SAF-A promotes origin licensing and replication fork progression to ensure robust DNA replication

The organisation of chromatin is closely intertwined with biological activities of chromosome domains, including transcription and DNA replication status. Scaffold attachment factor A (SAF-A), also known as Heteronuclear Ribonucleoprotein Protein U (HNRNPU), contributes to the formation of open chromatin structure. Here we demonstrate that SAF-A promotes the normal progression of DNA replication, and enables resumption of replication after inhibition. We report that cells depleted for SAF-A show reduced origin licensing in G1 phase, and consequently reduced origin activation frequency in S phase. Replication forks also progress less consistently in cells depleted for SAF-A, contributing to reduced DNA synthesis rate. Single-cell replication timing analysis revealed two distinct effects of SAF-A depletion: first, the boundaries between early- and late-replicating domains become more blurred; and second, SAF-A depletion causes replication timing changes that tend to bring regions of discordant domain compartmentalisation and replication timing into concordance. Associated with these defects, SAF-A-depleted cells show elevated -H2AX formation and tend to enter quiescence. Overall we find that SAF-A protein promotes robust DNA replication to ensure continuing cell proliferation.

Mode changing in J1909−3744: the most precisely timed pulsar

We present baseband radio observations of the millisecond pulsar J1909−3744, the most precisely timed pulsar, using the MeerKAT telescope as part of the MeerTime pulsar timing array campaign. During a particularly bright scintillation event the pulsar showed strong evidence of pulse mode changing, among the first millisecond pulsars and the shortest duty cycle millisecond pulsar to do so. Two modes appear to be present, with the weak (lower signal-to-noise ratio) mode arriving 9.26 ±3.94 μs earlier than the strong counterpart. Further, we present a new value of the jitter noise for this pulsar of 8.20 ± 0.14 ns in one hour, finding it to be consistent with previous measurements taken with the MeerKAT (9 ± 3 ns) and Parkes (8.6 ± 0.8 ns) telescopes, but inconsistent with the previously most precise measurement taken with the Green Bank telescope (14 ± 0.5 ns). Timing analysis on the individual modes is carried out for this pulsar, and we find an approximate $10\%$ improvement in the timing precision is achievable through timing the strong mode only as opposed to the full sample of pulses. By forming a model of the average pulse from templates of the two modes, we time them simultaneously and demonstrate that this timing improvement can also be achieved in regular timing observations. We discuss the impact an improvement of this degree on this pulsar would have on searches for the stochastic gravitational wave background, as well as the impact of a similar improvement on all MeerTime PTA pulsars.

The Peculiar Behavior of Burst Oscillations in the Accreting Millisecond X-ray Pulsar XTE J1814–338

Accreting millisecond X-ray pulsars (AMXPs) show burst oscillations during thermonuclear explosions of the accreted plasma which are markedly different from those observed in non-pulsating low mass X-ray binaries. The AMXP XTE J1814–338 is known for having burst oscillations that are phase locked (constant phase difference) and coincident with the accretion powered pulsations during all its thermonuclear bursts but the last one. In this work we use a coherent timing analysis to investigate this phenomenon in more detail and with higher time resolution than was done in the past. We confirm that the burst oscillation phases are, on average, phase locked to the accretion powered pulsations. However, they also display moderate (≲ 0.1 cycles) drifts during each individual burst, showing a repeating pattern that is consistently observed according to the thermonuclear burst phase (rise, peak, tail). Despite the existence of these drifting patterns, the burst oscillation phases somehow are able to average out at almost the exact position of the accretion powered pulsations. We provide a kinematic description of the phenomenon and review the existing models in the literature. The phenomenon remains without a clear explanation, but we can place important constraints on the thermonuclear burst mechanism. In particular, the observations imply that the ignition point of the thermonuclear burst occurs close to the foot of the accretion column. We speculate that the burning fluid expands in a backward tilted accretion column trapped by the magnetic field, while at the same time the burning flame covers the surface.

Worst-case Execution Time Calculation for Query-based Monitors by Witness Generation

Runtime monitoring plays a key role in the assurance of modern intelligent cyber-physical systems, which are frequently data-intensive and safety-critical. While graph queries can serve as an expressive yet formally precise specification language to capture the safety properties of interest, there are no timeliness guarantees for such auto-generated runtime monitoring programs, which prevents their use in a real-time setting. While worst-case execution time (WCET) bounds derived by existing static WCET estimation techniques are safe, they may not be tight as they are unable to exploit domain-specific (semantic) information about the input models. This article presents a semantic-aware WCET analysis method for data-driven monitoring programs derived from graph queries. The method incorporates results obtained from low-level timing analysis into the objective function of a modern graph solver. This allows the systematic generation of input graph models up to a specified size (referred to as witness models ) for which the monitor is expected to take the most time to complete. Hence, the estimated execution time of the monitors on these graphs can be considered as safe and tight WCET. Additionally, we perform a set of experiments with query-based programs running on a real-time platform over a set of generated models to investigate the relationship between execution times and their estimates, and we compare WCET estimates produced by our approach with results from two well-known timing analyzers, aiT and OTAWA.

Nauyaca: a New Tool to Determine Planetary Masses and Orbital Elements through Transit Timing Analysis

The transit timing variations method is currently the most successful method to determine dynamical masses and orbital elements for Earth-sized transiting planets. Precise mass determination is fundamental to restrict planetary densities and thus infer planetary compositions. In this work, we present Nauyaca, a Python package dedicated to finding planetary masses and orbital elements through the fitting of observed midtransit times from an N-body approach. The fitting strategy consists of performing a sequence of minimization algorithms (optimizers) that are used to identify high probability regions in the parameter space. These results from optimizers are used for initialization of a Markov chain Monte Carlo method, using an adaptive Parallel-Tempering algorithm. A set of runs are performed in order to obtain posterior distributions of planetary masses and orbital elements. In order to test the tool, we created a mock catalog of synthetic planetary systems with different numbers of planets where all of them transit. We calculate their midtransit times to give them as an input to Nauyaca, testing statistically its efficiency in recovering the planetary parameters from the catalog. For the recovered planets, we find typical dispersions around the real values of ∼1–14 M ⊕ for masses, between 10–110 s for periods, and between ∼0.01–0.03 for eccentricities. We also investigate the effects of the signal-to-noise ratio and number of transits on the correct determination of the planetary parameters. Finally, we suggest choices of the parameters that govern the tool for the usage with real planets, according to the complexity of the problem and computational facilities.

Power Estimation and Validation of Embedded Multiplier Based on ANN and Regression Technique

Nowadays, high-end Field-Programmable Gate Arrays (FPGAs) are capable of implementing relatively high-performance systems in the field of Digital Signal Processing (DSP). Due to the abundant application of multipliers, their implementation efficiency and performance have become a critical issue in designing the DSP systems. On the other hand, FPGAs consume a large amount of power due to their complex circuitry. So, the power estimation of FPGA implementations at an early design stage has become a critical design metric. Various models are available in the literature based on Look-up Tables (LUTs), but not much literature is available on speed-optimized multiplier design using DSP slices only. In this paper, an embedded multiplier (12.0 IP core) has been analyzed and customized for different Input/Output (I/O) configurations to estimate the power using Vivado Design Suite (2014.4) targeted to the Zynq-family FPGA device (Zynq evolution and development kit). The embedded multiplier IP has been optimized for performance using two different approaches, i.e., Mults (DSP)-based and LUTs-based. Post-synthesis attributes have been used for formulating the power estimation models based on Artificial Neural Network (ANN) and curve fitting and regression technique. The power values estimated from the proposed models have been authenticated with reference to those assessed from the commercial tool. Based on the results obtained, ANN-based model provides average errors of 0.73% and 0.88% for the LUTs and DSP-based designs, respectively. Whereas, the model based on curve fitting and regression technique provides average errors of 3.61% and 1.59% for the LUTs and DSP-based designs, respectively. The timing analysis has been done to get the design performance and time complexity of the proposed models. Area analysis of the design has also been performed in order to report the resource utilization.