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We present the first-year data set of high-cadence, long-duration observations of the bright millisecond pulsar J0437−4715 obtained in the Argentine Institute of Radioastronomy (IAR). Using two single-dish 30 m radio antennas, we gather more than 700 hr of good-quality data with timing precision better than 1 μs. We characterize the white and red timing noise in IAR's observations, we quantify the effects of scintillation, and we perform single-pulsar searches of continuous gravitational waves, setting constraints in the nHz–μHz frequency range. We demonstrate IAR's potential for performing pulsar monitoring in the 1.4 GHz radio band for long periods of time with a daily cadence. In particular, we conclude that the ongoing observational campaign of the millisecond pulsar J0437−4715 can contribute to increase the sensitivity of the existing pulsar-timing arrays. [ABSTRACT FROM AUTHOR]

We perform three-dimensional general-relativistic magnetohydrodynamic simulations with weak interactions of binary neutron-star (BNS) mergers resulting in a long-lived remnant neutron star, with properties typical of galactic BNS and consistent with those inferred for the first observed BNS merger GW170817. We demonstrate self-consistently that within ≲30  ms postmerger magnetized (σ∼5-10) incipient jets emerge with asymptotic Lorentz factor Γ∼5-10, which successfully break out from the merger debris within ≲20  ms. A fast (v≲0.6c), magnetized (σ∼0.1) wind surrounds the jet core and generates a UV/blue kilonova precursor on timescales of hours, similar to the precursor signal due to free neutron decay in fast dynamical ejecta. Postmerger ejecta are quickly dominated by magnetohydrodynamically driven outflows from an accretion disk. We demonstrate that, within only 50 ms postmerger, ≳2×10^{-2}M_{⊙} of lanthanide-free, quasispherical ejecta with velocities ∼0.1-0.2c is launched, yielding a kilonova signal consistent with GW170817 on timescales of ≲5  d.

This paper focuses on ultra-reliable low-latency Vehicle-to-Anything (V2X) communications able to meet the extreme requirements of high Levels of Automation (LoA) use cases. We introduce a system architecture and processing algorithms for the alignment of highly collimated V2X beams based either on millimeter-Wave (mmW) or Free-Space Optics (FSO). Beam-based V2X communications mainly suffer from blockage and pointing misalignment issues. This work focuses on the latter case, which is addressed by proposing a V2X architecture that enables a sensor-aided beam-tracking strategy to counteract the detrimental effect of vibrations and tilting dynamics. A parallel low-rate, low-latency, and reliable control link, in fact, is used to exchange data on vehicle kinematics (i.e., position and orientation) that assists the beam-pointing along the line-of-sight between V2X transceivers (i.e., the dominant multipath component for mmW, or the direct link for FSO). This link can be based on sub-6 GHz V2X communication, as in 5G frequency range 1 (FR1). Performance assessments are carried out to validate the robustness of the proposed methodology in coping with misalignment induced by vehicle dynamics. Numerical results show that highly directional mmW and/or FSO communications are promising candidates for massive data-rate vehicular communications even in high mobility scenarios.

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes' activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in β-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance β-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 β-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a β-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.