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Abstract Accurately specifying polar ionospheric electrodynamics is essential for understanding energy and momentum exchange between space and the upper atmosphere and for improving simulations of the ionosphere and the thermosphere. Statistical models are commonly used to provide input for global circulation models (GCMs). However, maps derived from simultaneous multi-instrument observations better represent the actual state of the system. Such maps integrate measurements from ground-based magnetometers and radars, in situ plasma and magnetic field sensors at low-Earth orbit, and optical and particle observations of auroral precipitation. However, ionospheric data assimilation remains in its early stages. Current methods rely on restrictive assumptions to simplify equations and stabilize inverse problems, but these constraints limit applicability beyond polar regions, hinder the inclusion of time-dependent processes, and prevent independent estimation of ionospheric conductance. This review examines the physical foundations of ionospheric data assimilation, evaluates the limitations of existing approaches, and explores pathways toward more accurate and flexible techniques. Specifically, we discuss approaches to: (1) use a common dataset to estimate conductance and fields in a single inversion; (2) incorporate neutral winds instead of assuming they are zero; (3) account for a realistic main magnetic field geometry instead of assuming radial field lines; (4) eliminate a sharp boundary between polar and low-latitude regions; (5) use F-region density measurements to capture the history of ionospheric conductance and plasma transport; (6) account for the magnetic field of ground-induced currents in a more realistic way; (7) include ionospheric induction effects to stabilize time-dependent inversions; and (8) couple ionospheric electrodynamics with global magnetosphere simulations to model the physics of time variations. 

Carbon dioxide (CO₂) assimilation by the enzyme Ribulose-1,5-bisphosphate Carboxylase/Oxygenase (Rubisco) underpins biomass accumulation in photosynthetic bacteria and eukaryotes. Despite its pivotal role, Rubisco has a slow carboxylation rate ( $k_{\mathit{cat}}^{{\mathit{CO}}_2}$ ) and is competitively inhibited by oxygen (O₂). These traits impose limitations on photosynthetic efficiency, making Rubisco a compelling target for improvement. Interest in Form II Rubisco fromGallionellaceaebacteria, which comprise a dimer or hexamer of large subunits, arises from their nearly fivefold higher $k_{\mathit{cat}}^{{\mathit{CO}}_2}$ than the average Rubisco enzyme. As well as having a fast $k_{\mathit{cat}}^{{\mathit{CO}}_2}$ (25.8 s⁻¹at 25 °C), we show thatGallionellaceaeRubisco (GWS1B) is extremely sensitive to O₂inhibition, consistent with its evolution under semianaerobic environments. We therefore used an in vivo mutagenesis-mediated screening pipeline to evolve GWS1B over six rounds under oxygenic selection, identifying three catalytic point mutants with improved ambient carboxylation efficiency: Thr-29-Ala (T29A), Glu-40-Lys (E40K), and Arg-337-Cys (R337C). Full kinetic characterization showed that each substitution enhanced the CO₂affinity of GWS1B under oxygenic conditions by subduing oxygen affinity, leading to 25% (E40K), 11% (T29A), and 8% (R337C) enhancements in carboxylation efficiency under ambient O₂at 25 °C. By contrast, under the near anaerobic natural environment ofGallionellaceae, the carboxylation efficiency of each mutant was impaired ~16%. These findings demonstrate the efficacy of artificial directed evolution to access distinctive regions of catalytic space in Rubisco. 

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. 

ABSTRACT Collagen type II (Col-II) and collagen type I (Col-I) are major components of articular cartilage present at different ratios at its surface. Understanding how each of these components mediates the assembly of molecular films derived from synovial fluid (SF), the native lubricant of synovial joints, is critical to explain the loss of mechanical performance in pathological conditions, guide the design of biomaterial implants meant to be in contact with SF, and develop molecular therapies to restore SF properties. This work demonstrates that Col-II articular surface model assists in scaffolding of full SF-derived films, while Col-I model lacks SF film scaffolding capabilities. However, when Col-II and Col-I are exposed to recombinant lubricin (rLub) alone, the major boundary lubricant in SF, both adsorbed and retained similar amounts. These insights, deduced from quartz crystal microbalance with dissipation, diffuse reflectance circular dichroism, and atomic force microscopy, reveal possible mechanisms underlying the loss of mechanical performance of synovial joints in pathology, where Col-I becomes the major collagenous component of the articular cartilage surface, as well as considerations for designing functional biomaterial implants. Furthermore, this work reinforces the idea of rLub as an intra-articular osteoarthritis therapy with the ability to bind to Col-II and Col-I, irrespectively. GRAPHICAL ABSTRACT 

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. 

ABSTRACT We present ground-based multiband light curves of the AGN Mrk 509, NGC 4151, and NGC 4593 obtained contemporaneously with Swift monitoring. We measure cross-correlation lags relative to Swift UVW2 (1928 Å) and test the standard prediction for disc reprocessing, which assumes a geometrically thin optically thick accretion disc where continuum interband delays follow the relation $$\tau (\lambda) \propto \lambda ^{4/3}$$. For Mrk 509 the 273-d Swift campaign gives well-defined lags that increase with wavelength as $$\tau (\lambda)\propto \lambda ^{2.17\pm 0.2}$$, steeper than the thin-disc prediction, and the optical lags are a factor of $$\sim 5$$ longer than expected for a simple disc-reprocessing model. This ‘disc-size discrepancy’ as well as excess lags in the u and r bands (which include the Balmer continuum and H $$\alpha$$, respectively) suggest a mix of short lags from the disc and longer lags from nebular continuum originating in the broad-line region. The shorter Swift campaigns, 69 d on NGC 4151 and 22 d on NGC 4593, yield less well-defined shorter lags $< 2$ d. The NGC 4593 lags are consistent with $$\tau (\lambda) \propto \lambda ^{4/3}$$ but with uncertainties too large for a strong test. For NGC 4151 the Swift lags match $$\tau (\lambda) \propto \lambda ^{4/3}$$, with a small U-band excess, but the ground-based lags in the r, i, and z bands are significantly shorter than the B and g lags, and also shorter than expected from the thin-disc prediction. The interpretation of this unusual lag spectrum is unclear. Overall these results indicate significant diversity in the $$\tau \!-\!\lambda$$ relation across the optical/UV/NIR, which differs from the more homogeneous behaviour seen in the Swift bands.