Magnetic and Velocity Fluctuations in the Near-Sun Region from 0.1−0.3 au Observed by Parker Solar Probe

The fluctuations observed in the slow solar wind at 1 au by the WIND spacecraft are shown by recent studies to consist of mainly magnetic-field directional turning and magnetic-velocity alignment structure (MVAS). How these structures are created has been a question because the nature of the fluctuations in the near-Sun region remains unknown. Here, we present an analysis of the measurements in the slow solar wind from 0.1−0.3 au by Parker Solar Probe during its first six orbits. We present the distributions in the C vb ′ – σ r plane of both the occurrence and average amplitudes of the fluctuations, including the magnetic field, the velocity, and the Elsässer variables, where C vb ′ is the correlation coefficient between the magnetic and velocity fluctuations multiplied by the opposite sign of the radial component of the mean magnetic field and σ r is the normalized residual energy. We find that the dominant composition is the outward-propagating Alfvénic fluctuations. We find Alfvénic fluctuations with C vb ′ > 0.95 , in which the amplitudes of z + reach 60 km s−1 and those of z − are close to the observational uncertainty. We also find a region with high C vb ′ and moderate minus σ r in which the fluctuations are considered MVAS being magnetic dominated with the amplitude of magnetic fluctuations reaching 60 km s−1. We provide empirical relations between the velocity fluctuation amplitude and C vb ′ . The comparison between these results and those observed at 1 au may provide some clues as to the nature and evolution of the fluctuations.

Electronic and Optical Properties of Atomic-Scale Heterostructure Based on MXene and MN (M = Al, Ga): A DFT Investigation

After the discovery of graphene, a lot of research has been conducted on two-dimensional (2D) materials. In order to increase the performance of 2D materials and expand their applications, two different layered materials are usually combined by van der Waals (vdW) interactions to form a heterostructure. In this work, based on first-principles calculation, some charming properties of the heterostructure constructed by Hf2CO2, AlN and GaN are addressed. The results show that Hf2CO2/AlN and Hf2CO2/GaN vdW heterostructures can keep their original band structure shape and have strong thermal stability at 300 K. In addition, the Hf2CO2/MN heterostructure has I-type band alignment structure, which can be used as a promising light-emitting device material. The charge transfer between the Hf2CO2 and AlN (or GaN) monolayers is 0.1513 (or 0.0414) |e|. The potential of Hf2CO2/AlN and Hf2CO2/GaN vdW heterostructures decreases by 6.445 eV and 3.752 eV, respectively, across the interface. Furthermore, both Hf2CO2/AlN and Hf2CO2/GaN heterostructures have remarkable optical absorption capacity, which further shows the application prospect of the Hf2CO2/MN heterostructure. The study of this work provides theoretical guidance for the design of heterostructures for use as photocatalytic and photovoltaic devices.

Translation Mechanism of Neural Machine Algorithm for Online English Resources

At the level of English resource vocabulary, due to the lack of vocabulary alignment structure, the translation of neural machine translation has the problem of unfaithfulness. This paper proposes a framework that integrates vocabulary alignment structure for neural machine translation at the vocabulary level. Under the proposed framework, the neural machine translation decoder receives external vocabulary alignment information during each step of the decoding process to further alleviate the problem of missing vocabulary alignment structure. Specifically, this article uses the word alignment structure of statistical machine translation as the external vocabulary alignment information and introduces it into the decoding step of neural machine translation. The model is mainly based on neural machine translation, and the statistical machine translation vocabulary alignment structure is integrated on the basis of neural networks and continuous expression of words. In the model decoding stage, the statistical machine translation system provides appropriate vocabulary alignment information based on the decoding information of the neural machine translation and recommends vocabulary based on the vocabulary alignment information to guide the neural machine translation decoder to more accurately estimate its vocabulary in the target language. From the aspects of data processing methods and machine translation technology, experiments are carried out to compare the data processing methods based on language model and sentence similarity and the effectiveness of machine translation models based on fusion principles. Comparative experiment results show that the data processing method based on language model and sentence similarity effectively guarantees data quality and indirectly improves the algorithm performance of machine translation model; the translation effect of neural machine translation model integrated with statistical machine translation vocabulary alignment structure is compared with other models.

Bioinformatics Analysis of B. Abortus Strain 2308 Protein and Its Drug Docking

Brucellosis is among the fast-spreading disease on Earth causing casualties in livestock as well as in humans. It’s an alarming situation to kick off the study of Brucellosis causing agent. Brucellosis is an infective sickness caused by Brucella abortus. Here, we have carried out the Insilco analysis of Brucella abortus strain 2308. This strain is mainly responsible for the disease. Here, we have tried to study the B. abortus strain 2308 by the means of bioinformatics methodology. We have run several Insilco tools to predict its structure and function. Moreover, we have carried out the methodology of protein homology modelling on this strain. Furthermore, we have also carried out several protein chain analyses, protein-protein interface, structure alignment, structure prediction and active site prediction. To make our study more productive we have also performed drug docking. These results will add on a little info in the emerging bioinformatics data regarding Brucella abortus.

Taxonomy of organizational alignment: implications for data-driven sustainable performance of firms and supply chains

PurposeThe purpose of this paper is to identify, characterize, classify and conceptualize different perspectives on strategic alignment still in use, propose a taxonomy and definitions that allow understanding the various coexisting concepts, as well as investigate the implications of strategic alignment for data-driven sustainable performance of firms and supply chains.Design/methodology/approachBibliographic review was used.FindingsThe taxonomy proposes two classes of strategic alignment: (1) Align – more rigorous types of alignment: structure alignment, strategic congruence and strategy alignment; (2) Fit – less rigorous types of alignment: contingency strategic adjustment, strategic coalignment and strategic consistency. Companies are accumulating large amounts of data, which relevance varies widely. The strategic alignment can define criteria to select only the data that have strategic value, which restricts the amount of data to be analyzed. Each of the six types of strategic alignment is appropriate for a given situation in companies and/or supply chains.Research limitations/implicationsThe limitations stem from the exclusive use of the taxonomy of strategic alignment, without considering the most diverse perspectives of strategy.Practical implicationsDecision makers will be able to identify more objectively which classes of data should be explored in each situation.Social implicationsTheoretical implications – The taxonomy proposal and the definition of each of the strategic alignment perspectives solve generalized misunderstandings resulting from the lack of a clear delimitation between the perspectives and the conceptual divergence between authors, who use them as equivalent or synonymous.Originality/valueFrom 1961 to 2019, no paper was found proposing taxonomy, typology, systematization, ranking, distribution or classification of strategic alignment. The strategic alignment can define criteria to select, within the large amount of data accumulated by the company, only those that have strategic value, what restricts the quantity of data to be analyzed and facilitates the decision of the leaders.

Dynamic Self-Assembly of Polyelectrolyte Composite Nanomaterial Film

The aim of this study is not only to investigate the feasibility of using PAH (polyallylamine hydrochloride) and PSS (poly styrene-4-sulfonic acid sodium salt) to prepare a film via a layer by layer self-assembly process entrained with silver nanoparticles, but also to show that the silver nanoparticles crystalline structure can be defined and deposited on the surface of the substrate in the desired alignment structure and manner, which is of great help to research on the LBL method in the cellulose field. The effect of outermost layer variation, assembly layers, and composition of multilayers on the formation of the LBL structure on a nanofibrillated cellulose (NFC)/polyvinyl alcohol (PVA) substrate was investigated. The deposition of PAH and PSS was monitored by Fourier-transform infrared spectroscopy (FT-IR). The morphology of the LBL film layers was observed by scanning electron microscope (SEM) and atomic force microscope (AFM). Furthermore, thermal degradation properties were investigated by thermogravimetric analysis (TGA), and physical properties of multilayer films were tested by a universal mechanical tester. The results reveal that PAH and PSS can be readily deposited on a NFC/PVA substrate by using LBL methodology to prepare self-assembled polyelectrolyte multilayer films. The surface morphology of the LBL composite changed from negative to positive charged depending on the final LBL treatment. Also, according to SEM and AFM analysis, silver nanoparticles were well dispersed in the (PAH/PSS) film, which significantly improved the thermal stability of the composite films.

The Design and Analysis of a Containment Vacuum and Pressure Vessel System

A nested confinement (inner) and containment (outer) vessel system is under development to conduct small shock-physics experiments in a high-speed proton imaging facility at Los Alamos National Laboratory. The dual vessel system is necessary to serve as a qualified confinement system and containment buffer boundary between a high explosives experiment and the environment. The paper describes the preliminary engineering design and analyses that have been performed on the outer containment pressure vessel, following ASME BPVC Sect. VIII Div. 1, for both pressure and vacuum conditions. Other engineering attributes which will be presented include an internal support structure for a nested inner vessel, an external integrated support and alignment structure for the complete vessel system, and the vacuum and gas handling equipment.

High capacity VO2(B) nanostrips synthesized by microwave-hydrothermal method

VO2(B) nanostrips were synthesized by microwave-hydrothermal method. The XRD patterns show that VO2(B) nanostrips are pure metastable monoclinic phase. VO2(B) nanostrips, in length of 1.5–2[Formula: see text][Formula: see text]m, width of 200–400[Formula: see text]nm, and thickness of 10–20[Formula: see text]nm, present exposed (001) facets and parallel alignment structure. The VO2(B) nanostrips are composed of nanosheets with 2–5[Formula: see text]nm thickness. A very high initial discharge capacity of 318.3[Formula: see text]mAh[Formula: see text]g[Formula: see text] is obtained and the capacity of 100th cycle is 248.5[Formula: see text]mAh[Formula: see text]g[Formula: see text] (about 78.0% retention) at 50[Formula: see text]mA[Formula: see text]g[Formula: see text]. The capacity fades at about 4.08% per cycle for the first 10 cycles. After 10 cycles, the fading slows down to 0.32% per cycle. The rate performance shows the first discharge capacities of VO2(B) nanostrips are 249.6, 212.0, 181.8, 161.7, and 145.2[Formula: see text]mAh[Formula: see text]g[Formula: see text] at 0.1, 0.2, 0.4, 0.8, and 1.6[Formula: see text]A[Formula: see text]g[Formula: see text], respectively, with around 100% coulombic efficiency. Glycerol and microwave-hydrothermal method contribute to the shaping and thickness of VO2(B) nanostrips with the parallel alignment nanostructure, which directly improves the electrical properties of this material.