One-dimensional Patterns Research Articles

Antioxidant analysis of protein from fresh and dry leaf of Orthosiphon aristatus (Blume) Miq.

Orthosiphon aristatus (Blume) Miq. is a folklore plant consumed as brewed tea for various health benefits. The white variety of the plants leaf and stem are predominantly sold in the market in dried form, blooming as a natural herbal product. To date, no proteomics and antioxidant studies are available on the fresh and dried leaf protein extract of O. aristatus since most studies take an interest in the crude extracts of plants. Thereupon, this study focuses on the One-dimensional (1D) electrophoretic pattern of the fresh and dry leaf determined via sodium dodecyl-sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Additionally, antioxidant proteins are currently being focused on for their link to controlling disease through their potential to destroy free radicals that are present in excess. Hence, an antioxidant assay was conducted for the fresh and dry leaf protein extract using 2,2-Diphenyl-1-picrylhydrazyl (DPPH) free radical assay and ferric reducing antioxidant power (FRAP) assay. The electrophoretic pattern obtained resulted in approximately 16 and 10 bands for the fresh and dry leaves respectively. As for the antioxidant activity, the dry leaf had higher radical scavenging activity and higher reducing power compared to the fresh leaf. The findings obtained provides insight in to the protein content and antioxidant activity found in the protein extract of fresh and dry leaves of O. aristatus. Hence, further detailed study of the protein extracts could further unveil their therapeutic potential.

Combined failure identification of intermediate bearing in aeroengine based on wavelet transform, second-order difference, and 1D-LBP

Intermediate bearing is one of key parts in double-rotor aeroengine, whose running state usually can only be monitored by casing signals. As the fault characteristic information detected from casing is weak and complex, it is generally difficult to be dug correctly. One-dimensional local binary pattern (1D-LBP) can depict failure information from the perspective of local feature extraction. Currently, the study on the application of 1D-LBP in fault identification is mostly based on original signals; due to the influence of component signals irrelevant to fault and noise, the fault information in original signals is weak and complex; besides, 1D-LBP is rather sensitive to noise, which is extremely possible to cause insufficient extraction of local textural features and the difficulty to identify a fault. To solve this problem and make it possible to precisely identify the fault of intermediate bearing of real aeroengine, the paper has proposed the combined method of wavelet transform (WT), second-order difference with 1D-LBP. WT is highly uncertain to determine the decomposition layer number. To solve the difficulty, correlation coefficient was introduced. Meanwhile, casing vibration signal was subjected to WT. Furthermore, because vibration signal often went with impact components in a bearing failure and second-order difference of signals was sensitive to impact feature, component signals obtained by WT were subjected to second-order difference operation. Additionally, taking advantage of 1D-LBP, second-order differences of signals were locally binarized with average value as criterion. Finally, 1D-LBP signals were re-transformed to decimal 1D local texture signals (1D-LTS). These 1D-LTS can embody local feature information of signals. According to the spectrum of 1D-LTS, combined failure type of intermediate bearing was identified. Through the comparison with WT and classical 1D-LBP method, and failure analysis after disassembly of aeroengine, the effectiveness and engineering applicability of proposed method have been verified.

Energy-Efficient Sleep Apnea Detection Using a Hyperdimensional Computing Framework Based on Wearable Bracelet Photoplethysmography.

Sleep apnea syndrome (SAS) is a common sleep disorder, which has been shown to be an important contributor to major neurocognitive and cardiovascular sequelae. Considering current diagnostic strategies are limited with bulky medical devices and high examination expenses, a large number of cases go undiagnosed. To enable large-scale screening for SAS, wearable photoplethysmography (PPG) technologies have been used as an early detection tool. However, existing algorithms are energy-intensive and require large amounts of memory resources, which are believed to be the major drawbacks for further promotion of wearable devices for SAS detection. In this paper, an energy-efficient method of SAS detection based on hyperdimensional computing (HDC) is proposed. Inspired by the phenomenon of chunking in cognitive psychology as a memory mechanism for improving working memory efficiency, we proposed a one-dimensional block local binary pattern (1D-BlockLBP) encoding scheme combined with HDC to preserve dominant dynamical and temporal characteristics of pulse rate signals from wearable PPG devices. Our method achieved 70.17 % accuracy in sleep apnea segment detection, which is comparable with traditional machine learning methods. Additionally, our method achieves up to 67× lower memory footprint, 68× latency reduction, and 93× energy saving on the ARM Cortex-M4 processor. The simplicity of hypervector operations in HDC and the novel 1D-BlockLBP encoding effectively preserve pulse rate signal characteristics with high computational efficiency. This work provides a scalable solution for long-term home-based monitoring of sleep apnea, enhancing the feasibility of consistent patient care.

PatternJ: an ImageJ toolset for the automated and quantitative analysis of regular spatial patterns found in sarcomeres, axons, somites, and more.

Regular spatial patterns are ubiquitous forms of organization in nature. In animals, regular patterns can be found from the cellular scale to the tissue scale, and from early stages of development to adulthood. To understand the formation of these patterns, how they assemble and mature, and how they are affected by perturbations, a precise quantitative description of the patterns is essential. However, accessible tools that offer in-depth analysis without the need for computational skills are lacking for biologists. Here, we present PatternJ, a novel toolset to analyze regular one-dimensional patterns precisely and automatically. This toolset, to be used with the popular imaging processing program ImageJ/Fiji, facilitates the extraction of key geometric features within and between pattern repeats in static images and time-lapse series. We validate PatternJ with simulated data and test it on images of sarcomeres from insect muscles and contracting cardiomyocytes, actin rings in neurons, and somites from zebrafish embryos obtained using confocal fluorescence microscopy, STORM, electron microscopy, and brightfield imaging. We show that the toolset delivers subpixel feature extraction reliably even with images of low signal-to-noise ratio. PatternJ's straightforward use and functionalities make it valuable for various scientific fields requiring quantitative one-dimensional pattern analysis, including the sarcomere biology of muscles or the patterning of mammalian axons, speeding up discoveries with the bonus of high reproducibility.

Optical feedback-induced spatiotemporal patterns with power law spectra in a liquid crystal light valve.

Pattern formation can be induced by coupling electromagnetic fields to a polarizable and lossy medium. Increasing energy injection patterns can exhibit aperiodic behaviors. We investigate the self-organization of unidimensional aperiodic patterns. Based on a liquid crystal light valve (LCLV) with optical feedback, we observed aperiodic one-dimensional patterns with power laws in the temporal and spatial spectrum density of the light intensity, and their pseudo envelope and phase characteristic of spatiotemporal complexity. Theoretically, a local model describes the system close to nascent bistability and spatial instability. Numerical simulations of this model show chaotic spatiotemporal patterns whose temporal and spatial spectra have exponents similar to those observed experimentally.

A feasibility study on femtosecond laser texturing of sprayed nanocellulose coatings

Nanocelluloses are emerging as natural materials with favourable properties for coating industry and can be applied by state-of-the-art spraying technology. While additional functionalities are commonly introduced through chemical modification, the surface microstructuring of nanocellulose coatings with high throughput methods remains unexplored. Here, a femtosecond laser is used for texturing spray-coated coatings made of cellulose nanofibrils (CNF) or cellulose nanocrystals (CNC). For coating thickness of 1.5 to 8 μm, processing limits were determined with maximum ablation energy linearly increasing with coating thickness and minimum ablation energy decreasing or increasing depending on the apparent coating density. Within applicable processing window of pulse rate and power setting, the operational ranges were determined for creating one-dimensional and two-dimensional surface patterns, requiring a higher laser energy for CNC compared to CNF coatings and yielding thinnest possible resolved patterns of 17 μm as determined by the laser spot diameter. The laser ablation under low energy corresponds to an increase in surface roughness and intensifies surface hydrophilicity, while the line patterns are able to pin water droplets with rising water contact angles up to 90°. Present feasibility study opens future possibilities for managing surface properties of nanocellulose coatings in applications where tuning of surface hydrophilicity is required.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Abstract Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms. However, it is still unclear how such information is affected by the physically dissipative diffusion process. Here we study one-dimensional patterning systems with analytical derivation and numerical simulations. We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns. Specifically, there exists an optimal diffusion constant that maximizes the positional information. Moreover, we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Comprehensive optical and thermal investigation of optimal near-infrared absorption enhancement of nano-patterned aluminum

Compelling electromagnetic (EM) properties, such as tight EM-confinement and fabrication-compatible architectures, propel the importance of metal-based nanophotonics in small-footprint devices, such as highly efficient optical absorbers. Here, we focus on boosting the absorption of optically thick bulk Aluminum (Al), the most abundant metal, solely by corrugating its surface periodically. Application-oriented, we utilize the simplest one-dimensional (1D) rectangular-grating pattern that can be remotely engraved on a large scale, e.g., using femtosecond pulsed lasers. We devise four designs for various utilizations optimized for perfect absorption around the application-abundant 1.06μm wavelength under transverse electric (TE), transverse magnetic (TM), and unpolarized (denoted TEM) irradiations. Lacking attractive plasmonic confinement properties, the s-polarization is considered electromagnetically “degenerate” to the p-polarization case, making it rarely explored in the literature of 1D-grating architectures. Nevertheless, we reveal that perfect s-polarized absorption is also attainable in such designs without adding extra layers. The designs’ performance, properties, limitations, and the propelling electromagnetic physics are theoretically and numerically discussed in-depth. A large-area sample of the TEM-optimized design was fabricated, facilitating uniquely extensive optical and radiative heating experimental investigation with realistic near-to-normal Gaussian-beam incidence. The absorption enhancement derived from wideband and single-frequency optical and radiative heating measurements agree well, also with the numerical simulations. Despite fabrication-derived thickness deviation, the design experimentally showed a 9.6-(TE), 6-(TM), and 7.8-(TEM) fold absorption enhancement over bulk Al. Considering the one-dimensional-patterning simplicity and its large-area fabrication compatibility, it is noteworthy and pioneering, particularly for the challenging s-polarization case. We also study a polarization-sensitive diffused reflection scattering pattern, evidently postulated to result from resonated surface roughness, highlighting the importance of radiative heating measurements. The elaborated original findings and methods are highly applicable alongside the prevalent material and spectrum.

Signature of low-dimensional quasi-F centers in zirconium-rich electrides.

Electrides are a class of materials consisting of non-nuclear excess electrons as quasi-F centers or Farbe centers within a positively charged lattice framework, and have significant applications in the fields of electrochemistry, spintronics, and electrode materials. Using first-principles quantum mechanical calculations, we have demonstrated exotic electronic structures of zirconium-rich electrides, Zr2X (X = O, Se, and Te), and obtained the quantitative values of charge transfer (oxidation states), and projected density of states associated with the localized quasi F-centers. The localized interstitial anionic electrons exhibit significant charge transfer values of approximately -1.88, -2.01, and -1.79 per atom in Zr2O, Zr2Se, and Zr2Te, respectively, and contribute actively in the electronic band structures and density of states at the Fermi level. From the 2D contour plot of the electron localization function (ELF), it has been predicted that the spatial distribution of the quasi-F centers stabilizes in the form of a one-dimensional pattern, with localized ELF sites interconnected with delocalized electron channels. Further, low work-function values of Zr2X, ranging from 2.7-3.4 eV, confirm the electride properties of these binary compounds, promising applications in electro-catalytic oxidations and anode materials in batteries. These unique electronic properties of anionic electrons free from nuclear binding in Zr2X have not been reported yet in the literature.

Magnetohydrodynamics and viscosity variation in couple stress squeeze film lubrication between rough flat and curved circular plates

A simplified mathematical model has been developed for understanding combined effects of surface roughness, viscosity variation and couple stresses on the squeeze film behaviour of a flat and a curved circular plate in the presence of transverse magnetic field. The Stokes (1966) couple stress fluid model is included to account for the couple stresses arising due to the presence of microstructure additives in the lubricant. In the context of Christensen’s (1969) stochastic theory for the lubrication of rough surfaces, two types of one-dimensional roughness patterns (radial and azimuthal) are considered. The governing modified stochastic Reynolds type equations are derived for these roughness patterns. Expressions for the mean squeeze film characteristics are obtained. Numerical computations of the results show that the azimuthal roughness pattern on the curved circular and flat plate results in more pressure buildup whereas performance of the squeeze film suffers due to the radial roughness pattern. Further the Lorentz force characterized by the Hartmann number, couple stress parameter and viscosity variation parameter improve the performance of the squeeze film lubrication as compared to the classical case (Non-magnetic, Newtonian case and non-viscous case).

An Investigation of the Link Between Artificial Intelligence and Academic Performance

The Use of AI in Pedagogy for Improving Student Learning In the 21st century, artificial intelligence and machine learning have become resourceful, magical, and innovative pedagogical tools in the global academic environment. These two teaching and learning technologies seem to be innovative wonders that change the course of education significantly from traditional learning to a technological learning approach. Hence, they contribute to the evolution of one-dimensional learning patterns to multi-dimensional concepts, i.e., from the physical classroom to digital education. The significance of these smart tools is the salient transformations brought about by the elevation of education pedagogy by enhancing effective teaching and learning and making it more seamless.

Dual-feature and multi-scale fusion using U2-net deep learning model for ECG biometric recognition

Aiming at the challenges that the traditional photoplethysmography (PPG) biometrics is not robust and precision of recognition, this paper proposes a dual-feature and multi-scale fusion using U2-net deep learning model (DMFUDM). First, to obtain complementary information of different features, we extract the local and global features of one-dimensional multi-resolution local binary patterns (1DMRLBP) and multi-scale differential feature (MSDF). Then, to extract robust discriminant feature information from the 1DMRLBP and MSDF features, a novel two-branch U2-net framework is constructed. In addition, a multi-scale extraction module is designed to capture the transition information. It consists of multiple convolution layers with different receptive fields for capturing multi-scale transition information. At last, a two-level attention module is used to adaptively capture valuable information for ECG biometrics. DMFUDM can obtain the average subject recognition rates of 99.76%, 98.31%, 98.97% and 98.87% on four databases, respectively, and experiment results show that it performs competitively with state-of-the-art methods on all four databases.

Overcoming Periodic Stripe Noise in Infrared Linear Array Images: The Fourier-Assisted Correlative Denoising Method.

Infrared linear array detectors frequently experience vertical, low-frequency, and periodic stripe noise during imaging, stemming from electro-mechanical interference. Unlike conventional periodic disturbances, this interference showcases long periodicities and is uniquely columnar in orientation. Its presence, especially within the low-frequency domain, renders conventional filtering techniques ineffective and, at times, detrimental to image quality. Addressing this challenge, we introduce Fourier-Assisted Correlative Denoising (FACD), a correlation-centric denoising approach tailored for such unique interference patterns. This mechanism begins with the capture of a pure background image, inclusive of periodic noise, during the non-uniform correction phase of the infrared detector. Leveraging the noise's frequency domain attributes, we extract a one-dimensional single-cycle noise signal. The infrared image is subsequently segmented into parts, and using the detected noise periodicity, the one-dimensional signals for each segment are computed. By leveraging the correlation between these signals and the benchmark one-dimensional noise pattern, we ascertain the noise profile within each segment. This profile is then employed for spatial domain denoising across the entire image frame. Empirical assessments confirm that the FACD outperforms contemporary denoising techniques by augmenting the peak signal-to-noise ratio by approximately 2.5 dB, underscoring its superior robustness. Furthermore, in light of its specificity to this noise model, FACD rapidly denoises high-resolution real infrared linear array scans, thus meeting the stringent real-time and resolution imperatives of advanced infrared linear array scanning apparatuses.

Ultra-broadband mid-infrared absorber based on hyperbolic α-MoO3

Owing to their broad operational bandwidth, broadband absorbers are extensively used in various applications, such as solar cells, microbolometers, and light modulators. To enhance energy harvesting, it is essential to achieve insensitivity to wide incident angles and polarization-independent absorption. α-MoO3 is a natural polar van der Waals crystal that hosts phonon polaritons in the mid-infrared spectral region. These polaritons can manipulate the infrared light at the nanoscale and break the diffraction limit, offering a great opportunity for the design of broadband absorbers. In this study, we propose a strategy based on an array of crossed the permittivity of α-MoO3 in [100] and [001] crystallographic axes to expand its broadband absorption. Triangular one-dimensional grating pattern is initially considered, which shows an ultra-broadband and wide-angle insensitive absorption within the range of 10.23–18.07 μm. Subsequently, square pyramidal two-dimensional arrays are investigated, which not only show ultra-broadband absorption and wide-angle insensitivity, but also exhibit polarization independence within the range of 10.46–18.32 μm. This remarkable broadband absorption is elucidated by the effective medium theory and the local power dissipation density. These results demonstrate an effective strategy for constructing ultra-broadband absorbers based on α-MoO3 for applications in solar thermal and photovoltaic systems.

Samarium addition-mediated simultaneous achievement of excellent resistance drift and superior thermal stability in phase-change compound antimony-selenium thin film

The Sm-doped Sb7Se3 thin films were systematically investigated, including phase change behavior, phase structure, microstructure, and electrical properties. The in-situ resistance test displays that the addition of Sm element leads to a significant increase in the crystallization temperature, decadal data retention and crystallization activation energy, implying better thermal stability. Crystallization kinetic analysis indicates a one-dimensional growth crystallization pattern, exhibiting an ultra-fast crystallization speed. The change in optical bandgap reflects that the exotic Sm atoms enhance the bandgap energy, which facilitates the reduction of the threshold current. Resistance drift test highlights the suppression of structural relaxation by Sm atoms, which would greatly improve the reliability of the information readout. X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectra, and transmission electron microscopy demonstrate that the addition of Sm retards the crystallization process and refines the grain size. Energy dispersive spectroscopy shows that the Sm dopant has incorporated into Sb7Se3 thin film. The phase change memory cell based on Sm-doped Sb7Se3 film exhibits faster running speed (100 ns) and lower power consumption (3.0 × 10−11 J) than the conventional Ge2Sb2Te5 material. All the results prove that incorporating appropriate amounts of Sm into Sb7Se3 material is an ideal technique for optimizing resistance drift and thermal stability of Sb7Se3 thin films.

Early performance and bonding mechanism of metakaolin (MK)- ground granulated blast furnace slag (GGBS) based geopolymer road repair mortar

ABSTRACT Metakaolin (MK) and ground granulated blast furnace slag (GGBS) based geopolymers have been utilised as materials for concrete road repair. However, their early-stage performance and bonding mechanism as rapid repairs are not well understood. This research investigated the workability, early strength development and bonding mechanism of geopolymer repair mortars with different GGBS contents. The reaction kinetics and reaction products of the geopolymer repairs were analyzed through reaction heat evolution and FTIR, and the microstructure of the bonding interface was examined using BSE-EDS. Results showed that geopolymer repair mortars with higher GGBS content exhibited shorter setting times, higher flowability, and higher compressive strength. Geopolymers demonstrated a one-dimensional rod-shaped nucleation pattern during hardening, and the crystallization rate decreased with GGBS addition. GGBS increased the formation of C-A-S-H gels and accelerated the geopolymerization process. However, excessive GGBS reduced bond strength due to the introduction of microcracks. A GGBS content of 60 wt.% is recommended in this investigation. The study also revealed that the cement substrate could absorb alkali activator, leading to the formation of high-Ca gels and strengthening the interface.

Rigid-flex stamped indium tin oxide film for convertible self-alignment

The alignment layer process, which is a key element for liquid crystal (LC) displays, was investigated for efficiency improvement and for suggesting a new mode. To produce alignment films that can be used in both twisted-nematic (TN) and vertical alignment (VA) configurations, InO solution is doped with SnO. Then, the pattern was transferred by attaching a one-dimensional soft-imprint mold, and pattern and orientation analyses were performed in accordance with the SnO ratio. The horizontal orientation performance improved as the SnO ratio increased, and the best orientation performance was observed for a film doped with 70% SnO. Further, the thermal stability improved and anchoring energy increased, which was measured to be very close to that of the rubbed polyimide film. The low transmittance of InO was overcome by doping with SnO, which has high transmittance. In the film doped with 80% SnO, the LC molecules were aligned in a vertical direction and were suitable for VA mode operation. By simple adjustment of the doping ratio, differences are observed with respect to the existing films in that the performance of the alignment layer is improved and the pretilt angles of the LC molecules can be changed. These convertible characteristics are expected to play a revolutionary role in the development of new LC driving modes.

Explainable automated anuran sound classification using improved one-dimensional local binary pattern and Tunable Q Wavelet Transform techniques

Explainable automated anuran sound classification using improved one-dimensional local binary pattern and Tunable Q Wavelet Transform techniques

Compound faults identification of rolling bearing based on one-dimensional mixed binary pattern

To address the difficulty in extracting the characteristics of combined failure of rolling bearings, a novel fault identification method, one-dimensional mixed binary pattern (1D-MBP), is proposed. Firstly, regarding that variance can better highlight the partial weak failure information of sequence than median, the binarization of vibration signals based on one-dimensional local binary pattern (1D-LBP) is carried out with variance as criterion. Meanwhile, binarization sequence is converted to decimal sequence as the local conversion signal (LCS). Secondly, considering that failure information of rolling bearings is reflected in partial and global texture, the paper proposed the method of gaining global weighted mean value by weighting partial mean value with partial energy. Binarize vibration signals based on one-dimensional global binary pattern (1D-GBP) with obtained global weighted mean value as criterion and convert the obtained binarized sequence into decimal as the global conversion signal (GCS). Thirdly, signals are reconstructed by obtained LCS and GCS to get 1D-MBP signal. Finally, combined failure types of bearing can be identified from 1D-MBP signals based on TEAGER energy spectrum (TES). The result indicates that the 1D-MBP not only can effectively control noise components in vibration signal but also can precisely identify the combined failure types of rolling bearings.

Slanted Structure of Blue Phase II Self-Aligned on One-Dimensional Patterned Surfaces.

Orientation analysis of liquid crystal (LC) devices is important for understanding and controlling light propagation behavior in these devices. Blue phases (BPs)─unique LC phases that self-organize into three-dimensional helical structures─are candidate materials for LC-based reflective diffractors. We realized BPII deflectors with large diffraction angles using one-dimensional surface alignment patterns. We analyzed the BPII lattice arrangement in the deflector based on Bragg reflections and demonstrated that the lattice structure was slanted with respect to the substrate, which was confirmed using transmission electron microscopy. In addition, we calculated the similarity between the alignment pattern on the substrate surface and the director arrangement of BPII near the interface, confirming that the structure observed experimentally matched the most probable calculated structure. Thus, this study contributes to the optical design of BPII deflectors and provides information on the orientation mechanism in high-order self-organizing soft matter structures.