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1. Self-oscillating, self-stabilizing, and self-referenced electro-optic comb

   https://doi.org/10.1364/OE.535014  

   Trask, Lawrence_Robert; Pericherla, Srinivas_Varma; Delfyett, Peter_J (January 2025, Optics Express)

   We demonstrate a widely spaced, stabilized, and self-referenced opto-electronic oscillator driven electro-optic modulator based optical frequency comb. Using an ultra-stable Fabry-Perot etalon as a stable reference, we simultaneously stabilize a CW laser and generate a low noise and stable RF oscillation used to drive an electro-optic comb. In such a manner, the Fabry-Perot etalon pins both the carrier-envelope-offset frequency (f_ceo) and the repetition rate of the comb in place (f_rep), eliminating the need for an external RF oscillator. Usage of the ultra-stable Fabry-Perot etalon as both an optical and RF reference allows the removal of an external RF oscillator. Additionally, we determined the key parameters in producing high contrast ultrashort pulses necessary for coherent octave spanning supercontinuum generation using long and weak pulses associated with electro-optic modulator based combs. By using a monolithically fiber based pulse compression scheme, we produced ultrashort pulses to facilitate measuring the carrier-envelope-offset frequency, allowing for the first self-starting, self-stabilized, and self-referenced opto-electronic oscillator driven electro-optic modulator based optical frequency comb. 

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2. Multifunctional NMC-Si Batteries With Self-Actuation and Self-Sensing

   https://doi.org/10.1115/SMASIS2017-3886  

   Ma, Jun; Rahn, Christopher; Frecker, Mary (September 2017, 2018 SMASIS)
3. Manipulation for self-Identification, and self-Identification for better manipulation

   Hang, Kaiyu; Bircher, Walter G.; Morgan, Andrew S.; Dollar, Aaron M. (May 2021, Science robotics)
4. Manipulation for self-Identification, and self-Identification for better manipulation

   https://doi.org/10.1126/scirobotics.abe1321  

   Hang, Kaiyu; Bircher, Walter G.; Morgan, Andrew S.; Dollar, Aaron M. (May 2021, Science Robotics)

   The process of modeling a series of hand-object parameters is crucial for precise and controllable robotic in-hand manipulation because it enables the mapping from the hand’s actuation input to the object’s motion to be obtained. Without assuming that most of these model parameters are known a priori or can be easily estimated by sensors, we focus on equipping robots with the ability to actively self-identify necessary model parameters using minimal sensing. Here, we derive algorithms, on the basis of the concept of virtual linkage-based representations (VLRs), to self-identify the underlying mechanics of hand-object systems via exploratory manipulation actions and probabilistic reasoning and, in turn, show that the self-identified VLR can enable the control of precise in-hand manipulation. To validate our framework, we instantiated the proposed system on a Yale Model O hand without joint encoders or tactile sensors. The passive adaptability of the underactuated hand greatly facilitates the self-identification process, because they naturally secure stable hand-object interactions during random exploration. Relying solely on an in-hand camera, our system can effectively self-identify the VLRs, even when some fingers are replaced with novel designs. In addition, we show in-hand manipulation applications of handwriting, marble maze playing, and cup stacking to demonstrate the effectiveness of the VLR in precise in-hand manipulation control. 

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5. SELF-RAG: LEARNING TO RETRIEVE, GENERATE, AND CRITIQUE THROUGH SELF-REFLECTION

   Asai, Akari; Wu, Zeqiu; Wang, Yizhong; Sil, Avirup; Hajishirzi, Hannaneh (May 2024, ICLR)