Input Frequency Research Articles

Implementation of a motion planning technique for a low-frequency piezo-actuated inchworm drive

A novel piezoelectric inchworm drive capable of long-range motion has been designed, fabricated, and tested in this research work. To control the motion of the inchworm drive, trajectory planning has been proposed. The trajectory planning ensures that the inchworm drive achieves smooth and continuous motion with high accuracy. Two trajectory planning methods were incorporated for the developed inchworm drive: a linear function with a parabolic blend trajectory and a cubic polynomial trajectory. Simulations for both the cubic polynomial and trapezoidal trajectories were conducted, with the estimated displacement results closely verified through experimental validation. The fabricated inchworm drive is tested for varying input voltages and frequencies. The experimental findings demonstrate that the proposed piezoactuated Inchworm drive can achieve substantial displacement, constrained only by the linear slide’s length. When an input signal of 150 V peak to peak and frequency of 10 Hz is applied to the inchworm drive, it was capable of moving at a speed of 1425 μm/s. When incorporating trajectory planning for the Inchworm drive the experimental results show that the maximum percentage error for the trapezoidal motion profile is 1.56% and the cubic polynomial profile trajectory is within 1% for the corresponding target position for a travel range of 25 mm of the inchworm drive.

The Impact of Input Types on Smart Contract Vulnerability Detection Performance Based on Deep Learning: A Preliminary Study

Stemming vulnerabilities out of a smart contract prior to its deployment is essential to ensure the security of decentralized applications. As such, numerous tools and machine-learning-based methods have been proposed to help detect vulnerabilities in smart contracts. Furthermore, various ways of encoding the smart contracts for analysis have also been proposed. However, the impact of these input methods has not been systematically studied, which is the primary goal of this paper. In this preliminary study, we experimented with four common types of input, including Word2Vec, FastText, Bag-of-Words (BoW), and Term Frequency–Inverse Document Frequency (TF-IDF). To focus on the comparison of these input types, we used the same deep-learning model, i.e., convolutional neural networks, in all experiments. Using a public dataset, we compared the vulnerability detection performance of the four input types both in the binary classification scenarios and the multiclass classification scenario. Our findings show that TF-IDF is the best overall input type among the four. TF-IDF has excellent detection performance in all scenarios: (1) it has the best F1 score and accuracy in binary classifications for all vulnerability types except for the delegate vulnerability where TF-IDF comes in a close second, and (2) it comes in a very close second behind BoW (within 0.8%) in the multiclass classification.

The effects of incidental learning and input frequency on the perception of non-native speech

The current study investigated the extent to which naive listeners could incidentally acquire non-native phonemic contrasts and the degree to which the frequency of exposure to the target phonemes affects their learning. A total of 100 English speakers were assigned to the following conditions: (1) 0-occurrence; (2) 2-occurrence; (3) 10-occurrence; (4) 20-occurrence; or (5) 30-occurrence. The participants watched a video that provided instruction on counting numbers in Korean while incidentally exposing them to various repetitions of the target phonemes. All participants completed a pretest, an immediate posttest, and a delayed posttest, each comprising an AX discrimination task. The effects of incidental exposure were found only in the 10-occurrence condition, in both the immediate posttest and the delayed posttest. While the current study demonstrates the overall efficacy of incidental exposure on the perception of non-native speech, it also highlights the important role that selective attention plays in language learning.

Artificial Neural Networks Based Prediction of Penetration in Activated Tungsten Inert Gas Welding

Using GTAW, or tungsten inert gas (TIG) welding, weld penetration is usually lesser than the other arc welding processes. ATIG (Activated-flux TIG) welding can be a good alternative to provide deep penetration, and hence, improved productivity. In this work, 304L SS plate of 8 mm thickness was used as base plate, and a flux with a mixture of SiO2, MnO2 and MoO3 was used as a ternary flux in the ratio of 1:1:2. A 2-factor 3-level response surface methodology of central composite design was considered for designing experimental runs. Back Propagation (BP) type Artificial Neural Networks (ANN) model was developed to assess penetration in ATIG welding by using heat input and pulse frequency as the two process parameters. The ANN chosen has 2-10-1 network structure. Results show that the predicted values through ANN are conforming quite well to the experimentally obtained penetration, and hence, the applicability of ANN.

Mathematical modelling for compliance-assisted artificial muscle based ornithopter

PurposeThis study aims to discuss the mathematical modelling of a compliance-assisted flapping mechanism and morphable structures for an UAV.Design/methodology/approachA compliance-assisted flapping wing was designed and modelled mathematically, and signals for the corresponding curves were calculated. The actual wing tip trace of a hummingbird was taken, and variables a, b, h and k were calculated from the image. This data was given to the mathematical model for plotting the graph, and the curve was compared with the input curve. The wing frame and mechanism for control surfaces using morphing is modelled along with single pivoted spine for centre of gravity augmentation and flight orientation control.FindingsThe model efficiently approximates the 2D path of the wing using line segments using the muscle and compliance mechanism.Practical implicationsUsing a compliance-assisted flapping mechanism offers practical advantages. It allows us to synchronize the flapping frequency with the input signal frequency, ensuring efficient operation. Additionally, the authors can enhance the torque output by using multiple muscle strands, resulting in a substantial increase in the system’s torque-to-weight ratio. This approach proves to be more favourable when compared to conventional methods involving motors or servos, ultimately offering a more efficient and robust solution for practical application.Social implicationsThis model focuses on creating a flexible and tunable mechanism that can at least trace four types of wing traces from the same design, for shifting from one mode of flight to another.Originality/valueConventional ornithopter flapping mechanisms are gear or servo driven and cannot trace a wing tip, but some can trace complicated curves, but only one at a time. This model can trace multiple curves using the same hardware, allowing the user to program the curve based on their needs or bird. The authors may vary the shape of the wing tip trace to switch between forward flight, hovering, backward flying, etc., which is not conceivable with any traditional flapping mechanism.

Absolute measurement of vacuum ultraviolet fluxes from inductively coupled plasmas via metal surface photoemission currents

Quantifying vacuum-ultraviolet (VUV) fluxes typically requires vacuum-compatible spectrometers and is often associated with significant cost and effort. A simple technique for the absolute measurement of local VUV fluxes from plasmas using the photoemission from a set of coated metal plates, is described. The radiant power from a 13.56 MHz hydrogen plasma operating at 40–87 mTorr and with an radio frequency (RF) input power from 100 to 120 W was investigated by irradiating a set of 2 cm diameter Au, Ag and Cu plates. The variation in photoemission currents was compared with the photoelectric yield curves to estimate the absolute flux incident on the surfaces in the 113–190 nm range. The measured fluxes were found to have an uncertainty of 5%–30% when compared with the VUV spectrometer measurements. The VUV output power was found to have a maximum at a pressure of 70–80 mTorr and to increase with RF power. In all cases, the VUV output power was measured to be approximately 12%–16% of the RF input power to the matching network, in good agreement with spectroscopy results.

Degradation mechanism and decomposition of sulfamethoxazole aqueous solution with persulfate activated by dielectric barrier discharge

ABSTRACT The present study focused on the degradation of sulfamethoxazole (SMX) aqueous solution and the toxicity of processing aqueous by the dielectric barrier discharge (DBD) activated persulfate (PS). The effects of input voltage, input frequency, duty cycle, and PS dosage ratio on the SMX degradation efficiency were measured. Based on the results of the Response Surface Methodology (RSM), SMX degradation efficiency reached 83.21% which is 10.54% higher than that without PS, and the kinetic constant was 0.067 min−1 in 30 min when the input voltage at 204 V (input power at 110.6 W), the input frequency at 186 Hz, the duty cycle at 63%, and the PS dosage ratio at 5.1:1. The addition of PS can produce more active particles reached 1.756 mg/L (O3), 0.118 mg/L (H2O2), 0.154 mmol/L (·OH) in 30 min. Furthermore, the DBD plasma system effectively activated an optimal amount of PS, leading to improved removal efficiency of COD, and TOC to 30.21% and 47.21%, respectively. Subsequently, eight primary by-products were pinpointed, alongside the observation of three distinct pathways of transformation. Predictions from the ECOSAR software indicated that most of the degradation intermediates were less toxic than SMX. The biological toxicity experiments elucidated that the treatment with the DBD/PS system effectively reduced the mortality of zebrafish larvae caused by SMX from 100% to 20.13% and improved the hatching rate from 55.69% to 80.86%. In particular, it is important to note that the degradation intermediates exhibit teratogenic effects on zebrafish larvae.

Modelling the developmental path in the acquisition of /l/-final irregular plurals by Portuguese children

ABSTRACT Previous empirical research has shown that Portuguese children aged 4;0 to 6;0 are sensitive to the quality of stem-final vowels when acquiring the irregular plural forms of /l/-final words (acquisition order: plurals of /al, ɛl, ɔl, ul/ > plurals of /il/). This study presents a formal account of this emergent pattern. We first construct an initial-state grammar that arguably instantiates Portuguese children’s grammatical knowledge at the onset of morpho-phonological acquisition. We then simulate morpho-phonological learning using two constraint-based models (Stochastic Optimality Theory and Noisy Harmonic Grammar) and their associated Gradual Learning Algorithm. The results of our learning simulations corroborate the experimental data, showing that the plural form of /il/-final words takes longer to master than that of other /l/-final words. In addition to replicating the empirical results, the learning simulation reveals two important implications. First, the raw frequency of individual forms cannot account for the attested patterns, suggesting that the input frequency is mediated by some principles of grammatical learning. Second, Harmonic Grammar outperforms Optimality Theory in simulating real acquisition data. Through the additive constraint interaction, Harmonic-Grammar learning is more restrictive, avoiding the generation of unobserved data in the course of morpho-phonological acquisition.

Effects of management practices on the ecosystem-service multifunctionality of temperate grasslands

Human wellbeing depends on ecosystem services, highlighting the need for improving the ecosystem-service multifunctionality of food and feed production systems. We study Swiss agricultural grasslands to assess how employing and combining three widespread aspects of grassland management and their interactions can enhance 22 plot-level ecosystem service indicators, as well as ecosystem-service multifunctionality. The three management aspects we assess are i) organic production system, ii) an eco-scheme prescribing extensive management (without fertilization), and iii) harvest type (pasture vs. meadow). While organic production system and interactions between the three management aspects play a minor role, the main effects of eco-scheme and harvest type considerably shape single services. Moreover, the eco-scheme ‘extensive management’ and the harvest type ‘pasture’ enhance plot-scale ecosystem-service multifunctionality, mostly through facilitating cultural services at the expense of provisioning services. These changes in ecosystem-service supply occur mainly via changes in land-use intensity, i.e., reduced fertilizer input and harvest frequency. In conclusion, diversifying grassland management where this is currently homogeneous across farms and landscapes depicts an important first step to improve landscape-scale multifunctionality for sustainable grassland systems. To meet societal ecosystem services demand, the three studied management aspects can be systematically combined to increase ecosystem services that are in short supply.

Muscarinic Modulation of Synaptic Transmission and Short-Term Plasticity in the Dorsal and Ventral Hippocampus

Muscarinic neurotransmission is fundamentally involved in supporting several brain functions by modulating flow of information in brain neural circuits including the hippocampus which displays a remarkable functional segregation along its longitudinal axis. However, how muscarinic neuromodulation contributes to the functional segregation along the hippocampus remains unclear. In this study we show that the nonselective muscarinic receptor agonist carbachol similarly suppresses basal synaptic transmission in the dorsal and ventral CA1 hippocampal field, in a concentration-depended manner. Furthermore, using a ten-pulse stimulation train of varying frequency we found that carbachol changes the frequency filtering properties more in ventral than dorsal hippocampus by facilitating synaptic inputs at a wide range of input frequencies in the ventral compared with dorsal hippocampus. Using the M2 receptor antagonist gallamine and the M4 receptor antagonist tropicamide, we found that M2 receptors are involved in controlling basal synaptic transmission and short-term synaptic plasticity (STSP) in the ventral but not the dorsal hippocampus, while M4 receptors participate in modulating basal synaptic transmission and STSP in both segments of the hippocampus. These results were corroborated by the higher protein expression levels of M2 receptors in the ventral compared with dorsal hippocampus. We conclude that muscarinic transmission modulates excitatory synaptic transmission and short-term synaptic plasticity along the entire rat hippocampus by acting through M4 receptors and recruiting M2 receptors only in the ventral hippocampus. Furthermore, M4 receptors appear to exert a permissive role on the actions of M2 receptors on STSP in the ventral hippocampus. This dorsoventral differentiation of muscarinic modulation is expected to have important implications in information processing along the endogenous hippocampal circuitry.

Role of endogenous soil microorganisms in controlling antimicrobial resistance after the exposure to treated wastewater

The reuse of treated wastewater (TWW) for irrigation appears to be a relevant solution to the challenges of growing water demand and scarcity. However, TWW contains not only micro-pollutants including pharmaceutical residues but also antibiotic resistant bacteria. The reuse of TWW could contribute to the dissemination of antimicrobial resistance in the environment. The purpose of this study was to assess if exogenous bacteria from irrigation waters (TWW or tap water-TP) affect endogenous soil microbial communities (from 2 soils with distinct irrigation history) and key antibiotic resistance gene sul1 and mobile genetic elements intl1 and IS613. Experiments were conducted in microcosms, irrigated in one-shot, and monitored for three months. Results showed that TP or TWW exposure induced a dynamic response of soil microbial communities but with no significant increase of resistance and mobile gene abundances. However, no significant differences were observed between the two water types in the current experimental design. Despite this, the 16S rDNA analysis of the two soils irrigated for two years either with tap water or TWW resulted in soil microbial community differentiation and the identification of biomarkers from Xanthomonadaceae and Planctomycetes families for soils irrigated with TWW. Low-diversity soils were more sensitive to the addition of TWW. Indeed, TWW exposure stimulated the growth of bacterial genera known to be pathogenic, correlating with a sharp increase in the copy number of selected resistance genes (up to 3 logs). These low-diversity soils could thus enable the establishment of exogenous bacteria from TWW which was not observed with native soils. In particular, the emergence of Planctomyces, previously suggested as a biomarker of soil irrigated by TWW, was here demonstrated. Finally, this study showed that water input frequency, initial soil microbial diversity and soil history drive changes within soil endogenous communities and the antibiotic resistance gene pool.

Electro-optomechanical entanglement in two coupled optical cavities with an LC microwave circuit

We theoretically investigate entanglement in a hybrid quantum system comprising two optical cavities coupled to a shared microwave cavity via optomechanical interactions. Our results demonstrate that increasing the microwave input power and frequency in the allowed range enhances entanglement between the microwave–optical and optical–optical modes. We also show by change frequency of the one optical cavity in the communication domain that we still have entanglement. This ability to generate robust microwave–optical photon entanglement shows promise for various quantum technologies. Optical photons could enable secure quantum communication in optical fibers, while microwave photons allow transmission to satellites. Overall, this hybrid cavity optomechanical system offers prospects as an efficient source of entangled photon pairs, vital for implementing long-distance quantum communication networks.

Interplay of synchronization and cortical input in models of brain networks

It is well known that synchronization patterns and coherence have a major role in the functioning of brain networks, both in pathological and in healthy states. In particular, in the perception of sound, one can observe an increase in coherence between the global dynamics in the network and the auditory input. In this perspective article, we show that synchronization scenarios are determined by a fine interplay between network topology, the location of the input, and frequencies of these cortical input signals. To this end, we analyze the influence of an external stimulation in a network of FitzHugh-Nagumo oscillators with empirically measured structural connectivity, and discuss different areas of cortical stimulation, including the auditory cortex.

Learning the Meanings of Function Words From Grounded Language Using a Visual Question Answering Model.

Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question answering models apparently can learn to use function words as part of answering questions about complex visual scenes. In this paper, we study what these models learn about function words, in the hope of better understanding how the meanings of these words can be learned by both models and children. We show that recurrent models trained on visually grounded language learn gradient semantics for function words requiring spatial and numerical reasoning. Furthermore, we find that these models can learn the meanings of logical connectives and and or without any prior knowledge of logical reasoning as well as early evidence that they are sensitive to alternative expressions when interpreting language. Finally, we show that word learning difficulty is dependent on the frequency of models' input. Our findings offer proof-of-concept evidence that it is possible to learn the nuanced interpretations of function words in a visually grounded context by using non-symbolic general statistical learning algorithms, without any prior knowledge of linguisticmeaning.

A Novel Ultra-Low Input Voltage and Frequency Self Starting AC–DC Boost Converter for Micro Energy Harvesting

A Novel Ultra-Low Input Voltage and Frequency Self Starting AC–DC Boost Converter for Micro Energy Harvesting

Chapter 4: Introduction and Getting Ready for Real-Ear Probe Microphone Measures.

Probe microphone measurements are an essential step in an individualized hearing aid fitting. These measurements allow audiologists to account for the individual's hearing and ear canal acoustics when programming hearing aids. An evidence-based hearing aid fitting includes matching the measured output of the hearing aids to targets for each input level and frequency. This allows the audiologist to confidently counsel the patient that the acoustic fitting is accurate, and the next step is for the individual to use the amplification during all waking hours to adapt to the newly amplified sounds. This also avoids mistakes such as overamplification or insufficient gain, which can endanger the patient and/or lead to a compromised fitting.

Fixed‐time consensus of networked Euler–Lagrange systems over event‐based communication under DoS attacks

AbstractThis article focuses on fixed‐time consensus of networked Euler–Lagrange systems (NELSs) over event‐based communication under denial‐of‐service (DoS) attacks. First of all, a basic fixed‐time consensus algorithm is developed for NELSs, where a general fixed‐time communication triggering scheme through error decomposition method is designed for decreasing communication frequencies while avoiding singularity. Then, to fulfil the consensus problem of NELSs in the presence of DoS attacks, a novel fixed‐time resilient algorithm is further presented by the basic algorithm, where the effective attack interval is redefined for carrying out the algorithm design. Furthermore, a hierarchical fixed‐time control framework with privacy preservation is introduced for the consensus problem of NELSs under DoS attacks. Meanwhile, a self‐triggered scheme is employed for the above algorithms to lower the update frequencies of control inputs. The stated algorithms possess a uniformly constrained upper bound on the convergence time, and are resilient as well as responsive to DOS attacks while saving control resources significantly. Finally, numerous illustrative examples are given for demonstrating the efficacy of the derived schemes.

MnO/ZnO:Zn Thin-Film Frequency Adaptive Heterostructure for Future Sustainable Memristive Systems.

In recent years, advances in materials engineering based on adaptive electronics have found a new paradigm to optimize drawbacks in signal processing. A two-layer MnO/ZnO:Zn heterostructure envisioned for frequency adaptive electronic signal processing is synthesized by sputtering, where the use of internal states allows reconfigurability to obtain new operating modes at different frequency input signals. X-ray diffraction (XRD) analysis is performed on each layer, revealing a cubic structure for MnO and a hexagonal structure for ZnO:Zn with preferential growth in [111] and [002] directions, respectively. Scanning electron microscope (SEM) micrographs show that the surface of both materials is homogeneous and smooth. The thickness for each layer is determined to be approximately 106.3 nm for MnO, 119.3 nm for ZnO:Zn and 224.1 nm for the MnO/ZnO:Zn structure. An electrical characterisation with an oscilloscope and signal generator was carried out to obtain the time-response signals and current-voltage (I-V) curves, where no degradation is detected when changing frequencies within the range of 100 Hz to 1 MHz. An equivalent circuit is proposed to explain the effects in the interface. Measurements of switching speeds from high resistance state (HRS) to low resistance state (LRS) at approximately 17 ns, highlight the device's rapid adaptability, and an estimated switching ratio of approximately 2 × 104 indicates its efficiency as a memristive component. Finally, the MnO/ZnO:Zn heterojunction delivers states that are stable, repeatable, and reproducible, demonstrating how the interaction of the materials can be utilised in adaptive device applications by applying frequencies and internal states to create new and innovative design schematics, thus reducing the number of components/connections in a system for future sustainable electronics.

Investigation of Legendre polynomials expanded adaptive controller with inverse compensation for high frequency tracking of electro-hydraulic force systems

Accurate force tracking of an electro-hydraulic force system (EHFS) is of great significance in various industrial applications. As the EHFS is inevitably confronted with hydraulic nonlinearities, dynamic variations and uncertain disturbances, the real-time force tracking performance is generally unsatisfactory, especially for high frequency command force signals. For reducing the force tracking error with relatively high frequency inputs, a Legendre polynomials expanded adaptive controller with inverse compensation is proposed in this paper. The proposed controller is constructed by introducing an offline designed inverse compensation (IC) controller and an online adaptive controller to the EHFS governed by traditional Proportional Integral (PI) controller, in which the former IC controller is acting as the inner loop controller and the latter adaptive controller is regarded as an outer controller. The inner loop IC controller with fixed control parameters is offline designed on the basis of traditional PI controller by means of the generalized projection identification algorithm and the zero magnitude error tracking technology, focusing on extending the real-time force tracking bandwidth of the EHFS. The outer loop online adaptive controller is developed by Legendre polynomials expanded adaptive filters with nonlinear mapping ability, whose weights are online updated by an adaptive tuning algorithm with the aim of handling system’s dynamic variations, nonlinearities and uncertain disturbances. The proposed controller is implemented on a real EHFS test rig by the xPC/Target rapid prototyping technique, and comparative experimental results demonstrate that the proposed controller can achieve much higher high frequency tracking performance than the traditional PI and IC controller commonly used in industry.

Study on Dynamic Post-Buckling Stability of Thin-Walled Cylinders Subjected to Horizontal Vibration

Abstract As a lesson learned from the Fukushima nuclear accident, the importance of accident mitigation for beyond design basis events (BDBEs) is recognized. Excessive earthquake is a typical BDBE. During such events, the fast reactor main vessel (FRMV) is vulnerable to buckling because of its thin-walled cylindrical structure. Buckling deformation without causing immediate collapse should not be considered as a limit state in BDBEs. Instead, the objective is to achieve a stable post-buckling state. In the present study, dynamic post-buckling behavior of thin-walled cylinders under intense horizontal vibration is experimentally studied, which simulates loop-type FRMV design. Finite element method (FEM) simulation is also conducted and validated by experimental data. Based on results analysis, a global response stability after buckling is confirmed. The buckled model shows resilience to withstand catastrophic collapse even when intense excitation continues to apply. Using equivalent linear response method, dynamic mechanisms behind the stability are revealed. Due to substantial degradation of structural stiffness, the post-buckling response shifts into the out-of-phase domain such that response divergence is prevented. Meanwhile, the response is notably delayed from the input, which impedes the conversion of input energy into kinetic energy, reducing the inertial impact to the structure. These mechanisms are found to be independent of input waveforms and can be applied to a general seismic scenario. Moreover, the limit for global response stability after buckling and the effect of input frequency on the post-buckling behavior are clarified.