T-loop phosphorylation of Arabidopsis CDKA;1 is required for its function and can be partially substituted by an aspartate residue

As in other eukaryotes, progression through the cell cycle in plants is governed by cyclin-dependent kinases. Phosphorylation of a canonical Thr residue in the T-loop of the kinases is required for high enzyme activity in animals and yeast. We show that the Arabidopsis thaliana Cdc21/Cdc28 homolog CDKA; 1 is also phosphorylated in the T-loop and that phosphorylation at the conserved Thr-161 residue is essential for its function. A phospho-mimicry T161D substitution restored the primary defect of cdka; 1 mutants, and although the T161D substitution displayed a dramatically reduced kinase activity with a compromised ability to bind substrates, homozygous mutant plants were recovered. The rescue by the T161D substitution, however, was not complete, and the resulting plants displayed various developmental abnormalities. For instance, even though flowers were formed, these plants were completely sterile as a result of a failure of the meiotic program, indicating that different requirements for CDKA; 1 function are needed during plant development

Andreev Reflection in Heavy-Fermion Superconductors and Order Parameter Symmetry in CeCoIn_5

Differential conductance spectra are obtained from nanoscale junctions on the heavy-fermion superconductor CeCoIn$_5$ along three major crystallographic orientations. Consistency and reproducibility of characteristic features among the junctions ensure their spectroscopic nature. All junctions show a similar conductance asymmetry and Andreev reflection-like conductance with reduced signal (~ 10%-13%), both commonly observed in heavy-fermion superconductor junctions. Analysis using the extended Blonder-Tinkham-Klapwijk model indicates that our data provide the first spectroscopic evidence for $d_{x^2-y^2}$ symmetry. To quantify our conductance spectra, we propose a model by considering the general phenomenology in heavy fermions, the two-fluid behavior, and an energy-dependent density of states. Our model fits to the experimental data remarkably well and should invigorate further investigations.Comment: 4 pages, 4 figures; Phys. Rev. Lett., published versio

Universal phase shift and non-exponential decay of driven single-spin oscillations

We study, both theoretically and experimentally, driven Rabi oscillations of a single electron spin coupled to a nuclear spin bath. Due to the long correlation time of the bath, two unusual features are observed in the oscillations. The decay follows a power law, and the oscillations are shifted in phase by a universal value of ~pi/4. These properties are well understood from a theoretical expression that we derive here in the static limit for the nuclear bath. This improved understanding of the coupled electron-nuclear system is important for future experiments using the electron spin as a qubit.Comment: Main text: 4 pages, 3 figures, Supplementary material: 2 pages, 3 figure

Machine learning calibration of low-cost NO2 and PM10 sensors: non-linear algorithms and their impact on site transferability

Low-cost air pollution sensors often fail to attain sufficient performance compared with state-of-the-art measurement stations, and they typically require expensive laboratory-based calibration procedures. A repeatedly proposed strategy to overcome these limitations is calibration through co-location with public measurement stations. Here we test the idea of using machine learning algorithms for such calibration tasks using hourly-averaged co-location data for nitrogen dioxide (NO2) and particulate matter of particle sizes smaller than 10 µm (PM10) at three different locations in the urban area of London, UK. We compare the performance of ridge regression, a linear statistical learning algorithm, to two non-linear algorithms in the form of random forest regression (RFR) and Gaussian process regression (GPR). We further benchmark the performance of all three machine learning methods relative to the more common multiple linear regression (MLR). We obtain very good out-of-sample R2 scores (coefficient of determination) >0.7, frequently exceeding 0.8, for the machine learning calibrated low-cost sensors. In contrast, the performance of MLR is more dependent on random variations in the sensor hardware and co-located signals, and it is also more sensitive to the length of the co-location period. We find that, subject to certain conditions, GPR is typically the best-performing method in our calibration setting, followed by ridge regression and RFR. We also highlight several key limitations of the machine learning methods, which will be crucial to consider in any co-location calibration. In particular, all methods are fundamentally limited in how well they can reproduce pollution levels that lie outside those encountered at training stage. We find, however, that the linear ridge regression outperforms the non-linear methods in extrapolation settings. GPR can allow for a small degree of extrapolation, whereas RFR can only predict values within the training range. This algorithm-dependent ability to extrapolate is one of the key limiting factors when the calibrated sensors are deployed away from the co-location site itself. Consequently, we find that ridge regression is often performing as good as or even better than GPR after sensor relocation. Our results highlight the potential of co-location approaches paired with machine learning calibration techniques to reduce costs of air pollution measurements, subject to careful consideration of the co-location training conditions, the choice of calibration variables and the features of the calibration algorithm

Seismic modeling using the frozen Gaussian approximation

We adopt the frozen Gaussian approximation (FGA) for modeling seismic waves. The method belongs to the category of ray-based beam methods. It decomposes seismic wavefield into a set of Gaussian functions and propagates these Gaussian functions along appropriate ray paths. As opposed to the classic Gaussian-beam method, FGA keeps the Gaussians frozen (at a fixed width) during the propagation process and adjusts their amplitudes to produce an accurate approximation after summation. We perform the initial decomposition of seismic data using a fast version of the Fourier-Bros-Iagolnitzer (FBI) transform and propagate the frozen Gaussian beams numerically using ray tracing. A test using a smoothed Marmousi model confirms the validity of FGA for accurate modeling of seismic wavefields.Comment: 5 pages, 8 figure

Detection of single electron spin resonance in a double quantum dot

Spin-dependent transport measurements through a double quantum dot are a valuable tool for detecting both the coherent evolution of the spin state of a single electron as well as the hybridization of two-electron spin states. In this paper, we discuss a model that describes the transport cycle in this regime, including the effects of an oscillating magnetic field (causing electron spin resonance) and the effective nuclear fields on the spin states in the two dots. We numerically calculate the current flow due to the induced spin flips via electron spin resonance and we study the detector efficiency for a range of parameters. The experimental data are compared with the model and we find a reasonable agreement.Comment: 7 pages, 5 figures. To be published in Journal of Applied Physics, proceedings ICPS 200

Spin-echo of a single electron spin in a quantum dot

We report a measurement of the spin-echo decay of a single electron spin confined in a semiconductor quantum dot. When we tip the spin in the transverse plane via a magnetic field burst, it dephases in 37 ns due to the Larmor precession around a random effective field from the nuclear spins in the host material. We reverse this dephasing to a large extent via a spin-echo pulse, and find a spin-echo decay time of about 0.5 microseconds at 70 mT. These results are in the range of theoretical predictions of the electron spin coherence time governed by the dynamics of the electron-nuclear system.Comment: 5 pages, 4 figure

Nuclear Spin Effects in Semiconductor Quantum Dots

The interaction of an electronic spin with its nuclear environment, an issue known as the central spin problem, has been the subject of considerable attention due to its relevance for spin-based quantum computation using semiconductor quantum dots. Independent control of the nuclear spin bath using nuclear magnetic resonance techniques and dynamic nuclear polarization using the central spin itself offer unique possibilities for manipulating the nuclear bath with significant consequences for the coherence and controlled manipulation of the central spin. Here we review some of the recent optical and transport experiments that have explored this central spin problem using semiconductor quantum dots. We focus on the interaction between $10^4-10^6$ nuclear spins and a spin of a single electron or valence-band hole. We also review the experimental techniques as well as the key theoretical ideas and the implications for quantum information science.Physic

Difficult phylogenetic questions: more data, maybe; better methods, certainly

Contradicting the prejudice that endosymbiosis is a rare phenomenon, Husník and co-workers show in BMC Biology that bacterial endosymbiosis has occured several times independently during insect evolution. Rigorous phylogenetic analyses, in particular using complex models of sequence evolution and an original site removal procedure, allow this conclusion to be established after eschewing inference artefacts that usually plague the positioning of highly divergent endosymbiont genomic sequences

Multiple Nuclear Polarization States in a Double Quantum Dot

We observe multiple stable states of nuclear polarization in a double quantum dot under conditions of electron spin resonance. The stable states can be understood within an elaborated theoretical rate equation model for the polarization in each of the dots, in the limit of strong driving. This model also captures unusual features of the data, such as fast switching and a `wrong' sign of polarization. The results reported enable applications of this polarization effect, including manipulation and control of nuclear fields.Comment: 5 pages, 4 figures, 7 pages supplementary materia