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Large-scale solar ejections are well understood, but the extent to which small-scale solar features directly influence the solar wind remains an open question, primarily due to the challenges of tracing these small-scale ejections and their impact. Here, we measure the fine-scale motions of network bright points along a coronal hole boundary in high-resolution Hαimages from the 1.6 m Goode Solar Telescope at Big Bear Solar Observatory to quantify the agitation of open flux tubes into generating Alfvénic pulses. We combine the motion, magnetic flux, and activity duration of the flux tubes to estimate the energy content carried by individual Alfvénic pulses, which is ∼10²⁵erg, adequately higher than the energies ∼10²³erg estimated for the magnetic switchbacks observed by the Parker Solar Probe (PSP). This implies the possibility that the surface-generated Alfvénic pulses could reach the solar wind with sufficient energy to generate switchbacks, even though some of then are expected to be reflected back in the stratified solar atmosphere. Alfvénic pulses further reproduce for the first time other properties of switchbacks, including the filling factor above ∼8% at granular and supergranular scales, which correspond best to the lower end of the mesoscale structure. This quantitative result for solar energy output in the form of Alfvénic pulses through magnetic funnels provides a crucial clue to the ongoing debate about the dynamic cycle of energy exchange between the Sun and the mesoscale solar wind that has been raised, but has not been adequately addressed, by PSP near-Sun observations. 

The present study evaluates Mill scale which is a steel industry waste and bismuth trioxide simultaneously as a potential radiation shielding material in geopolymer composite. An innovative and first of its kind lead-free design has been developed for making radiation shielding materials using mill scale and bismuth trioxide as shielding aggregates and industrial wastes such as fly ash and blast furnace slag as precursors for the geopolymer composite. The mill scale and bismuth trioxide based composite material are characterized for their radiation shielding characteristics based on shielding parameters commonly used in radiation shielding like linear attenuation coefficient (μ), half value thickness (HVT) and Mean Free Path (MVP) for 0.662 MeV energy. The determined shielding parameters are compared with traditional shielding materials like concrete with heavy aggregates. X-Ray diffraction studies have confirmed the presence of Bismuth ferrite as the major shielding phase responsible for radiation shielding. The mechanical properties of the prepared composites are determined for their strength in direct compression. Depending upon the radiation shielding parameters like linear attenuation coefficient and half value thickness an optimum dosage of mill scale and bismuth trioxide as a shielding composite to provide adequate shielding for X-Ray diagnostic and medical facilities against X-ray photons of low intensity has been recommended. The highest linear attenuation coefficient values of fly ash and slag based geopolymer composites had been observed to be 0.208 and 0.225, respectively. 

At the core of Network Functions Virtualization lie Network Functions (NFs) that run co-resident on the same server, contend over its hardware resources and, thus, might suffer from reduced performance relative to running alone on the same hardware. Therefore, to efficiently manage resources and meet performance SLAs, NFV orchestrators need mechanisms to predict contention-induced performance degradation. In this work, we find that prior performance prediction frameworks suffer from poor accuracy on modern architectures and NFs because they treat memory as a monolithic whole. In addition, we show that, in practice, there exist multiple components of the memory subsystem that can separately induce contention. By precisely characterizing (1) the pressure each NF applies on the server's shared hardware resources (contentiousness) and (2) how susceptible each NF is to performance drop due to competing contentiousness (sensitivity), we develop SLOMO, a multivariable performance prediction framework for Network Functions. We show that relative to prior work SLOMO reduces prediction error by 2-5x and enables 6-14% more efficient cluster utilization. SLOMO's codebase can be found at https://github.com/cmu-snap/SLOMO. 

Abstract Complete theoretical understanding of the most complex superconductors requires a detailed knowledge of the symmetry of the superconducting energy-gap$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$, for all momentakon the Fermi surface of every bandα. While there are a variety of techniques for determining$$|{\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha |$$ $\mid {\Delta }_k^{\alpha }\mid$, no general method existed to measure the signed values of$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$. Recently, however, a technique based on phase-resolved visualization of superconducting quasiparticle interference (QPI) patterns, centered on a single non-magnetic impurity atom, was introduced. In principle, energy-resolved and phase-resolved Fourier analysis of these images identifies wavevectors connecting allk-space regions where$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$has the same or opposite sign. But use of a single isolated impurity atom, from whose precise location the spatial phase of the scattering interference pattern must be measured, is technically difficult. Here we introduce a generalization of this approach for use with multiple impurity atoms, and demonstrate its validity by comparing the$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$it generates to the$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$determined from single-atom scattering in FeSe where s_±energy-gap symmetry is established. Finally, to exemplify utility, we use the multi-atom technique on LiFeAs and find scattering interference between the hole-like and electron-like pockets as predicted for$${\mathrm{{\Delta}}}_{\mathbf{k}}^\alpha$$ ${\Delta }_k^{\alpha }$of opposite sign.