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1. An ATPase with a twist: A unique mechanism underlies the activity of the bacterial tyrosine kinase, Wzc

   https://doi.org/10.1126/sciadv.abj5836  

   Hajredini, Fatlum; Ghose, Ranajeet (September 2021, Science Advances)

   BY-kinases constitute a protein tyrosine kinase family that encodes unique catalytic domains that deviate from those of eukaryotic kinases resembling P-loop nucleotide triphosphatases (NTPases) instead. We have used computational and supporting biochemical approaches using the catalytic domain of the Escherichia coli BY-kinase, Wzc, to illustrate mechanistic divergences between BY-kinases and NTPases despite their deployment of similar catalytic motifs. In NTPases, the “arginine finger” drives the reactive conformation of ATP while also displacing its solvation shell, thereby making favorable enthalpic and entropic contributions toward βγ-bond cleavage. In BY-kinases, the reactive state of ATP is enabled by ATP·Mg 2+ -induced global conformational transitions coupled to the conformation of the Walker-A lysine. While the BY-kinase arginine finger does promote the desolvation of ATP, it does so indirectly by generating an ordered active site in combination with other structural elements. Bacteria, using these mechanistic variations, have thus repurposed an ancient fold to phosphorylate on tyrosine. 

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2. Invariance Through Latent Alignment

   https://doi.org/10.15607/RSS.2022.XVIII.064  

   Yoneda, Takuma; Yang, Ge; Walter, Matthew R.; Stadie, Bradly C. (June 2022, Proceedings of Robotics: Science and Systems (RSS))

   A robot’s deployment environment often involves perceptual changes that differ from what it has experienced during training. Standard practices such as data augmentation attempt to bridge this gap by augmenting source images in an effort to extend the support of the training distribution to better cover what the agent might experience at test time. In many cases, however, it is impossible to know test-time distribution- shift a priori, making these schemes infeasible. In this paper, we introduce a general approach, called Invariance through Latent Alignment (ILA), that improves the test-time performance of a visuomotor control policy in deployment environments with unknown perceptual variations. ILA performs unsupervised adaptation at deployment-time by matching the distribution of latent features on the target domain to the agent’s prior experience, without relying on paired data. Although simple, we show that this idea leads to surprising improvements on a variety of challenging adaptation scenarios, including changes in lighting conditions, the content in the scene, and camera poses. We present results on calibrated control benchmarks in simulation—the distractor control suite—and a physical robot under a sim-to-real setup. Video and code available at: https: //invariance-through-latent-alignment.github.io 

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3. Enabling Fine-grained Finger Gesture Recognition on Commodity WiFi Devices

   https://doi.org/10.1109/TMC.2020.3045635  

   Tan, Sheng; Yang, Jie; Chen, Yingying (December 2020, IEEE Transactions on Mobile Computing)

   null (Ed.)

   Gesture recognition has become increasingly important in human-computer interaction and can support different applications such as smart home, VR, and gaming. Traditional approaches usually rely on dedicated sensors that are worn by the user or cameras that require line of sight. In this paper, we present fine-grained finger gesture recognition by using commodity WiFi without requiring user to wear any sensors. Our system takes advantages of the fine-grained Channel State Information available from commodity WiFi devices and the prevalence of WiFi network infrastructures. It senses and identifies subtle movements of finger gestures by examining the unique patterns exhibited in the detailed CSI. We devise environmental noise removal mechanism to mitigate the effect of signal dynamic due to the environment changes. Moreover, we propose to capture the intrinsic gesture behavior to deal with individual diversity and gesture inconsistency. Lastly, we utilize multiple WiFi links and larger bandwidth at 5GHz to achieve finger gesture recognition under multi-user scenario. Our experimental evaluation in different environments demonstrates that our system can achieve over 90% recognition accuracy and is robust to both environment changes and individual diversity. Results also show that our system can provide accurate gesture recognition under different scenarios. 

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4. Issues Related to Using Finger-Fitts law to Model One-Dimensional Touch Pointing Tasks

   https://doi.org/10.1145/3490355.3490360  

   Ko, Yu-Jung; Zhao, Hang; Ramakrishnan, IV; Zhai, Shumin; Bi, Xiaojun (October 2021, Ninth International Symposium of Chinese CHI (Chinese CHI 2021))

   Finger-Fitts law [6] is a variant of Fitts’ law which accounts for the finger ambiguity in touch pointing. In this paper we investigated two research questions related to Finger-Fitts law: (1) Should Finger-Fitts law use nominal target width W or effect target width We to model MT? and (2) should Finger-Fitts law use a pre-defined value (denoted by σa) or a free parameter (denoted by c) to represent the absolute ambiguity caused by finger touch? Our investigation on two touch pointing datasets showed that there are cases where using nominal width has stronger model fitness, and also cases where using effective width is better. Regarding the representation of finger ambiguity, using a free parameter c to represent the ambiguity of finger touch always leads to stronger model fitness than using the pre-defined σa, after controlling for overfitting. It indicates that viewing the finger ambiguity as an empirically determined parameter has more flexibility to capture the ambiguity of finger touch involved in the study. Overall, our research advances the understanding on how to model Finger touch input with Finger-Fitts law. 

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5. The ultrafast snap of a finger is mediated by skin friction

   https://doi.org/10.1098/rsif.2021.0672  

   Acharya, Raghav; Challita, Elio J.; Ilton, Mark; Saad Bhamla, M. (November 2021, Journal of The Royal Society Interface)

   null (Ed.)

   The snap of a finger has been used as a form of communication and music for millennia across human cultures. However, a systematic analysis of the dynamics of this rapid motion has not yet been performed. Using high-speed imaging and force sensors, we analyse the dynamics of the finger snap. We discover that the finger snap achieves peak angular accelerations of 1.6 × 10 6 ° s −2 in 7 ms, making it one of the fastest recorded angular accelerations the human body produces (exceeding professional baseball pitches). Our analysis reveals the central role of skin friction in mediating the snap dynamics by acting as a latch to control the resulting high velocities and accelerations. We evaluate the role of this frictional latch experimentally, by covering the thumb and middle finger with different materials to produce different friction coefficients and varying compressibility. In doing so, we reveal that the compressible, frictional latch of the finger pads likely operates in a regime optimally tuned for both friction and compression. We also develop a soft, compressible friction-based latch-mediated spring actuated model to further elucidate the key role of friction and how it interacts with a compressible latch. Our mathematical model reveals that friction plays a dual role in the finger snap, both aiding in force loading and energy storage while hindering energy release. Our work reveals how friction between surfaces can be harnessed as a tunable latch system and provides design insight towards the frictional complexity in many robotic and ultra-fast energy-release structures. 

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