Simple Structure Research Articles

Photonic reservoir computing for parallel task processing based on a feedback-free spin-polarized VCSEL

Time delayed reservoir computing (RC) is a novel artificial neural network that is easy to implement in hardware due to its extremely simple structure. Because of its time-division multiplexed information processing, laser-based photonic time-delayed RCs usually realize parallel processing with polarization/wavelength multiplexing. However, the performance of two different tasks is difficult to regulate separately and simultaneously in the time delayed RC system, especially for the chip-scale configuration. Here, we propose a feedback-free RC system based on a spin-polarized vertical-cavity surface-emitting semiconductor laser (VCSEL), which simplifies the whole system structure and can process time series prediction and waveform recognition tasks in parallel, with employing the input and output coding to provide the effect from past states. By separately setting the number of past states introduced by the coding for the two tasks, the performance of the two tasks can be adjusted respectively. Furthermore, by appropriately tuning the pump polarization ellipticity which is the unique feature for the spin-polarized VCSEL, the computational ability of the proposed RC can be focused on one of the two parallel tasks. Therefore, the proposed RC system is capable of dealing with different tasks with high performance, and also expected to provide a viable solution for integrated neuromorphic computing systems due to its compact, feedback-free structure.

Truncated Differential-Neural Key Recovery Attacks on Round-Reduced HIGHT

Recently, differential-neural cryptanalysis, which integrates deep learning with differential cryptanalysis, has emerged as a powerful and practical cryptanalysis method. It has been particularly applied to lightweight block ciphers, which are characterized by simple structures and operations, and relatively small block and key sizes. In resource-constrained environments, such as Internet of Things (IoT), it is essential to verify the resistance of existing lightweight block ciphers against differential-neural cryptanalysis to ensure security. In differential-neural cryptanalysis, a deep learning model, known as a neural distinguisher, is trained to differentiate a target cipher from others, facilitating key recovery through statistical analysis. For successful differential-neural cryptanalysis, it is crucial to develop a highly accurate neural distinguisher and to optimize the key recovery attack algorithm. In this paper, we introduce a novel neural distinguisher and key recovery attack against the 15-round reduced HIGHT cipher. Our proposed neural distinguisher is capable of distinguishing HIGHT ciphertext by analyzing only a portion of the ciphertext, which we refer to as a truncated neural distinguisher. Notably, our experiments demonstrate that the truncated neural distinguisher achieves performance comparable to existing distinguishers trained on entire ciphertext blocks, while enabling a more efficient key recovery attack through a divide-and-conquer strategy. Furthermore, we observe a significant improvement in key recovery efficiency compared to traditional cryptanalysis methods.

A TDLAS gas detection method based on digital signal modulation

This research presents a novel TDLAS gas concentration detection method based on digital modulation. The method inherits the advantage of a simple system structure from Direct Absorption Spectroscopy, as well as the excellent sensitivity of Wavelength Modulation Spectroscopy. A low-frequency sawtooth wave is employed to drive the laser, resulting in a digital direct absorption spectrum signal. By constructing a cosine modulation sequence in the time domain and performing linear interpolation on the direct absorption spectrum, it successfully converts to a wavelength-modulated absorption spectrum and simultaneously generates a digital reference signal at double the frequency. Ultimately, phase-locked amplification technology can be used to calculate the amplitude of the second harmonic. Since both the modulation and reference signals are generated digitally, they ensure a strict frequency-doubling relationship and phase correlation, which not only reduces the complexity of the hardware system but also effectively minimizes system errors. Because digital technology generates both the modulation and reference signals, it ensures that they have the same phase and a strict frequency-doubling relationship. Experimental results demonstrate that, when fitted by a cubic polynomial, the second harmonic amplitude and the gas concentration have a correlation coefficient (R2) as high as 0.99999 and a root mean square error as low as 0.0011. This proves the method's great accuracy and reliability in practical applications.

Developing Deformable Facets for Heliostats: An Increased Solar Concentration for Thermochemical Applications with Central Tower Receivers

In the present article a new design of a deformable facet and a heliostat with several deformable facets is presented. Previous work has been made around designing heliostats with concentrating facets in the facilities of the Plataforma Solar de Hermosillo. The evaluation and design process of facets and their evolution is also shown and reviewed. The facet design was initially conceived as a parabolic trough surface, however, through a modification of the facet, the surface was transformed into a concave surface. The resulting spot produced by the facet assumes nearly a spherical surface. A heliostat constructed with these facets shows similar optical performance with a previous one made with spherical facets; this spherical heliostat has a higher peak and mean flux. Nevertheless, the deformable facet heliostat presents a simpler construction and structure. A comparison between both heliostats will be presented.

A magneto-elastica reinforced elastomer makes soft robotic grippers

Soft robotics represents a burgeoning and interdisciplinary domain characterized by diverse research avenues encompassing actuation strategies, materials science, fabrication techniques, morphing mechanisms, and control methods. This work introduces a novel approach to soft actuators and robotic grippers by intricately exploring the magneto-elastica of spherical magnet chains. First, a kind of magneto-elastica reinforced elastomer is achieved by embedding millimetre-sized spherical neodymium-iron-boron (NdFeB) magnets into the polymer elastomer. By modulating the coupling effect of the magnetic and elastic contributions, the bending deformation of the magneto-elastica reinforced elastomer can be initialized. Subsequently, we analytically derive the coupled stiffness formula to integrate the discrete-scale magneto-elastica with the continuum elasticity using the transformed section method. For comparison, we further employ the multi-physics coupling simulation method to reveal the complex magnetics-mechanics interactions within the composite beam. As a proof of concept, we demonstrate two distinct configurations of rope-motor-driven robotic grippers respectively: three-finger soft robotic gripper and five-finger soft anthropomorphic hand. Pick-and-place experiments indicate that they have the good applicability to grasp objects with various sizes, surfaces and forms, including delicate, deformable, and irregularly shaped objects. In conclusion, the proposed method offers compelling advantages, including structural simplicity and modularity, facile manufacturability utilizing commonplace materials and 3D printing, in-situ active magneto-elastica-driven resilience and selectable actuation modalities via either magnetic or mechanical stimuli. We anticipate that the exploratory research can potentially manifest further contributions to soft actuators and soft robots.

Submerged and completely open solid–liquid triboelectric nanogenerator for water wave energy harvesting

AbstractTriboelectric nanogenerator (TENG) is an emerging wave energy harvesting technology with excellent potential. However, due to issues with sealing, anchoring, and difficult deployment over large areas, TENG still cannot achieve large‐scale wave energy capture. Here, a submerged and completely open solid–liquid TENG (SOSL‐TENG) is developed for ocean wave energy harvesting. The SOSL‐TENG is adapted to various water environments. Due to its simple structure, it is easy to deploy into various marine engineering facilities in service. Importantly, this not only solves the problem of difficult construction of TENG networks at present, but also effectively utilizes high‐quality wave energy resources. The working mechanism and output performance of the SOSL‐TENG are systematically investigated. With optimal triggering conditions, the transferred charge (Qtr) and short‐circuit current (Isc) of SOSL‐TENG are 2.58 μC and 85.9 μA, respectively. The wave tank experiment is taken for fully demonstrating the superiority of the SOSL‐TENG network in large‐scale collection and conversion of wave energy. Due to the excellent output performance, TENG can harvest wave energy to provide power for various commercial electronic devices such as LED beads, hygrothermograph, and warning lights. Importantly, the SOSL‐TENG networks realizes self‐powered for electrochemical systems, which provides a direction for energy cleanliness in industrial systems. This work provides a prospective strategy for large‐scale deployment of TENG applications, especially for harvesting wave energy in spray splash zones or at the surface of the water.image

A New Hybrid Improved Arithmetic Optimization Algorithm for Solving Global and Engineering Optimization Problems

The Arithmetic Optimization Algorithm (AOA) is a novel metaheuristic inspired by mathematical arithmetic operators. Due to its simple structure and flexible parameter adjustment, the AOA has been applied to solve various engineering problems. However, the AOA still faces challenges such as poor exploitation ability and a tendency to fall into local optima, especially in complex, high-dimensional problems. In this paper, we propose a Hybrid Improved Arithmetic Optimization Algorithm (HIAOA) to address the issues of susceptibility to local optima in AOAs. First, grey wolf optimization is incorporated into the AOAs, where the group hunting behavior of GWO allows multiple individuals to perform local searches at the same time, enabling the solution to be more finely tuned and avoiding over-concentration in a particular region, which can improve the exploitation capability of the AOA. Second, at the end of each AOA run, the follower mechanism and the Cauchy mutation operation of the Sparrow Search Algorithm are selected with the same probability and perturbed to enhance the ability of the AOA to escape from the local optimum. The overall performance of the improved algorithm is assessed by selecting 23 benchmark functions and using the Wilcoxon rank-sum test. The results of the HIAOA are compared with other intelligent optimization algorithms. Furthermore, the HIAOA can also solve three engineering design problems successfully, demonstrating its competitiveness. According to the experimental results, the HIAOA has better test results than the comparator.

Recent Patents on Piano Tuning System

Piano tuning plays a very important role in piano playing and music education. Regular tuning can prolong the service life of the piano, improve the sound saturation, and make the sound more concentrated and full. Automated mechanical equipment, controllers, sensors, and other equipment are used to automatically tune pianos to solve the problems of human error, overtone resonance interference, string breakage, etc., occurring in manual tuning. To solve the above problems, based on the synthesis of related patents and research results, the patents on automatic tuning system and methods for modulating piano are introduced in detail. An automatic tuning system can replace manual tuning, simplify the complex process of tuning, and consider the problem of overtone interference caused by the vibration of the strings to improve the accuracy of tuning; it can, at the same time, perform real-time monitoring of the string tension, protecting the strings from breaking due to tuning. The automatic tuning system has a simple structure and a high degree of automation; its method is highly accurate and it can replace professional tuning technicians, being highly innovative and widely practical.

A chaotic time series prediction model based on the improved dung beetle optimizer and echo state network

Echo state network (ESN) possesses advantages such as simple network structure, ease of training, and reliable prediction performance, making them widely applied in the field of time series prediction. Selecting the optimal reservoir parameters is a key issue in ESN research, as it determines the effectiveness of the network prediction, and it is crucial to design an efficient optimization method for parameter optimization. This paper introduces an improved version of the dung beetle optimizer (IDBO), which employs various strategies to enhance population initialization, algorithm optimization capability, and convergence speed. For theoretical function optimization problems, comparing IDBO with other commonly used optimization methods validated its effectiveness and feasibility. Subsequently, combining IDBO with ESN to construct a new model, IDBO-ESN, and conducting time series prediction experiments, the superior performance of this model is verified on two benchmark datasets and one real dataset.

The Neural Correlates of Spontaneous Beat Processing and Its Relationship with Music-Related Characteristics of the Individual.

In the presence of temporally organized stimuli, there is a tendency to entrain to the beat, even at the neurological level. Previous research has shown that when adults listen to rhythmic stimuli and are asked to imagine the beat, their neural responses are the same as when the beat is physically accented. The current study explores the neural processing of simple beat structures where the beat is physically accented or inferred from a previously presented physically accented beat structure in a passive listening context. We further explore the associations of these neural correlates with behavioral and self-reported measures of musicality. Fifty-seven participants completed a passive listening EEG paradigm, a behavioral rhythm discrimination task, and a self-reported musicality questionnaire. Our findings suggest that when the beat is physically accented, individuals demonstrate distinct neural responses to the beat in the beta (13-23 Hz) and gamma (24-50 Hz) frequency bands. We further find that the neural marker in the beta band is associated with individuals' self-reported musical perceptual abilities. Overall, this study provides insights into the neural correlates of spontaneous beat processing and its connections with musicality.

Data-Driven Dynamic Security Partition Assessment of Power Systems Based on Symmetric Electrical Distance Matrix and Chebyshev Distance

A rapid dynamic security assessment (DSA) is crucial for online preventive and restoration decision-making. The deep learning-based DSA models have high efficiency and accuracy. However, the complex model structure and high training cost make them hard to update quickly. This paper proposes a dynamic security partition assessment method, aiming to develop accurate and incrementally updated DSA models with simple structures. Firstly, the power grid is self-adaptively partitioned into several local regions based on the mean shift algorithm. The input of the mean shift algorithm is a symmetric electrical distance matrix, and the distance metric is the Chebyshev distance. Secondly, high-level features of operating conditions are extracted based on the stacked denoising autoencoder. The symmetric electrical distance matrix is modified to represent fault locations in local regions. Finally, DSA models are constructed for fault locations in each region based on the radial basis function neural network (RBFNN) and Chebyshev distance. An online incremental updating strategy is designed to enhance the model adaptability. With the simulation software PSS/E 33.4.0, the proposed dynamic security partition assessment method is verified in a simplified provincial system and a large-scale practical system in China. Test results demonstrate that the Chebyshev distance can improve the partition quality of the mean shift algorithm by approximately 50%. The RBFNN-based partition assessment model achieves an accuracy of 98.96%, which is higher than the unified assessment with complex models. The proposed incremental updating strategy achieves an accuracy of over 98% and shortens the updating time to 30 s, which can meet the efficiency of online application.

Centroid opposition-based backtracking search algorithm for global optimization and engineering problems

Evolutionary algorithms (EAs) have a lot of potential to handle nonlinear and non-convex objective functions. Particularly, the backtracking search algorithm (BSA) is a popular nature-based evolutionary optimization method that has attracted many researchers due to its simple structure and efficiency in problem-solving across diverse fields. However, like other optimization algorithms, BSA is also prone to reduced diversity, local optima, and inadequate intensification capabilities. To overcome the flaws and increase the performance of BSA, this research proposes a centroid opposition-based backtracking search algorithm (CoBSA) for global optimization and engineering design problems. In CoBSA, specific individuals simultaneously acquire current and historical population knowledge to preserve population variety and improve exploration capability. On the other hand, other individuals execute the position from the current population's centroid opposition to progress convergence speed and exploitation potential. In addition, an elite process based on logistic chaotic local search was developed to improve the superiority of the current individuals. The suggested CoBSA was validated on a set of benchmark functions and then employed in a set of application examples. According to extensive numerical results and assessments, CoBSA outperformed the other state-of-the-art methods in terms of accurateness, reliability, and execution capability.

Graphene‑vanadium dioxide ultra-wideband dual regulated absorber

In this paper, we propose a novel tunable THZ absorber consisting of a patterned graphene layer and a metal plate separated by a vanadium dioxide dielectric layer. The absorbent has a simple structure, is easy to make graphene patterns, and has a dual regulatory function. The ability to double regulate comes from the fact that the state of vanadium dioxide changes with the temperature between the insulating phase and the metal phase, resulting in a change in its conductivity. When vanadium dioxide is in the insulating phase, the total reflection characteristics of the absorber are >7 THz, and when vanadium dioxide is in the metallic phase, the absorber achieves near-perfect absorption in the ultra-wideband range of 3 THz to 12.4 THz (9.4 THz). Local surface plasmon resonance explains the perfect absorption. Compared with previous absorbers, our proposed absorbers are not only simple in structure, the graphene pattern is also easy to process, but also have double adjustment and perfect absorption in the ultra-wideband range, are not sensitive to polarized light, and have large tolerances for the Angle of incident. The further development and enrichment of terahertz metamaterials and metasurface devices will also have beneficial implications for terahertz wave applications in sensing, communications, and radar. Due to their significant application value in stealth, detection, and communication, metamaterial absorbers have become a research hotspot in the field of metamaterials.

Enhanced broadband perfect absorption in visible and near-infrared regimes

ABSTRACT It is still a challenge to achieve perfect ((near-unity)) absorption across a wide wavelength range with a three-layer structure. This paper presents a metamaterial absorber (MA) based on MXene that can achieve broadband and perfect absorption in the near-infrared and visible regions. The MA with a simple three-layer structure consists of a top Ti3C2T x layer, an intermediate dielectric layer and a bottom gold layer. It can achieve perfect absorption (the absorptivity over 99%) in the wavelength range of 730–900 nm. The electric field distribution reveals that the localized surface plasmon resonance occurring at the interface of Ti3C2T x and SiO2 leads to strong absorption over the wide wavelength range. Furthermore, the MA exhibits excellent angular stability. This work provides a method to construct MAs with broadband perfect absorption in the near-infrared and visible band.

Design of low-cost humidity sensor based on chipless RFID

It is of great significance to design a low-cost chipless radio frequency identification(RFID) sensor for environmental humidity monitoring. To this end, polyvinyl alcohol (PVA) film is used as a humidity sensitive material, and the overall size of the rectangular substrate is 18 mm × 18 mm ×0.5 mm. Through the humidity sensing principle and simulation analysis, the change of environmental humidity causes the change of the dielectric constant of the humidity sensitive material PVA, which in turn affects the resonant frequency offset of the entire sensor. The simulation results show that the relative humidity working range of the designed humidity sensor is 21.9% ∼ 52.5%, the corresponding sensor resonant frequency range is 2.76 ∼ 2.51GHz, the total offset reaches 250 MHz, and the average sensitivity at the maximum relative humidity is 23.08MHz/% . The designed humidity sensor has the advantages of miniaturization, simple structure and low cost, and can be used for humidity monitoring in various target environments. Keywords.low cost; chipless RFID humidity sensor; polyvinyl alcohol; humidity monitoring; humidity sensitive material.

Free-radical-induced grafting of rice starch with gallic acid and evaluation of the reaction products' ability to stabilize Pickering emulsions

Pickering emulsions can be stabilized with native rice starch (NRS), but their hydrophobicity is low. Gallic acid (GA) has a simple molecular structure and a rich variety of functional groups. Pickering emulsions can be made more stable by hydrophobically modifying the esterification reaction of NRS with GA to improve its dual wetting properties. In this study, the free radical-induced grafting method was used to prepare rice starch–GA graft copolymer (NRS-g-GA). The addition of GA could improve the crystallinity and orderliness of NRS. The results of Fourier transform infrared spectroscopy and 1H NMR indicated that GA was successfully grafted onto NRS. After modification, the contact angle of NRS increased from 18.2° to 60.2° (NRS-g-GA; 1:1). The emulsion prepared from NRS-g-GA showed better stability than NRS, improving the emulsification of NRS. Its stable emulsion exhibited an emulsion system dominated by elasticity. Thus, GA could be grafted onto NRS to enhance its emulsifying properties, opening up new applications for GA and NRS and promoting the development of starch-based Pickering emulsions in the future.

Application of Chlorosulfonyl Isocyanate (CSI) in the Synthesis of Fused Tetracyclic Ketone Ring Systems.

Chlorosulfonyl isocyanate (CSI) is a complex reagent capable of facilitating numerous synthetic transformations, including lactam/lactone formation, sulfonylation, Friedel-Crafts-type acylations, and cycloadditions. Annulation reactions to form nitrogen-, oxygen-, and sulfur-bearing heterocycles have been observed with CSI; however, the application of CSI toward the generation of fused cyclic ketone ring systems has not been previously reported. A serendipitous discovery of the pertinence of CSI occurred during a structure-activity relationship campaign around our established lead benzosuberene-based molecule that functions as a potent inhibitor of tubulin polymerization. The benzylic olefin within this molecule represents a promising moiety for further functionalization. CSI was initially investigated as a reagent to effect transformation of this olefin to its corresponding β-lactam functionality, but instead resulted in an unexpected tetracyclic fused ring system in high yield (88%). This finding led to an exploration of the reactivity of CSI with various arenes. Benzosuberene analogues with varying functionalizations were synthesized and treated with CSI, with all examples resulting in a fused ring system except those bearing electron-withdrawing groups. Notably, simplified arene structures with fewer substituents were also observed to undergo cyclization under these conditions. This strategy represents a promising approach for the synthesis of appropriately functionalized tetracyclic ring systems.

Research on magnetic nonchain transport of steel cartridge casing ammunition

Magnetic force is used to drive ferromagnetic objects by shortening the magnetic flux path to reduce magnetic reluctance and increase magnetic conductivity. Based on this characteristic, magnetic force drives have been widely applied in various fields, such as military, transportation, and engineering, attracting significant attention. This paper proposes a method for the nonchain transport of steel shell ammunition based on magnetic force. The force generated by the minimal magnetic resistance in the air gap is utilized to drive the steel shell ammunition. A calculation model for the driving component is proposed using the Maxwell stress tensor method, and the accuracy of the model is verified by simulating ammunition motion curves using finite element software. Finally, prototype experiments are conducted to explore the motion conditions under uncertain ammunition masses. The magnetic nonchain ammunition transport mechanism features a simpler structure and lower maintenance costs, making it more suitable for use on unmanned platforms.

Error performance of DF cooperative SMTs with I/Q imbalance over Beckmann fading channels

The direct down-conversion principle, which has generally been used in the design of multiple-input multiple-output (MIMO) schemes, including space modulation techniques (SMTs), is attractive to researchers because of its low cost, low power consumption with fewer components, flexible and simple structure. However, hardware imperfections such as in-phase (I) and quadrature-phase (Q) imbalance (IQI) negatively affect the performance of the systems with direct down-conversion in practice. On the other hand, cooperative communication is a promising technology that can be utilized in the design of future wireless networks due to its significant advantages such as increasing system reliability, extending network coverage, reducing channel degradation, and providing high quality of service. In this study, SMT-based methods are integrated into cooperative systems, and a flexible and comprehensive model is presented that is applicable to many channel structures. Specifically, the error performance analysis of space shift keying (SSK), spatial modulation (SM), and quadrature SM (QSM) systems in the presence of IQI in decode-and-forward (DF) cooperative communication is carried out by analytical derivations and computer simulations over generalized Beckmann fading channels. The obtained results show that the performance of SMT-based DF cooperative systems is superior to the conventional schemes, and the effects of receiver IQI can be eliminated by optimal detector designs.

Two-dimensional optical micro displacement sensing and crosstalk elimination based on the self-imaging effect of a grating pair

This paper proposes a straightforward method for measuring micro-displacement synchronously along two orthogonal axes. A single structure consists of a pair of two-dimensional gratings and a quadrant detector aligned with a collimated laser is used to detect the micro-displacement. The crosstalk and the common-mode noise are eliminated through a two-step differential process. Experimental results demonstrate that the displacement measurement resolution can reach 40 nm with a sensitivity of 0.483 V/µm within the linear range. The accuracy obtained is 0.29% on the X-axis and 0.31% on the Y-axis within a 500 µm range. The signal-to-noise ratio is improved by 4.56 dB after differential. The simplicity and high compactness of this measurement structure make it suitable for fabrication and alignment using microfabrication processes, which show great potential in many applications such as gyroscopes, accelerators, and multi-dimensional displacement measurements.