Dynamic Frequency Research Articles

Intelligent Tunable Wave-Absorbing CNTs/VO2/ANF Composite Aerogels Based on Temperature-Driving.

The development of new electromagnetic absorbing materials is the main strategy to address electromagnetic radiation. Once traditional electromagnetic wave-absorbing materials are prepared, it is difficult to dynamically change their electromagnetic wave-absorbing performance. Facing the complexity of the information age and the rapid development of modern radar, it is significant to develop intelligent modulation of electromagnetic wave-absorbing materials. Here, CNTs/VO2/ANF composite aerogels with dynamic frequency tunability and switchable absorption on/off were synthesized. Based on the phase change behavior of VO2, the degree of polarization and interfacial effects of multiple heterogeneous interfaces between VO2 and CNTs and aramid nanofibers (ANFs) were modulated at different temperatures. With the increase in temperature (from 25 to 200 °C), the maximum absorption frequency of the frequency tunable aerogel is modulated from 12.24 to 8.56 GHz in the X-band, and the absorption intensity remains stable. The maximum effective switching bandwidth (ΔEAB) of the wave-absorbing switchable aerogel is 3.70 GHz. This study provides insights into intelligent electromagnetic wave absorption performance and paves the way for temperature-driven application of intelligent modulation of electromagnetic absorbers.

Dynamics analysis of rotating soft core sandwich beams using the absolute nodal coordinates formulation with zigzag theory

With the widespread use of rotating sandwich structures in engineering applications, it is significant to understand their vibration characteristics and dynamic behavior. Since the absolute nodal coordinates formulation (ANCF) is one of the most effective methods for solving rotational dynamics, it is feasible to use the ANCF with zigzag theory (ANCF-ZZ) to analyze the dynamics of these structures. Therefore, this study builds upon existing research to further refine the theory of ANCF-ZZ and proposes diverse models for determining the element complexity required in modeling rotating sandwich structures. In order to better solve the dynamics of rotating sandwich beams, the ANCF-ZZ is described in a floating coordinate system by coordinate transformation. Subsequently, the dimensionless frequency and dynamic responses of rotating sandwich beams are analyzed, and the influence of core-to-face elastic modulus ratio and thickness ratio on them are investigated. The results show that the segmental description of the cross-section based on the zigzag theory is more influential than the warping description by higher-order interpolating polynomials. Consequently, reducing the order of original high-order ANCF-ZZ beam elements can improve computational efficiency without affecting accuracy. In addition, the ANCF-ZZ captures the dynamic stiffening effect and frequency veering phenomena, which are essential characteristics in rotational frequency analysis. Compared with commercial finite element software, the ANCF-ZZ not only can accurately analyze the dynamic stiffening effect of rotating sandwich beams but also can obtain the deformation response at non-constant rotational speeds and higher rotational speeds using a few elements, which is valuable for engineering applications.

Thermal Safe Power Constrained Dynamic Mapping for Heterogeneous Multicore System

Heterogeneous multicore system could provide high flexibility for applications through integrating different types of cores. As the number of cores increases, more and more transistors are integrated which could lead to the rise of chip temperature, thus have a negative impact on the system performance. At present, the typical method to tackle this problem is dynamic voltage and frequency scaling (DVFS) which reduces the voltage and frequency to achieve cooling. However, DVFS will make the heterogeneous multicore system unable to take full advantage of its performance. This paper proposes a dynamic mapping method called TspDM which maximizes the system performance target under the premise of satisfying the temperature safety power. TspDM exploits the runtime performance counters of running threads to dynamically adjust thread mapping. Specifically, a lightweight Artificial Neural Network (ANN) model is proposed to obtain the thread-to-core type mapping when a remapping process is activated. Subsequently, TspDM determines the specific core locations of threads according to the number of threads mapped to a certain core type and the thermal safety power computation. The experimental results show that the proposed method is 21% better than that of PCMig while ensuring the thermal safety of heterogeneous platform. In addition, TspDM outperforms recent performance constrained and power constrained literature in terms of system throughput.

Nonlinear vibration of five-layered functionally graded piezoelectric semiconductor nano-plate on Pasternak foundation

The vibration character of piezoelectric semiconductor nano-plate is important for understanding the multi-fields coupling and optimizing the serving behavior. In this article, the nonlinear vibration of five-layered functionally graded piezoelectric semiconductor nano-plate based on Pasternak foundation is studied, and the nonlocal theory is used to analyze the size-dependent dynamic response of nano-plate. Combining the Von karman’s nonlinear deformation theory and the constitutive of piezoelectric semiconductor layers, Hamilton’s principle is introduced to derive the nonlinear governing equations. To solve the nonlinear governing equations, the updated iteration method for this problem is proposed. Through numerical examples, it is found that the initial electron concentration in piezoelectric semiconductor layer, the nonlocal parameter, the functionally graded index in the plate, the elastic modulus of Pasternak foundation and the geometrical parameters can be designed to effectively tune the dynamic nonlinear frequency and damping of layered functionally graded piezoelectric semiconductor nanoplate. The interaction of these parameters is also analyzed in detail. Comparison with existing numerical results is also presented. A new way is provided to tune the nonlinear vibration of multi-layered piezoelectric semiconductor nano-plate.

An enhanced meta-heuristic algorithm used for energy conscious priority-based task scheduling problems in heterogeneous multiprocessor systems

The Task Scheduling Problem (TSP) in Multiprocessor Systems (MPS) is an emerging research area in heterogeneous distributed computing environments. Managing complex tasks and achieving optimal efficiency while scheduling tasks in MPS presents challenges. Although adding more processors to a single system greatly increases its processing power, the energy these processors produce is the main drawback. Here, we employed a multi-objective optimization strategy to reduce the makespan and Energy Consumption (EC). To reduce processor EC, we considered an effective Dynamic Voltage and Frequency Scaling (DVFS) technique. Three distinct energy sources are considered, originating from the processors' communication, idle, and active states. The scheduling sequence of tasks and the assignment of tasks to processors are two vital aspects of TSP. Here, the tasks are arranged based on priority using the Upward Rank technique. To minimize the makespan and EC while allocating tasks to processors, we use the population-based metaheuristic method called Enhanced Honey Badger Optimisation (EHBO). We proposed three improvements to the HBO algorithm in EHBO. Initially, we addressed opposite learning-based population initialization to exclude the least suitable candidates and generate a candidate scheduling population that adheres to task precedence. Subsequently, the levy-flight technique is employed to improve the local and global search and preserve their ideal healthy balance. Finally, using dynamic values rather than constant value improves the ability to obtain maximum food. Several experiments are conducted on random task graphs and real-life data sets. Additionally, the results are compared with other upgraded meta-heuristic algorithms, demonstrating the superiority of EHBO.

Energy Transition, fossil Fuels, and green Innovations: Paving the way to achieving sustainable development Goals in the United States

The United States, as the world's second-largest polluter, emitted a staggering 4.7 billion metric tonnes of carbon dioxide in 2020. During the Leaders’ Climate Summit, the US president articulated precise targets for combating climate change, notably a 50 to 52 percent reduction in net CO2 emissions from 2005 levels by 2030. Consequently, it becomes imperative to identify the pivotal factors that are driving this intensified dedication to achieving the Sustainable Development Goals (SDGs). Hence, it is vibrant to determine the basic causes propelling the intensified interest in meeting SDGs 7 and 13. From this perspective, this study explores the dynamic link between energy transition, fossil fuel energy, green innovation, and economic complexity index on CO2 emissions and ecological footprint in the United States from 1980 to 2020. The dynamic Autoregressive-Distributed Lag (ARDL) simulations and Frequency Domain Causality (FDC) techniques are applied for long-medium and short-run causal association among the variables. Our empirical evidence shows that energy transition, fossil fuel energy, and economic complexity increase CO2 emissions and ecological footprint. On the other hand, green innovation reduces CO2 emissions and ecological impact only in the long term. The pragmatic outcomes suggest that authorities should inhibit Fossil Fuel Energy, concentrate on energy transitions, and include more renewable sources in the US energy mix. The findings would assist the United States in meeting SDGs 7 and 13.

Characterization of acid-soluble collagen (ASC) derived from walleye pollock and silver carp skin and comparison them with the collagen from pig and duck skin

The acid-soluble collagens (ASC) extracted from the skins of walleye pollock and silver carp were compared with ASCs from skins of duck and pig in physicochemical properties. The dry weight extraction rates of ASCs from walleye pollock and silver carp were 14.10 % and 10.30 %, which were significantly higher than those of pig and duck (4.53 % and 3.14 %). It was found that the ASCs from skins of pig, walleye pollock and silver carp were all type I collagen with intact triple helix structure, while ASC from duck skin was a mixture of type I and type II collagen.The PI of the four ASCs was in the weakly acidic range (5.49–6.84), but ASCs from two fish skins were less thermally stable than that from pig and duck. The dynamic frequency scanning showed that collagen from porcine skin always maintained elastic behavior, while the other three ASCs changed from viscous behavior to elastic behavior with the increasing of frequency. The collagen from two fish skins had a less dense microstructure. The high extraction rate proved that two fish skins were high-quality raw materials for collagen, and the differences in physicochemical properties allowed fish skin collagen to have different applications than terrestrial animal collagen.

KRAS mutations allelic frequency dynamics using plasma extracellular vesicles: Association with survival outcomes in localized pancreatic adenocarcinoma.

KRAS mutations allelic frequency dynamics using plasma extracellular vesicles: Association with survival outcomes in localized pancreatic adenocarcinoma.

Estimating the region of attraction of wind integrated power systems based on improved expanding interior algorithm

AbstractThis paper proposes an improved expanding interior algorithm (EIA) to estimate the region of attraction (ROA) of power systems with wind power generation based on sum of squares (SOS) programming. An ordinary differential equation (ODE) model is derived for the doubly‐fed induction generator‐based wind turbine (DFIGWT), which is named as an enhanced synchronous‐generator‐mimicking (ESGM) model. The ESGM model bridges the gap between the requirement of an ODE model in ROA estimation and the conventional differential‐algebraic equation (DAE) model of the DFIGWT system. The ESGM model is able to accurately reflect the low frequency dynamics of the DFIGWT. Moreover, an improved EIA is designed to estimate the ROA based on SOS programming, which has higher efficiency than the existing ROA estimation algorithms based on SOS programming. It is able to adaptively search for the Lyapunov function and obtain an optimal estimation of the ROA in an iterative process. The accuracy and efficiency of this algorithm are verified in three test systems composed of DFIGWTs and synchronous generators (SGs). The morphological changes in the ROA of the test systems caused by the penetration of DFIGWT are examined.

Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers, and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control. This causes a deterioration in the performance of the primary frequency control and, in some cases, may even result in frequency instability within the power system. Therefore, a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power. The Padé approximation was used to model the time delays, and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays. The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored. In addition, a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics. Finally, a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform. The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

Energy-aware task scheduling for streaming applications on NoC-based MPSoCs

Streaming applications are being extensively run on portable embedded systems, which are battery-operated and with limited memory. Thus, minimizing the total energy consumption of such a system is important. We investigate the problem of offline scheduling for streaming applications composed of non-preemptible periodic dependent tasks on homogeneous Network-on-Chip (NoC)-based Multiprocessor System-on-Chip (MPSoCs) such that their total energy consumption is minimized under memory constraints. We propose a novel unified approach that integrates task-level software pipelining with Dynamic Voltage and Frequency Scaling (DVFS) to solve the problem. Our approach is supported by a set of novel techniques, which include constructing an initial schedule based on a list scheduling where the priority of each task is its approximate successor-tree-consistent deadline such that the workload across all the processors is balanced, a retiming heuristic to transform intra-period dependencies into inter-period dependencies for enhancing parallelism, assigning an optimal discrete frequency for each task and each message using a Non-Linear Programming (NLP)-based algorithm and an Integer-Linear Programming (ILP)-based algorithm, and an incremental approach to reduce the memory usage of the retimed schedule in case of memory size violations. Using a set of real and synthetic benchmarks, we have implemented and compared our unified approach with two state-of-the-art approaches, RDAG+GeneS (Wang et al., 2011) , and JCCTS (Wang et al., 2013a). Experimental results show that our approach’s maximum, average, and minimum improvements over RDAG+GeneS (Wang et al., 2011) are 31.72%, 14.05%, and 7.00%, respectively. Our approach’s maximum, average, and minimum improvement over JCCTS (Wang et al., 2013a) are 35.58%, 17.04%, and 8.21%, respectively.

Energy Efficient Heuristics to Schedule Task Graphs on Heterogeneous Voltage-Frequency Islands

For energy and cost-efficient computing, many desktops and embedded computing devices these days use voltage frequency islands (VFIs) based processors. An island in VFIs consists of multiple homogeneous cores; however, multiple islands are generally heterogeneous in nature. In contrary to architectures (non-VFI) with per-core dynamic voltage frequency scaling (DVFS), in VFI, all the cores in an island run on the same voltage/frequency at the same time. The energy-aware scheduling of task graphs on VFI architectures is challenging and different from non-VFI architectures in which task-based DVFS is possible. However, in VFI scheduling, the time slot for which an island runs on a particular voltage will be decided. In this paper, we analyse 20 different scheduling heuristics for VFI architectures by varying the size of this time slot based on the workload properties and also by varying the voltage/frequency of the time slots. We also propose a heuristic OptSlotVFI to utilize all the slots optimally. The results show that the VFI scheduling heuristics are able to generate schedules which improve energy consumption up to 25% with an equivalent or shorter schedule length than the state-of-the-art approaches.

Sexual violence in the workplace and associated health outcomes: a nationwide, cross-sectional analysis of women in Iceland

Workplace sexual violence against women is a pressing global issue with scarce knowledge on its health implications. Existing research is largely limited to specific occupations, which calls for comprehensive, population-based studies. This study aimed to examine the associations between self-labelled workplace sexual violence and a variety of health outcomes in a nationally representative sample of Icelandic women aged 18-69 years. Participants in this cross-sectional study were women in the Stress-And-Gene-Analysis (SAGA) cohort who answered the question regarding workplace sexual violence, defined in our study as encompassing all work sectors, academic settings, and other school environments. Eligible participants were women, aged 18-69 years, residing in Iceland, who spoke Icelandic and were listed in the Icelandic Population Register or had a contact number registered with the online 1819 service. Poisson and binomial regressions were used to assess the associations between workplace sexual violence and validated measures of current mental and physical health outcomes (eg, probable depression, general anxiety, and severe sleep problems). Multiple imputation was performed to account for missing values in the dataset. The study was conducted from March 1, 2018, to July 1, 2019. Of the 113 814 women deemed eligible for study inclusion, 104 197 were invited to take part in the online survey. Of those invited, 30 403 women completed the survey and were included in the SAGA cohort. Among these participants, 15 812 provided answers to the question regarding exposure to workplace sexual harassment or violence. Exposure to sexual violence was associated with an increased prevalence of probable depression (prevalence ratio [PR] 1·50 [95% CI 1·41-1·60]), general anxiety (PR 1·49 [1·40-1·59]), social phobia (PR 1·62 [1·48-1·78]), self-harm (PR 1·86 [1·53-2·28]), suicidal ideation (PR 1·68 [1·44-1·68]), suicide attempts (PR 1·99 [1·62-2·44]), binge drinking (PR 1·10 [1·01-1·20]), sleep problems (PR 1·41 [1·48-1·91]), physical symptoms (PR 1·59 [1·48-1·70]), and sick leave (PR 1·20 [1·12-1·28]). The prevalence of the health outcomes among those exposed show age-related differences: younger women report anxiety or depression more frequently, while older women report sleep problems after experiencing workplace sexual violence. In this cross-sectional study self-reported experiences of sexual violence in the workplace were associated with several self-reported health outcomes. The findings suggest a need for targeted interventions to promote workplace safety and to mitigate adverse health implications among people who have experienced workplace sexual violence. Future research should explore factors such as the frequency, duration, and relationship dynamics of workplace sexual violence, as well as the effect on different genders and sexual orientations, to deepen our understanding of these experiences and inform effective prevention strategies. Reykjavík Energy Research Fund, The Icelandic Gender Equality Fund, European Research Council, and Icelandic Center for Research.

Novel Fuzzy Logic Controls to Enhance Dynamic Frequency Control and Pitch Angle Regulation in Variable-Speed Wind Turbines

This study introduced a novel control approach based on fuzzy logic control (FLC) to enhance the frequency regulation capacity of variable-speed wind turbines (VSWTs). The proposed method integrates FLC within droop and inertia control loops. Real-time measurements of the system frequency and the rate of change of frequency (ROCOF) serve as inputs to the FLC, enabling the method to improve the frequency response by VSWTs. In addition, the method employs FLC for pitch angle frequency control, optimizing reserve power for frequency regulation under varying wind speed levels. The innovative aspect of this study lies in the simultaneous application of FLC to pitch angle frequency control and droop/inertia control, leading to the enhanced frequency regulation capability of VSWTs and smoother operation across a range of wind speeds. Compared with traditional methods, the proposed approach provides a comprehensive and effective solution to the challenges associated with frequency regulation in VSWTs. Through simulations across different wind speed scenarios, the proposed control method demonstrated the best performance among various mature methods, highlighting the efficacy of the proposed method on the frequency regulation of VSWTs under different wind speeds. This study’s findings highlight the potential of the proposed FLC-based method to optimize frequency regulation and contribute to more reliable and efficient wind energy systems.

Design of hyperbolic quasi-zero stiffness metastructures coupled with nonlinear stiffness for low-frequency vibration isolation

Quasi-zero stiffness (QZS) metastructures with simple structures exhibit a high low-frequency vibration isolation performance, but the bearing capacity and working regions are limited due to the linear positive stiffness elements. In this study, a novel hyperbolic QZS metastructure coupled with nonlinear stiffness is designed by combining a pair of cosine-shaped beams and arc-shaped beams for low-frequency vibration isolation. Finite element models (FEM) and experimental analysis are utilized to examine the static characteristics of the metastructure, revealing a wide QZS region and significant load-bearing capacity. The metastructure can achieve effective vibration isolation properties through reasonably designing the unit cells. The influence of geometrical parameters on the QZS region is investigated to optimize and realize desirable QZS features. The dynamic equation and response of the vibration isolation system are determined using the harmonic balance method. Moreover, the corresponding displacement transmissibility is confirmed by numerical simulation. The results of the dynamic sweep frequency experiment further verify the validity of the theoretical analysis model. The hyperbolic QZS metastructure system possesses good vibration isolation performance due to the introduction and compensation of a nonlinear positive stiffness arc beam element. The proposed hyperbolic QZS metastructure provides a significant route for the stiffness compensation of metastructures.

Integrated Ultra‐Wideband Dynamic Microwave Frequency Identification System in Lithium Niobate on Insulator

AbstractThe capability to identify the frequency of unknown microwave signals with an ultra‐wide measurement bandwidth is highly desirable in radar astronomy, satellite communication, and 6G networks. Compared to electronic solutions, the integrated photonic technology‐enabled dynamic instantaneous frequency measurement (DIFM) approach is attractive as it offers unique advantages, such as ultra‐wide frequency measurement bandwidth, high flexibility, and immunity to electromagnetic interference. However, so far the bandwidth of the reported DIFM systems based on integrated photonic technology is limited to below 30 GHz due to the finite bandwidth of electro‐optical modulators (EOMs), limiting their applications, particularly in the field of millimeter wave technology (30–300 GHz). Here, the first integrated dynamic microwave instantaneous frequency measurement system with a record‐breaking operation bandwidth (ranging from 5 to 65 GHz) and low root‐mean‐square (RMS) error (≈300 MHz) is presented on the lithium niobate on insulator (LNOI) integrated photonic platform. This demonstration paves the way for high‐performance millimeter wave photonic integrated devices using the LNOI platform.

Style Generative Adversarial Network Combined with Dynamic Fundamental Frequency Difference Compensation: A Practical and Efficient Method for Emotional Voice Conversion

This paper explores a novel emotional voice conversion (EVC) method based on the style generative adversarial network combined with dynamic fundamental frequency difference compensation. On the one hand, in terms of spectrum mapping, based on the method of EVC using star generative adversarial network, we propose to replace one-hot vectors with the emotion style features extracted from spectrum to represent emotional information. It enables the conversion not only to fully learn emotion style from the target speech, but also to transfer unseen emotion styles to a new utterance, that is, one-shot EVC. On the other hand, given that the traditional logarithm Gaussian normalization transformation and its some variants for prosody transfer are not enough to reflect the fine-grained fundamental frequency distribution difference between the different emotional speech, we propose the improved strategy of dynamic fundamental frequency difference compensation. The experimental results show that our proposed method can accomplish high quality one-shot EVC, significantly outperforming the baseline in terms of speech quality and emotional saturation in both objective and subjective evaluations.

From home to office: dynamics of remote work frequency, boundary crossing and employee well-being

PurposeTo examine the impact of using work-related information and communication technology (ICT) during off-job hours on employees' emotional exhaustion and to elucidate the role of psychological detachment (PD) and positive work reflection (PWR). Additionally, the study investigated the influence of the frequency of remote work on this relationship.Design/methodology/approachStructural equation modeling was conducted using a three-wave online survey with 507 full-time employees consisting of 170 non-remote workers, 75, 77, 63, 61, and 61 remote workers for one to five days weekly, respectively.FindingsWork-related ICT use during off-job hours inhibited PD and encouraged PWR, exacerbating emotional exhaustion. Furthermore, remote work frequency promotes boundary crossing and moderates the relationship between PWR and emotional exhaustion.Originality/valueThis study contributes to the literature by highlighting the complex interplay between boundary crossing, coping strategies, and emotional exhaustion in remote work. It highlights the importance of fostering PD and minimizing boundary crossing to promote employees’ well-being in increasingly flexible work environments.

Frequency-constrained scheduling based on synchronous generators’ dynamic response in low inertia systems

Ensuring safe control over post-fault frequency dynamics is a complex task due to the future decline of inertial response and governor response in low-carbon power networks. This paper proposes a novel system scheduling model which incorporates a detailed description of the inertial and governor’s response of conventional generators as well as the system-level frequency dynamics. The proposed methodology is able to consider the typical overshoot of the governor’s response to optimally allocate enough headroom among generators. In addition, a set of constraints on the frequency deviation and on its rate of change allows to optimize the energy production whilst maintaining the security of the system. Furthermore, the paper develops a constraint on the rise time of the governor’s response. Hence, the proposed methodology allows to enforce specific dynamics concerning the governor’s response. The proposed model is applied to analyze a 2030 GB low-carbon scenario. Results demonstrate the value of the proposed methodology e.g. as reduction of system operational cost and curtailment of renewables. Results also indicate value of well formulating the post-fault rate of change of frequency and the impact of limitations to the dynamic response of conventional generators.

Interpersonal dynamics of vocal fundamental frequency in couples: Depressive symptoms, anxiety symptoms, and relationship distress

Given the bidirectional association between psychopathology and relationship distress, an in-depth understanding of couples' interaction processes that contribute to psychopathology is needed. This study examined the interpersonal dynamics of vocally-encoded emotional arousal (fundamental frequency, f0) during couple conversations and their associations with depressive symptoms, anxiety symptoms, and relationship distress. Data from eight samples were pooled (N = 404 couples) to examine (a) overall trajectories of f0 across the interaction and (b) moment-by-moment intraindividual changes in and interpersonal reactivity to partners' f0. Multilevel growth models and repeated-measures actor-partner interdependence models demonstrated that individuals with more severe depression showed more synchronizing reactivity to their partners' f0 on a moment-by-moment basis, and their overall baseline level of f0 was lower. More severe relationship distress was associated with more steeply increasing trajectories of f0 and with greater synchronizing reactivity to partners' f0. Relative differences in depressive symptoms between the two members of a couple were associated with interpersonal dynamics of f0 as well. There were no associations with anxiety symptoms. Thus, depressive symptoms were associated with characteristic interpersonal dynamics of vocally-encoded emotional arousal; yet, most consistent associations emerged for relationship distress, which future studies on individual psychopathology should take into account.