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Snow Water Equivalent dataset contains information about snow water equivalent (SWE), temperature, precipitation, wind speed, relative humidity, and related climate variables across different locations and time periods. It includes daily observations and derived variables for hydrological and climate analysis. An additional column, source, specifies the origin of each data column. 

Quantum sensing with nitrogen vacancy (NV) color center defects in diamond was optimized with hardware and machine learning approaches, which led to the development of small footprint quantum sensor devices. 

Evolutionary radiations generate most of Earth’s biodiversity, but are there common ecomorphological traits among the progenitors of radiations? In Synapsida (the mammalian total group), ‘small-bodied faunivore’ has been hypothesized as the ancestral state of most major radiating clades, but this has not been quantitatively assessed across multiple radiations. To examine macroevolutionary patterns in a phylogenetic context, we generated a time-calibrated metaphylogeny (‘metatree’) comprising 1,888 synapsid species from the Carboniferous through the Eocene (305–34 Ma) based on 269 published character matrices. We used comparative methods to investigate body size and dietary evolution during successive synapsid radiations. Faunivory is the ancestral dietary regime of each major synapsid radiation, but relatively small body size is only established as the common ancestral state of radiations near the origin of Mammaliaformes in the Late Triassic. The faunivorous ancestors of synapsid radiations typically have numerous novel characters compared with their contemporaries, and these derived traits may have helped them to survive faunal turnover events and subsequently radiate. 

Radio frequency (RF) signals are frequently used in emerging quantum applications due to their spin state manipulation capability. Efficient coupling of RF signals into a particular quantum system requires the utilization of carefully designed and fabricated antennas. Nitrogen vacancy (NV) defects in diamond are commonly utilized platforms in quantum sensing experiments with the optically detected magnetic resonance (ODMR) method, where an RF antenna is an essential element. We report on the design and fabrication of high efficiency coplanar RF antennas for quantum sensing applications. Single and double ring coplanar RF antennas were designed with −37 dB experimental return loss at 2.87 GHz, the zero-field splitting frequency of the negatively charged NV defect in diamond. The efficiency of both antennas was demonstrated in magnetic field sensing experiments with NV color centers in diamond. An RF amplifier was not needed, and the 0 dB output of a standard RF signal generator was adequate to run the ODMR experiments due to the high efficiency of the RF antennas. 

We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally linear with an additive nonlinear component. Such systems commonly model the nonlinear effects of an unknown environment on a nominal system. We optimize over a class of nonlinear feedback policies inspired by certainty equivalent "estimate-and-cancel" control laws pioneered in classical adaptive control to achieve significant performance improvements in the presence of uncertainties of large magnitude, a setting in which existing learning-based predictive control algorithms often struggle to guarantee safety. In contrast to previous work in robust adaptive MPC, our approach allows us to take advantage of structure (i.e., the numerical predictions) in the a priori unknown dynamics learned online through function approximation. Our approach also extends typical nonlinear adaptive control methods to systems with state and input constraints even when we cannot directly cancel the additive uncertain function from the dynamics. Moreover, we apply contemporary statistical estimation techniques to certify the system’s safety through persistent constraint satisfaction with high probability. Finally, we show in simulation that our method can accommodate more significant unknown dynamics terms than existing methods.