNA damage response during infection in
B. cinerea . The heat shock protein (Hsp70) BcSsb and E3 ubiquitin ligase BcRad18 were identified as substrates of SUMOylation; moreover, their SUMOylation both requires a single unique SUMO‐interacting motif (SIM).SUMOylated BcSsb regulates β‐tubulin accumulation, thereby affecting the stability of microtubules and consequently mycelial growth at low temperature. On the contrary, SUMOylated BcRad18 modulates mono‐ubiquitination of the sliding clamp protein proliferating cell nuclear antigen (PCNA), which is involved in response to oxidative DNA damage during infection.
Our study uncovers the molecular mechanisms of SUMOylation‐mediated low‐temperature survival and oxidative DNA damage tolerance during infection in a devastating fungal pathogen, which provides novel insights into low‐temperature adaptation and pathogenesis for postharvest pathogens as well as new targets for inhibitor invention in disease control.