Binary Structure Research Articles

Construction of Medusa-Like Adhesive Carbon Nanotube Array Induced by Deformation of Alumina Sheets.

To change the binary structure of nanotube and nanotube array in vertically aligned carbon nanotube arrays, this work deposits regularly arranged amorphous alumina sheets on the classical array growth catalyst (10nm-thick alumina and 2nm-thick iron) and obtains an array similar to the Medusa head. Subsequent experiments revealed that these alumina sheets show both unstable and stable qualities during growth: unstable in that they thermally deform and change their newly discovered characteristics of blocking carbon source diffusion, which regulates the nanotube growth order in specific areas; stable in that they withstand the deformation caused by heat and sequential growth of nanotubes, serving as a substrate and buffer layer for Medusa's hair, i.e., nanotube bundles on the array surface. Their combination splits this binary structure into a tertiary architecture consisting of nanotubes, nanotube bundles, and the array spanning nano-, micro-, and milli-meter. Benefiting from this structure, this array exhibits a unique near-isotropic adhesion characteristic compared to existing reports and outperforms classical and patterned arrays with the same classical catalyst and growth conditions.

Techniques and methods for obtaining access to data protected by linux-based encryption – A reference guide for practitioners

This research presents an overview of the typical disc and folder-level encryption that a digital forensic investigator may encounter when investigating a Linux operating system. Based on prior first-hand experience and significant follow-up testing and research, this work examines the operation of such encryption from the user's perspective, discusses how the encryption operates “under the hood”; and explores methods and techniques that can be used to access and retrieve data from such encrypted devices, both during at-scene/live forensic investigation and also post-scene. Worked examples are presented, to aid the reader's understanding. This research also presents considerations, approaches and steps that can be used by an investigator, in order to maximise the potential for data acquisition, and most crucially discusses lessons learnt to facilitate getting the best evidence in such cases. A breakdown of the binary structure of the key files associated with fscrypt is also presented, for reference. Current limitations and gaps in knowledge are also discussed.

Assembly Requirements for the Construction of Large-Scale Binary Protein Structures.

The precise assembly of multiple biomacromolecules into well-defined structures and materials is of great importance for various biomedical and nanobiotechnological applications. In this study, we investigate the assembly requirements for two-component materials using charged protein nanocages as building blocks. To achieve this, we designed several variants of ferritin nanocages to determine the surface characteristics necessary for the formation of large-scale binary three-dimensional (3D) assemblies. These nanocage variants were employed in protein crystallization experiments and macromolecular crystallography analyses, complemented by computational methods. Through the screening of nanocage variant combinations at various ionic strengths, we identified three essential features for successful assembly: (1) the presence of a favored crystal contact region, (2) the presence of a charged patch not involved in crystal contacts, and (3) sufficient distinctiveness between the nanocages. Surprisingly, the absence of noncrystal contact mediating patches had a detrimental effect on the assemblies, highlighting their unexpected importance. Intriguingly, we observed the formation of not only binary structures but also both negatively and positively charged unitary structures under previously exclusively binary conditions. Overall, our findings will inform future design strategies by providing some design rules, showcasing the utility of supercharging symmetric building blocks in facilitating the assembly of biomacromolecules into large-scale binary 3D assemblies.

Highly compressible and stretchable ceramic aerogels with nanofiber-nanosheet binary synergistic structure for thermal insulation in extreme environments

Ceramic aerogels are ideal candidates for thermal insulation in extreme environments because of their high porosity, low thermal conductivity, and chemical and thermal inertness. However, the intrinsic rigidity and brittleness of ceramic aerogels hinder their practical application. In this study, we designed a composite mullite aerogel with a nanofiber-nanosheet binary synergistic structure to obtain superior thermal insulation properties and robust mechanical performance. Composite aerogels were manufactured by combining electrospinning and freeze-drying. They exhibited superior temperature-invariant compressibility, flexibility, stretchability, fatigue tolerance, and thermal insulation performance. Our study will enable the innovative design of mechanically reliable ceramics for numerous extreme applications ranging from battery protection to space exploration.

Rethinking the relationships between gel like structure and sludge dewaterability based on a binary gel like structure model: Implications for the online sensing of dewaterability

The digital transformation of sludge treatment processes requires online sensing of dewaterability. This topic has been attempted for many years based on macroscopic shear rheology. However, the relationship between rheological behavior and dewaterability remains noncommittal, and the reason is unclear. Herein, a binary gel-like structure model was proposed including the interactions network at the supra-flocs level and the gel-like structure at the flocs level. Multiple advanced techniques including optical tweezers were employed to precisely understand the binary gel-like structure and to classify the correlation mechanism between this gel-like structure, rheological behavior, and dewaterability. The analysis of sludge from eight wastewater treatment plants showed the binary gel-like structures at both supra-flocs and flocs levels have significant relationships with sludge dewaterability (p < 0.05). Further deconstruction of the sludge viscoelastic behavior illustrated that the gel-like structure at the supra-flocs level dominates the rheological behavior of sludge. Moreover, the direct description of the binary gel-like structure in four typical sludge treatment processes highlighted the importance of the flocs level's structure in determining the dewaterability. Overall, this study revealed that shear rheology may prefer to stress the interactions network at the supra-flocs level but mask the flocs level's structure, although the latter is important. This observation may provide a general guideline for the design of robust sensors for dewaterability.

Ventilating noise barrier with slow wave propagation metamaterial

There has been rapid development of acoustic metamaterials over the past decades, which provide more flexible and effective alternatives to conventional acoustic applications in the field of noise insulation. Recent approaches resolve the conflict between noise insulation and ventilation with partially open meta-structures. Such a binary design eliminates the monopolar and dipolar modes, leading to a total reflection boundary. It holds huge potential in practical scenarios. More simple structures and a broader operating bandwidth are highly desirable to enhance its applicability. This work adopts a binary structure to tune the surface response: open areas with air and slow wave propagation layers with helical-structured metamaterial. These two phases alternate along the radial direction, forming a concentrically layered ventilating insulator. The numerically optimized metamaterial performs efficiently in a wide frequency band and has been validated through experiments.

On the multi-objective perspective of discrete topology optimization in fluid-structure interaction problems

Fluid-structure interaction is a challenging topic that addresses fluid and solid physics, as well as the stress coupling between them. Traditional topology optimization methods are performed with coupling load interpolation schemes in order to have some information on fluid flow sensitivity analysis and improve compliance minimization into design-dependent problems. In this paper, we propose a strategy to design fluid-structure systems by combining solid and fluid objectives without the need for the coupling load interpolation scheme. Therefore, we investigate topology optimization applied to fluid-structure interaction problems via a multi-objective formulation. We combine structural compliance with some fluid flow objective functions (energy dissipation, downforce, and drag) subject to a volume constraint. We assume linear elasticity for the solid and the steady incompressible Navier-Stokes equations for the fluid. The optimization problem is solved by using sequential integer linear programming via the TOBS (Topology Optimization of Binary Structures) method with a geometry trimming (GT) technique. It is a gradient-based method that produces explicit (discrete) boundaries that are convenient for coupled physics problems. Numerical results are presented for two and three-dimensional problems considering low to moderate Reynolds numbers. We demonstrate that the proposed multi-objective approach yields physically meaningful designs with improved performance, highlighting that the incorporation of coupling load interpolation into fluid-structure interaction optimization is redundant.

Stochastic modeling of turbulent mixing based on a hierarchical swapping of fluid parcels

AbstractTurbulent mixing is an omnipresent phenomenon that constantly affects our everyday life and plays an important role in a variety of industrial applications. The simulation of turbulent mixing poses great challenges, since the full resolution of all relevant length and time scales is associated with an immense computational effort. This limitation can be overcome by only resolving the large‐scale effects and completely model the sub‐grid scales. The development of an accurate sub‐grid mixing model is therefore a key challenge to capture all interactions in the sub‐grid scales. At this place, the hierarchical parcel‐swapping (HiPS) model formulated by A.R. Kerstein [J. Stat. Phys. 153, 142–161 (2013)] represents a computationally efficient and scale‐resolving turbulent mixing model. HiPS mimics the effects of turbulence on time‐evolving, diffusive scalar fields. In HiPS, the diffusive scalar fields or a state space is interpreted as a binary tree structure, which is an alternative approach compared to the most common mixing models. Every level of the tree represents a specific length and time scale, which is based on turbulence inertial range scaling. The state variables are only located at the base of the tree and are treated as fluid parcels. The effects of turbulent advection are represented by stochastic swaps of sub‐trees at rates determined by turbulent time scales associated with the sub‐trees. The mixing only takes places between adjacent fluid parcels and at rates consistent with the prevailing diffusion time scales. In this work, the HiPS model formulation for the simulation of passive scalar mixing is detailed first. Preliminary results for the mean square displacement, passive scalar probability density function (PDF) and scalar dissipation rate are given and reveal the strengths of the HiPS model considering the reduced order and computational efficiency. These model investigations are an important step of further HiPS advancements. The integrated auxiliary binary tree structure allows HiPS to satisfy a large number of criteria for a good mixing model. From this point of view, HiPS is an attractive candidate for modeling the mixing in transported PDF methods.

Photochromic properties of novel composites on the base of biopolymers and plasma‐modified Mo4O11 and W18O49 nanostructures

AbstractNovel photochromic composites based on biopolymers (polyvinyl alcohol, starch) and Mo4O11 and W18O49 as the fillers were obtained and characterized. To improve the photochromic properties, molybdenum and tungsten oxide sols were treated by an underwater diaphragm discharge to obtain binary structures of the MoOx/WOx and WOx/MoOx (2 &lt; x &lt; 3) types. The formation of such oxides was confirmed by TEM, EDX, XRD analysis, and Raman spectroscopy data. Plasma treatment is increased the color intensity and reversibility. The modified sols were incorporated into polymer matrices. Spectral studies have shown that the color of photo‐colored composites depends on the chemical structure of the polymer matrix. Mechanical tests have shown the possibility of obtaining hardened or plastic composites depending on the concentration and nature of the filler.Highlights Photochromic polymer composites with W18O49 and Mo4O11 as fillers were obtained. Diaphragm discharge used as a tool for sol modification. WOx/MoOx and MoOx/WOx structures have improved photochromic properties. Color of irradiated polymer composites depends on chemical structure of polymer. Mechanical properties are determined by the polymer filler concentration.

Broadband optical vortex beam generation using flat-surface nanostructured gradient index vortex phase masks

We developed a new kind of compact flat-surface nanostructured gradient index vortex phase mask, for the effective generation of optical vortex beams in broadband infrared wavelength range. A low-cost nanotechnological material method was employed for this work. The binary structure component consists of 17,557 nano-sized rods made of two lead–bismuth–gallium silicate glasses which were developed in-house. Those small rods are spatially arranged in such a way that, according to effective medium theory, the refractive index of this internal structure is constant in the radial direction and linearly changes following azimuthal angle. Numerical results demonstrated that a nanostructured vortex phase mask with a thickness of 19 μm can convert Gaussian beams into fundamental optical vortices over 290 nm wavelength bandwidth from 1275 to 1565 nm. This has been confirmed in experiments using three diode laser sources operating at 1310, 1550, and 1565 nm. The generation of vortex beams is verified through their uniform doughnut-like intensity distributions, clear astigmatic transformation patterns, and spiral as well as fork-like interferograms. This new flat-surface component can be directly mounted to an optical fiber tip for simplifying vortex generator systems as well as easier manipulation of the generated OVB in three-dimensional space.

Oblique random forests with binary and ternary decision structures and non-parallel hyperplanes classifiers

Oblique random forests with binary and ternary decision structures and non-parallel hyperplanes classifiers

Gendered stereotype content for people with a nonbinary gender identity

Background Gender stereotypes about women and men have a complementary structure, where women and men are seen as high/low in feminine characteristics and low/high in masculine characteristics. These stereotypes are related to representation within social roles, where beliefs about social role occupation influences which characteristics are associated with women or men. It is not known how people with gender identities that do not fit a binary structure are stereotyped. The current study provides a first step towards addressing this gap. Methods Swedish participants (N = 152) reported descriptive stereotype content (positive/negative feminine/masculine personality characteristics) and estimations of representation within domestic and occupational social roles for people with a nonbinary gender identity for the past, present, and future in a between-groups design. Stereotype content for the past included a higher degree of feminine compared to masculine characteristics, but ratings for the present and future showed no differentiation between femininity and masculinity. Results People with a nonbinary gender identity were believed to more frequently occupy feminine compared to masculine social roles for all time points; this was especially pronounced for occupational social roles. The theorised connection between social role occupation and stereotype content did not emerge: degree of positive masculinity and femininity correlated positively with representation in masculine domestic and occupational roles respectively, but positive femininity was negatively correlated with representation in feminine occupational roles. Conclusions These results indicate that stereotypes about people with a nonbinary gender identity do not show the same complementary pattern or reliance on social roles as gender stereotypes about women and men, but that there is a feminine bias in perceptions of social role occupation for people with a nonbinary gender identity.

Bacterial cellulose based TiO2-CdS nanocomposite gel with enhanced photocatalytic activity for adsorptive degradation of cationic dye

Dye released by industrial is one of the main known pollutants in wastewater, which is harmfully affected to the human health. Adsorptive method by absorbents and photocatalytic degradation technique are advanced technologies to remove dyes from wastewater. However, the single technique mentioned above has imperfections limiting its application. Herein, in order to integrate the two techniques and take both advantages, bacterial cellulose (BC) based titanium dioxide (TiO2)‑cadmium sulfide (CdS) nanocomposite gel was prepared by microwave-assisted solvothermal synthesis. The BC@TiO2-CdS nanocomposite gel was characterized by SEM, EDS, XRD, XPS, Raman spectral and TG, its photocatalytic mechanism was proved by PL. The results showed the TiO2-CdS nanophotocatalyst exhibited binary hierarchical structure and followed the Z-scheme type photocatalytic system. The Z-scheme heterojunction is advantageous for photo-generated charge separation and migration. The photocatalytic performance of BC@TiO2-CdS nanocomposite gel was evaluated by MB degradation under visible light irradiation. Due to synergistic effect of BC matrix and TiO2-CdS, the as-prepared BC@TiO2-CdS nanocomposite gel possesses enhanced photocatalytic activity with 94.47 % removal of methylene blue (MB) after 180 min visible light irradiation. Therefore, this work provides a facile route to fabricate bio-mass based efficient nanophotocatalytic material for pretreating the water pollution.

Fault diagnosis of a computer interlocking system for railway signal control

The signal control of the railway transportation system is crucial for operational safety. This paper briefly introduces the computer interlocking system for railway signal control, describes the tree-structured neural network used for fault diagnosis of the interlocking system, and introduces the particle swarm optimization (PSO) algorithm for improvement. Finally, a simulation experiment was conducted on a railway station to compare the traditional back-propagation neural network (BPNN), the support vector machine, the traditional tree-structured neural network, and the improved tree-structured neural network for fault diagnosis. It was found that the topological structure of the device distribution in the railway station could be transformed into a tree structure, and with the introduction of hidden nodes, it could become a binary tree structure where each leaf node represents a device; the improved tree-structured neural network had the highest recognition performance for both two-class tasks (determining system failure or not) and multi-class tasks (identifying fault type).

Binary structure constrained gravity inversion based on seismic first arrival travel time data

Gravity exploration method is one of the important methods for deep mineral resource exploration, but gravity data inversion has limited resolution ability in the vertical direction. In order to improve the vertical resolution of gravity data inversion, we propose a binary structure constrained gravity inversion method based on seismic first arrival travel time data. This method effectively reconstructs a density model with high vertical resolution by transferring the structural information of a high-resolution velocity model reconstructed by seismic data inversion to gravity data inversion through the binary structure constrained technique. This strategy eliminates the need to integrate both gravity and seismic methods into a single inversion framework, avoiding both the difference in convergence speeds between the two methods, as well as getting rid of the complexity associated with calculating structural coupling terms. Theoretical simulations show that the fuzzy c-means cluster analysis technique can accurately extract the target region of the velocity model reconstructed by seismic data inversion. Under the constraint of seismic structural information, the resolution of reconstructed density model is much higher than that of separate gravity data inversion, which proves that high resolution seismic information can improve the vertical resolution of gravity data inversion. Compared with the traditional cross-gradient joint inversion, the binary structure constrained gravity inversion method can further improve the resolution of the density model, especially in the reconstruction of the anomaly interface, which verifies that the method has certain effectiveness.

Ramanujan-gram: an autonomous weak period fault extraction method under strong noise

Under the influence of strong noise, period fault features of rolling bearing are not obvious, which increases the difficulty of accurately extracting period fault features. An autonomous weak period fault extraction method under strong noise named Ramanujan-gram is proposed in this paper. The greatest advantage of Ramanujan-gram is that it uses the Ramanujan feature extraction technique to reconstruct the components in each frequency band, which can overcome the weakness of the weak noise robustness of the filter methods used by the traditional kurtogram methods and improve the accuracy of period fault feature extraction. Meanwhile, the adaptive frequency band segmentation method based on the order statistical filter is used for adaptive frequency band segmentation, which overcomes the defect that the binary tree structure of fixed frequency band segmentation may destroy the optimal demodulated frequency band. Considering that kurtosis index is difficult to accurately evaluate period fault information in components, Ramanujan-gram adopts adaptive square envelope spectrum weighted kurtosis index to improve the evaluation accuracy of period fault information. The test signals of rolling bearing verify that Ramanujan-gram has strong noise robustness and is an effective method for weak period fault extraction under strong noise.

Lightweight, strong, and thermally insulating polybenzoxazine aerogel thermal protection composites for antioxidant ablation long to 1800 s

The lightweight ablation materials that have been successfully applied in thermal protection systems (TPS) are the focus of attention owing to the urgent demand for aerospace vehicles to have efficient thermal insulation materials with lightweight, long-term antioxidant, and micro-ablation. However, improving the antioxidant ablation properties in a long-term aerobic atmosphere is still a significant challenge. Herein, a novel strategy to fabricate needle quartz fiber (NQF) reinforced SiO2 aerogel interpenetrating polybenzoxazine (PBO) aerogel thermal protection composites (NQF/SiO2–PBOs) with a binary network structure is proposed. The as-prepared NQF/SiO2–PBOs perfectly inherited their porous nanostructure and captivating properties, including lightweight (0.53 g/cm3), high mechanical strengths, and low thermal conductivity of 0.048 W/(m·K) at 25 °C and 0.079 W/(m·K) at 1100 °C. Moreover, the NQF/SiO2–PBOs exhibited outstanding high-temperature thermal insulation and long-time antioxidant ablation with low linear and mass ablation rates. The cold surface temperature peaked at approximately 307.2 °C within 1800 s when the hot surface temperature exceeded 1100 °C. The ablation/thermal insulation mechanism was also discussed through the analysis of the microstructure, chemical structure, and crystal structure. This research provides a meaningful reference for the development and exploitation of new advanced lightweight, long-term antioxidant, and micro-ablative thermal protective materials.

Dictionary of composites: new empirical data

The article presents the results of the study of composites that have appeared in the Russian language in recent decades. The relevance of the research is due to the active process of replenishing in the class of composites, as well as a high interest in the study of their structure and semantics. We distinguish the binary structure of compound words (sometimes multicomponent) of varying degrees of solidity and offer four types of their classification. We also identify groups of composites by their thematic attribution.The material under study represents complex lexical units not previously recorded in the dictionaries and provides new empirical data.The material for the study was obtained from various sources: oral speech, fiction, advertising and journalistic texts, Internet resources - the article notes that the range of these words is genetically and structurally heterogeneous: today, the leading trend compared to the early period is the formation of a group of words in the Russian language according to a fixed analytical model: an attribute in the preposition plus a noun.Foreign-language components easily form new words and have high activity, enter into free syntagmatic relations. Such a feature – the presence of analytical neoplasms – is a consequence of the general trend of the modern Russian language – the growth of analyticism.The article notes that many complex words form combinations with a common component, thereby creating word-formation models, as well as single classes and word-formation fields.The functional status, the degree of assimilation of components, the ability to enter into syntagmatic relations, as well as the frequency and other characteristics of the words considered here are not similar. The article notes that the process of borrowing, which has moved to various functional areas, as well as the formation of new complex words according to the models considered in the article, contribute to the development and expansion of the lexical composition in the modern Russian language.

Controllable synthesis of Bi2O3-MoO3 binary system metal composite oxides and structure–activity relationships for aerobic oxidative desulfurization

Controllable synthesis of Bi2O3-MoO3 binary system metal composite oxides and structure–activity relationships for aerobic oxidative desulfurization

MIA-Net: Multi-Modal Interactive Attention Network for Multi-Modal Affective Analysis

When a multi-modal affective analysis model generalizes from a bimodal task to a trimodal or multi-modal task, it is usually transformed into a hierarchical fusion model based on every two pairwise modalities, similar to a binary tree structure. This easily leads to large growth in model parameters and computation as the number of modalities increases, which limits the model's generalization. Moreover, many multi-modal fusion methods ignore that different modalities contribute differently to affective analysis. To tackle these challenges, this paper proposes a general multi-modal fusion model that supports trimodal or multi-modal affective analysis tasks, called Multi-modal Interactive Attention Network (MIA-Net). Instead of treating different modalities equally, MIA-Net takes the modality that contributes the most to emotion as the main modality and the others as auxiliary modalities. MIA-Net introduces multi-modal interactive attention modules to adaptively select the important information of each auxiliary modality one by one to improve the main-modal representation. Moreover, MIA-Net enables quick generalization to trimodal or multi-modal tasks through stacking multiple MIA modules, which maintains efficient training and only requires linear computation and stable parameter counts. Experimental results of the transfer, generalization, and efficiency experiments on the widely-used datasets demonstrate the effectiveness and generalization of the proposed method.