Dynamic Frequency Research Articles

Effects of Ultrasonic Power on the Structure and Rheological Properties of Skin Collagen from Albacore (Thunnus alalunga).

The effects of ultrasonic power (0, 150, 300, 450, and 600 W) on the extraction yield and the structure and rheological properties of pepsin-soluble collagen (PSC) from albacore skin were investigated. Compared with the conventional pepsin extraction method, ultrasonic treatment (UPSC) significantly increased the extraction yield of collagen from albacore skin, with a maximum increase of 8.56%. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis revealed that peptides of low molecular weight were produced when the ultrasonic power exceeded 300 W. Meanwhile, secondary structure, tertiary structure, and X-ray diffraction analyses showed that the original triple helix structure of collagen was intact after the ultrasonic treatment. The collagen solutions extracted under different ultrasonic powers had significant effects on the dynamic frequency sweep, but a steady shear test suggested that the collagen extracted at 150 W had the best viscosity. These results indicate that an ultrasonic power between 150 and 300 W can improve not only the extraction yield of natural collagen, but also the rheological properties of the collagen solution without compromising the triple helix structure.

Extended Kalman filtering for enhancing a cyclic pattern-updating scheme of single-pixel dynamic fluorescence spatial frequency domain imaging: publisher's note.

This publisher's note contains a correction to Opt. Lett.48, 5443 (2023)10.1364/OL.495099.

Effect of PV Plant on Frequency Stability in IEEE12 Bus System for Different Penetration Levels and Depth of Frequency Support

The utilization of renewable energy sources, particularly large-scale photovoltaic plants (PVPs), has been increasing in power systems. However, the high penetration of PVPs in power systems has implications for the system's moment of inertia and frequency response. Therefore, it is crucial to thoroughly investigate the impact of PVPs on system frequency. This study focuses on investigating the effects of a large-scale PVP at various penetration levels on frequency and the depth of frequency support. The study proposes a strategy aimed at maximizing power generation from PVPs while also providing support to system frequency. To assess the effects of PVPs, the study examines events such as load outages, generator outages, load changes, and three-phase short circuits. Additionally, the relationship between voltage and frequency during these events is considered, with the load represented by an impedance model. By studying the depth of frequency support alongside different penetration levels, the study provides a detailed understanding of the impact of PVPs on frequency. The study aims to determine the threshold at which the penetration level of PVPs becomes significant in terms of frequency support. This analysis sheds light on the point at which the presence of PVPs begins to exert a notable influence on frequency stability and support within the power system. Overall, the study contributes to the integration of PVPs in power systems by providing insights into their impact on frequency dynamics and proposing strategies to enhance power generation and frequency support simultaneously.

Emergent strong zero mode through local Floquet engineering

Periodically driven quantum systems host exotic phenomena that often do not have any analog in undriven systems. Floquet prethermalization and dynamical freezing of certain observables, via the emergence of conservation laws, are realized by controlling the drive frequency. Recent experimental developments in synthetic quantum matter, such as superconducting qubits and cold atoms, have opened avenues for implementing local Floquet engineering which can achieve spatially modulated quantum control of states. Here, we uncover the novel memory effects of local periodic driving in a nonintegrable spin-half staggered Heisenberg chain. For a boundary-driven protocol at the dynamical freezing frequency, we show the formation of an approximate strong zero mode, a prethermal quasilocal operator, due to the emergence of a discrete global Z2 symmetry. This is captured by constructing an accurate effective Floquet Hamiltonian using a higher-order partially resummed Floquet-Magnus expansion. The lifetime of the boundary spin can be exponentially enhanced by enlarging the set of suitably chosen driven sites. We demonstrate that in the asymptotic limit, achieved by increasing the number of driven sites, a strong zero mode emerges, where the lifetime of the boundary spin grows exponentially with system size. The nonlocal processes in the Floquet Hamiltonian play a pivotal role in the total freezing of the boundary spin in the thermodynamic limit. The novel dynamics of the boundary spin is accompanied by a rich structure of entanglement in the Floquet eigenstates where specific bipartitions yield an area-law scaling while the entanglement for random bipartitions scales as a volume-law. Our work addresses the long-standing question of the existence of a strong zero mode in a nonintegrable model and elucidates the complex nature of thermalization in locally driven systems. Published by the American Physical Society 2024

A modified stochastic finite-fault method for estimating strong ground motion: Validation and application

We developed a modified stochastic finite-fault method for estimating strong ground motions. An adjustment to the dynamic corner frequency was introduced, which accounted for the effect of the location of the subfault relative to the hypocenter and rupture propagation direction, to account for the influence of the rupture propagation direction on the subfault dynamic corner frequency. By comparing the peak ground acceleration (PGA), pseudo-absolute response spectra acceleration (PSA, damping ratio of 5%), and duration, the results of the modified and existing methods were compared, demonstrating that our proposed adjustment to the dynamic corner frequency can accurately reflect the rupture directivity effect. We applied our modified method to simulate near-field strong motions within 150 km of the 2008 MW7.9 Wenchuan earthquake rupture. Our modified method performed well over a broad period range, particularly at 0.04–4 s. The total deviations of the stochastic finite-fault method (EXSIM) and the modified EXSIM were 0.1676 and 0.1494, respectively. The modified method can effectively account for the influence of the rupture propagation direction and provide more realistic ground motion estimations for earthquake disaster mitigation.

Ionization and neutral gas heating efficiency in radio frequency electrothermal microthrusters: The role of driving frequency

The development of compact, low power, charge–neutral propulsion sources is of significant recent interest due to the rising application of micro-scale satellite platforms. Among such sources, radio frequency (rf) electrothermal microthrusters present an attractive option due to their scalability, reliability, and tunable control of power coupling to the propellant. For micropropulsion applications, where available power is limited, it is of particular importance to understand how electrical power can be transferred to the propellant efficiently, a process that is underpinned by the plasma sheath dynamics. In this work, two-dimensional fluid/Monte Carlo simulations are employed to investigate the effects of applied voltage frequency on the electron, ion, and neutral heating in an rf capacitively coupled plasma microthruster operating in argon. Variations in the electron and argon ion densities and power deposition, and their consequent effect on neutral-gas heating, are investigated with relation to the phase-averaged and phase-resolved sheath dynamics for rf voltage frequencies of 6–108 MHz at 450 V. Driving voltage frequencies above 40.68 MHz exhibit enhanced volumetric ionization from bulk electrons at the expense of the ion heating efficiency. Lower driving voltage frequencies below 13.56 MHz exhibit more efficient ionization due to secondary electrons and an increasing fraction of rf power deposition into ions. Thermal efficiencies are improved by a factor of 2.5 at 6 MHz as compared to the more traditional 13.56 MHz, indicating a favorable operating regime for low power satellite applications.

There’s More to Timing than Time

The TIME project: Timing and Sound in Musical Microrhythm (2017–2022) studied microrhythm; that is, how dynamic envelope, timbre, and center frequency, as well as the microtiming of a variety of sounds, affect their perceived rhythmic properties. The project involved theoretical work regarding the basic aspects of microrhythm; experimental studies of microrhythm perception, exploring both stimulus features and the participants’ enculturated expertise; observational studies of how musicians produce particular microrhythms; and ethnographic studies of musicians’ descriptions of microrhythm. Collectively, we show that: (a) altering the microstructure of a sound (“what” the sound is) changes its perceived temporal location (“when” it occurs), (b) there are systematic effects of core acoustic factors (duration, attack) on microrhythmic perception, (c) microrhythmic features in longer and more complex sounds can give rise to different perceptions of the same sound, and (d) musicians are highly aware of microrhythms and have developed vocabularies for describing them. In addition, our results shed light on conflicting results regarding the effect of microtiming on the “grooviness” of a rhythm. Our use of multiple, interdisciplinary methodologies enabled us to uncover the complexity of microrhythm perception and production in both laboratory and real-world musical contexts.

Time and frequency dynamics between NFT coins and economic uncertainty

Non-fungible tokens (NFTs) are one-of-a-kind digital assets that are stored on a blockchain. Examples of NFTs include art (e.g., image, video, animation), collectables (e.g., autographs), and objects from games (e.g., weapons and poisons). NFTs provide content creators and artists a way to promote and sell their unique digital material online. NFT coins underpin the ecosystems that support NFTs and are a new and emerging asset class and, as a new and emerging asset class, NFT coins are not immune to economic uncertainty. This research seeks to address the following questions. What is the time and frequency relationship between economic uncertainty and NFT coins? Is the relationship similar across different NFT coins? As an emerging asset, do NFT coins exhibit explosive behavior and if so, what role does economic uncertainty play in their formation? Using a new Twitter-based economic uncertainty index and a related equity market uncertainty index it is found that wavelet coherence between NFT coin prices (ENJ, MANA, THETA, XTZ) and economic uncertainty or market uncertainty is strongest during the periods January 2020 to July 2020 and January 2022 to July 2022. Periods of high significance are centered around the 64-day scale. During periods of high coherence, economic and market uncertainty exhibit an out of phase relationship with NFT coin prices. Network connectedness shows that the highest connectedness occurred during 2020 and 2022 which is consistent with the findings from wavelet analysis. Infectious disease outbreaks (COVID-19), NFT coin price volatility, and Twitter-based economic uncertainty determine bubbles in NFT coin prices.

Dynamic Time-Varying Frequency Connectedness Analysis across Crude Oil, Geopolitical Risk, Economic Policy Uncertainty, and Stock Markets

Dynamic Time-Varying Frequency Connectedness Analysis across Crude Oil, Geopolitical Risk, Economic Policy Uncertainty, and Stock Markets

Artificial Intelligence Driven Power Optimization in IOT-Enabled Wireless Sensor Networks

The widespread use of Wireless Sensor Networks (WSN) in Internet of Things (IoT) causes energy efficiency issues. This paper proposes an AI-based solution to this problem. The propose an AI-Driven Power Optimization framework for IoT-enabled WSN using Deep Q-Network (DQN) and Dynamic Voltage and Frequency Scaling (DVFS). These techniques can adapt to changing network conditions and reduce power consumption when used together. Sensor nodes provide environmental parameters, battery status, and network behavior data to the AI-driven framework DQN is implemented after data preprocessing to learn and make power management decisions using reinforcement learning. Neural network-driven agent operates in a state and action space. It optimizes energy use with rewards. Real-time hardware power adjustment is done using DVFS. DVFS precise control and AI-driven decision-making create a comprehensive power optimization strategy. AI adapts to new challenges and optimizes network lifespan by improving its power management policies. Experimental implementations of the proposed framework show significant energy savings, network lifespan extension, and QoS improvements. AI-Driven Power Optimization in IoT-enabled WSN is proven effective and flexible. This study shows the potential of AI, specifically DQN and DVFS, in IoT-enabled WSN. This AI-Driven Power Optimization framework addresses energy efficiency and improves IoT sensor networks. AI improves power optimization in IoT-enabled WSN making IoT deployments more sustainable and resilient.

Terahertz Photons Inhibit Cancer Cells Long Term by Suppressing Nano Telomerase Activity.

Telomeres are nanoscale DNA-protein complexes to protect and stabilize chromosomes. The reexpression of telomerase in cancer cells is a key determinant crucial for the infinite proliferation and long-term survival of most cancer cells. However, the use of telomerase inhibitors for cancer treatment may cause problems such as poor specificity, drug resistance, and cytotoxicity. Here, we discovered a nondrug and noninvasive terahertz modulation strategy capable of the long-term suppression of cancer cells by inhibiting telomerase activity. First, we found that an optimized frequency of 33 THz photon irradiation effectively inhibited the telomerase activity by molecular dynamics simulation and frequency filtering experiments. Moreover, in vitro experiments showed that telomerase activity in 4T1 and MCF-7 cells significantly decreased by 77% and 80% respectively, after 21 days of regular 33 THz irradiation. Furthermore, two kinds of cells were found to undergo aging, apoptosis, and DNA double-strand breaks caused by telomere crisis, which seriously affected the survival of cancer cells. In addition, the tumorigenicity of 4T1 cells irradiated with 33 THz waves for 21 days in in vivo mice decreased by 70%. In summary, this study demonstrates the potential application of THz modulation in nano therapy for cancer.

Challenges in achieving adequate glycemic control among children with type 1 diabetes mellitus in a resource-limited setting: A cross-sectional study from Sudan

ObjectiveTo assess glycemic control and associated factors in children with type 1 diabetes mellitus (T1DM) attending the pediatric diabetes clinic in Wad-Madani City, Sudan. MethodsThis cross-sectional observational study was conducted at a referral center in Sudan. The study population consisted of children aged 1–18 years who had been diagnosed with T1DM for more than 1 year and were under regular follow-up in the clinic. Data on their glycemic control and sociodemographic and clinical characteristics were captured. ResultsOut of 211 enrolled patients, 120 (56.9 %) were females. The mean age was 11.7 years (SD = 4.0), with the mean age at diagnosis of 6.7 years (SD = 4.0). Only 6.2 % achieved adequate glycemic control. Adolescents had particularly poor control (97.8 %). The mean glycosylated hemoglobin (HBA1c) level was 10.4 % (90 mmol/mol). Inferior glycemic control was associated with advancing age, older age at diagnosis, belonging to single-parent households, less frequent self-monitoring of blood glucose (SMBG), and having a greater number of siblings or household members. A third of patients (33.8 %) had had one or more diabetes ketoacidosis (DKA) episodes in the previous year. There was a high prevalence of lipodystrophy (34.1 %) and arthropathy (25.1 %). ConclusionsAn exceptionally low proportion of children with T1DM achieved adequate glycemic control, with adolescents particularly struggling. SMBG frequency and family dynamics emerged as potential factors, highlighting the urgent need for tailored interventions and improved diabetes education in resource-limited settings.

Coordinated restoration of inverter‐based power sources and synchronous generators for the high renewable penetrated power system considering the dynamic frequency regulation capability

AbstractExtensive inverter‐based power sources (IPS) impose significant challenges on the restoration of high renewable penetrated power systems (HRPPS). To enhance HRPPS resilience, the proper utilization of IPSs must be implemented. Combining frequency dynamics of IPSs and synchronous generators, this paper proposes a coordinated restoration method for multi‐type power sources after a major blackout. First, interactions between synchronous generators and IPSs are systematically analyzed. Based on this, output characteristics and constraints of IPSs in the power sources restoration process are quantified. Second, the dynamic frequency regulation capability (DFRC) of restored systems is quantified based on a unified transfer function structure model. Then the maximum power disturbance that restored systems can bear is derived based on DFRC indices including the maximum frequency deviation and the rate of change of frequency. Third, considering interactions between power sources and the DFRC of restored systems, a coordinated restoration optimization model of multi‐type power sources is proposed. Finally, case studies based on a modified IEEE 39‐bus system are simulated to verify the applicability and superiority of the proposed method. Meanwhile, results show that the proposed method for quantifying DFRC is more suitable for HRPPSs than traditional inertia‐based methods.

Changes in eating habits and lifestyle during the first year of the COVID-19 pandemic across metropolitan regions in Brazil and Germany: A survey-based cross-sectional study.

COVID-19 caused profound societal changes to cope rapidly with the new circumstances. The food market changed its quantity, quality, form, and frequency dynamics. Consequently, food-eating habits and lifestyles like physical exercise likely experienced changes. An online-based survey was conducted between June 2020 and January 2021 in the metropolitan regions of Rhine Ruhr Metropolis (RRM), Greater São Paulo (GSP), other metropolitan regions in São Paulo state (oMRSP), other Brazilian metropolitan regions (oBRMR), and the remaining urban areas in both countries (oUA), representing different contexts of Brazil and Germany. We assessed self-reported changes in physical activity level, diet quality, self-reported eating habits, and buying groceries during the first year of the pandemic. In Germany, indoor and outdoor activities increased for 34% of the respondents, while in Brazil, there was a decrease in physical activity for 50% of the participants. The Healthy Eating Index (HEI) scored higher among Brazilians (16.8) than Germans (15.2) on a 0-29 HEI scale. Increased awareness of healthy and sustainable eating habits was observed in GSP (0.7), oMRSP (0.63), oBRMR (0.7), and oUA (0.68) on a scale from no change (0) to change (1). In RRM, an increase in convenience foods was noticed (0.86). Participants reported discomfort with food purchasing due to hygiene measures and avoided going to the supermarket (0.7 on average in Brazil and 0.58 for females using the same 0-1 scale). Also, food supply at the grocery shops was reported to be often unavailable and in lower quantities. A real-time assessment of self-reported changes in eating habits and lifestyle during the lockdown in 2020 in different contexts is insightful for rethinking strategies to improve conditions in the post-COVID-19 era and prepare for future pandemics.

FREQUENCY SYNCHRONIZATION REVEALS THAT SPIKE-WAVE DISCHARGES IN WAG/RIJ RATS ARE SIGNIFICANTLY NONLINEAR PHENOMENON

In this work, we studied the time-frequency dynamics of spike-wave discharges in rats with predisposition to absence epilepsy (WAG/Rij line) in two frequency ranges: 7–12,Hz and 14–24,Hz. The first and the second harmonics of the seizure main frequency lie in these ranges. Recordings of brain local field potentials of eight animals in eleven experiments of eight hour duration were analyzed. The method was based on the fast Fourier transform with a Hann’s window, and skeletons were constructed based on the obtained spectrograms. Using the skeletons, a visual and automated numerical assessment of the main frequency evolution was performed. As a result of this analysis, it was shown that temporal dynamics of the main frequency in the range 14–24,Hz follows the dynamics of the main frequency in the range 7–12,Hz. Since during the baseline activity the main frequencies in two considered ranges were developing independently, our finding indicates that the discharge is a significantly nonlinear process.

Influence of changes in tip structure on wind wheel vibration characteristics under wind wheel-tower coupling

This study conducted modal and vibration-characteristic tests using transient excitation and spectrum analysis methods to find the variation law of vibration characteristics of wind wheels with bifurcated tip structures as compared to wind wheels with unmodified tips when the coupling between a wind wheel and its tower is considered. Additionally, a finite element analysis was used to calculate the mechanical characteristics of wind power manoeuvres. The following are the major results of this study. As compared to the non-trailer state, the coupling action of the wind wheel and the tower reduced the static frequency of the unmodified wind wheel and the bifurcated blade tip structure wind wheel under the trailer state. The static frequency of the bifurcated blade tip structure wind wheel under the coupling action decreases more significantly. Compared with the single wind wheel which is not affected by coupling, the dynamic frequency of the whole machine decreases after being affected by coupling, and the bifurcated blade structure has less influence on the coupling effect. Compared with the non-trailer state, the dynamic frequency curves of the two blade tip structure wind wheels in the trailer state decrease, the speed range in the resonance area is shortened, and the corresponding speed in the resonance area is reduced. The results of this study provide data support and design reference for reliable design of wind turbines.

Multi-criteria Optimization of Real-time DAGs on Heterogeneous Platforms under P-EDF

This article tackles the problem of optimal placement of complex real-time embedded applications on heterogeneous platforms. Applications are composed of directed acyclic graphs of tasks, with each directed-acyclic-graph (DAG) having a minimum inter-arrival period for its activation requests and an end-to-end deadline within which all of the computations need to terminate since each activation. The platforms of interest are heterogeneous power-aware multi-core platforms with Dynamic Voltage and Frequency Scaling (DVFS) capabilities, including big.LITTLE Arm architectures and platforms with GPU or FPGA hardware accelerators with Dynamic Partial Reconfiguration capabilities. Tasks can be deployed on CPUs using partitioned EDF-based scheduling. Additionally, some of the tasks may have an alternate implementation available for one of the accelerators on the target platform, which are assumed to serve requests in non-preemptive FIFO order. The system can be optimized by minimizing power consumption, respecting precise timing constraints, maximizing the applications’ slack, respecting given power consumption constraints, or even a combination of these, in a multi-objective formulation. We propose an off-line optimization of the mentioned problem based on mixed-integer quadratic constraint programming (MIQCP). The optimization provides the DVFS configuration of all the CPUs (or accelerators) capable of frequency switching and the placement to be followed by each task in the DAGs, including the software-vs.-hardware implementation choice for tasks that can be hardware accelerated. For relatively big problems, we developed heuristic solvers capable of providing suboptimal solutions in a significantly reduced time compared to the MIQCP strategy, thus widening the applicability of the proposed framework. We validate the approach by running a set of randomly generated DAGs on Linux under SCHED_DEADLINE, deployed onto two real boards, one with Arm big.LITTLE architecture, the other with FPGA acceleration, verifying that the experimental runs meet the theoretical expectations in terms of timing and power optimization goals.

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Given the increasing interests in carbon neutrality due to climate change, photovoltaic (PV)‐based microgrid has become an important research topic worldwide. Typically, high PV penetration without proper control schemes causes power quality issues such as voltage or frequency violation, resulting in the limited PV hosting capacity. Reactive and active power support from the PV is effective to solve the issues, however, it is a critical challenge to efficiently contribute to the stabilizing controls under the inverter capacity constraint. Recent studies have applied smart inverters, equipped with fixed active and reactive power control reserves, for dynamic voltage and frequency support. In this paper, we proposed a control strategy in which the control reserves for voltage and frequency support are flexibly adjusted using virtual power factor (VPF) to improve the power quality with reducing active power curtailment. The effectiveness of the proposed Q‐V/P‐f control is verified through numerical simulations using a microgrid model developed in MATLAB/Simulink platform. It was observed through the simulation that the proposed method contributed to mitigating voltage and frequency fluctuation with satisfying the inverter capacity constraint. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Large-size gold–aluminum alloy cluster Al12Au60 stabilized by an encapsulating B12 icosahedron: a first-principles study

The investigation of novel clusters incorporating gold (Au) has attracted increasing attention due to their intriguing architecture and feasibility of experimental synthesis. In this study, a large-size gold–aluminum alloy cluster with icosahedral B12 as its core, specifically a B12@Al12Au60 cluster, is proposed and demonstrated to have remarkable stability as ascertained through first-principles calculations. The core–shell assembly, B12@Al12Au60, exhibiting I symmetry, is characterized by the incorporation of an icosahedral B12 motif within the outer shell of the Al12Au60 framework. By thorough analysis encompassing vibrational frequency and molecular dynamics simulations, the structural stability of the core–shell B12@Al12Au60 is investigated. The electronic characteristics are probed through adaptive natural density partitioning analysis, revealing the presence of 66 multi-center two-electron σ bonds distributed across the entirety of the core–shell configuration. Furthermore, scrutiny of distinct dimeric configurations composed of core–shell B12@Al12Au60 underscores their relative autonomy and potential prospects for applications within cluster-assembled materials.

Adaptive rock-paper-scissors game enhances eco-evolutionary performance at cost of dynamic stability

The rock-paper-scissors (RPS) game is a classic model for exploring the performance of how multiple strategies interact and evolve over time. The classic RPS game assumes a fixed benefit and cost for each strategy against another one when two players meet, while its evolutionary game considers the frequency dynamics of the three strategies with each's fitness influenced by its net payoff. This may not reflect the complexity of real-world scenarios as strategies can co-adapt with each other. We introduce an adaptive RPS game that captures the dynamics of strategy densities with trait-mediated payoffs, and the adaptive dynamics of coevolving traits via incremental mutations leading to adaptively evolving payoffs. Results show that the adaptive RPS game approaches a steady state of strategy density, if any, faster than the evolutionary RPS game. The stable coexistence of all strategies in the evolutionary game can be easily destabilized in the adaptive game. Strategies that are allowed to adaptively change their traits also performed better and achieved greater strategy densities than those fixed strategies in the adaptive game. The coevolving strategies in the adaptive RPS game exhibit complex and diverse attractors in the trait space, sensitive to both initial conditions and model parameters, but exhibiting positive payoffs with greater benefits than costs. These findings highlight how adaptive games enhance strategy performance by sacrificing eco-evolutionary dynamic stability.