Search Results (10,051)

This study focuses on a hydraulic cylinder that is directly connected to a fixed-displacement hydraulic pump driven by an electric servo motor. This particular setup is referred to as a one-motor-one-pump motor-controlled hydraulic cylinder (MCC). This paper presents a new approach to address mode switching oscillation (MSO) in MCCs by incorporating system pressure control capabilities. It conducts a detailed investigation into the factors that contribute to MSO in standard MCCs and thoroughly evaluates the effectiveness of the proposed system in mitigating MSO. The simulation results demonstrate the successful suppression of MSO. In conclusion, the proposed MCC with system pressure control capabilities is validated and, furthermore, it shows great potential for practical applications involving small loads and rapid retraction. Full article

Phase noise is a consequence of the instability inherent in the operation of oscillators, making it impossible to entirely eliminate. For low-cost internet of things (IoT) devices, this type of noise can be particularly pronounced, posing a challenge in providing high-quality localization services. To tackle this issue, this paper introduces an improved localization algorithm that includes phase noise compensation. The proposed algorithm enhances the direction of arrival (DoA) estimation for each base station by employing the EM–MUSIC method, subsequently forming a non-convex optimization problem based on the mean square error (MSE) of the estimated DoA results. Finally, a closed-form solution is derived through rational assumptions and approximations. Results show that this algorithm effectively minimizes localization errors and achieves accuracy levels within the sub-meter range. Full article

In light of the fact that existing centrality indexes disregard the influence of dynamic characteristics and lack generalizability due to standard diversification, this study investigates dynamic survivability centrality, which enables quantification of oscillators’ capacity to impact the dynamic survivability of nonlinear oscillator systems. Taking an Erdős–Rényi random graph system consisting of Stuart–Landau oscillators as an illustrative example, the typical symmetry synchronization is considered as the key mission to be accomplished in light of the study and the dynamic survivability centrality value is found to be dependent on both the system size and connection density. Starting with a small scale system, the correctness of the theoretical results and the superiority in comparison to traditional indexes are verified. Further, we present the quantitative results by means of error analysis, distribution comparison of various indexes and relationship with system structure exploration, and give the position of the key oscillator. The results demonstrate a negligible error between the theoretical and numerical outcomes, and highlighting that the distribution of dynamic survivability centrality closely resembles the distribution of system state changes. The conclusions serve as evidence for the accuracy and validity of the proposed index. The findings provide an effective approach to protect systems to improve dynamic survivability. Full article

The pure pursuit (PP) method has been widely employed in automated guided vehicles (AGVs) to address path tracking challenges. However, the traditional pure pursuit method exhibits certain limitations in tracking performance. For instance, selecting a look-ahead point that is too close can lead to oscillations during tracking, while selecting one that is too far away can result in slow tracking and corner-cutting issues. To address these challenges, this paper proposes a multistep prediction pure pursuit method. First, the look-ahead distance calculation equation is adjusted by incorporating path curvature, allowing it to adaptively adjust according to road conditions. Next, to avoid oscillations caused by constant changes in the look-ahead distance, this paper adopts the prediction concept of model predictive control (MPC) to make multistep predictions for the pure pursuit method. The final input is derived from a linear weighted combination of the multistep prediction results. Simulation analyses and experiments demonstrate that the multistep predictive pure pursuit method significantly enhances the tracking performance of the traditional pure pursuit method. Full article

The analysis conducted herein has shown that the efficiency of smoke precipitation can be improved by additionally making smoke particles interact with ultrasonic (US) oscillations. Because the efficiency of US coagulation lowers when small particles assemble into agglomerates, the authors of this work have suggested studying how smoke particles interact with complex sound fields. The fields are formed by at least two US transducers which work at a similar frequency or on frequencies with small deviations. To form these fields, high-efficiency bending wave ultrasonic transducers have been developed and suggested. It has been shown that a complex ultrasonic field significantly enhances smoke precipitation. The field in question was constructed by simultaneously emitting 22 kHz US oscillations with a sound pressure level no lower than 140 dB at a distance of 1 m. The difference in US oscillations’ frequencies was no more than 300 Hz. Due to the effect of multi-frequency ultrasonic oscillations induced in the experimental smoke chamber, it was possible to provide a transmissivity value of 0.8 at a distance of 1 m from the transducers and 0.9 at a distance of 2 m. Thus, the uniform visibility improvement and complete suppression of incoming smoke was achieved. At the same time, the dual-frequency effect does not require an increase in ultrasonic energy for smoke due to the agglomeration of small particles under the influence of high-frequency ultrasonic vibrations and the further aggregation of the formed agglomerates by creating conditions for the additional rotational movement of the agglomerates due to low-frequency vibrations. Full article

Objective: This study aimed to explore longitudinal relationships between neurophysiological biomarkers and upper limb motor function recovery in stroke patients, focusing on electroencephalography (EEG) and transcranial magnetic stimulation (TMS) metrics. Methods: This longitudinal cohort study analyzed neurophysiological, clinical, and demographic data from 102 stroke patients enrolled in the DEFINE cohort. We investigated the associations between baseline and post-intervention changes in the EEG theta/alpha ratio (TAR) and TMS metrics with upper limb motor functionality, assessed using the outcomes of five tests: the Fugl-Meyer Assessment (FMA), Handgrip Strength Test (HST), Pinch Strength Test (PST), Finger Tapping Test (FTT), and Nine-Hole Peg Test (9HPT). Results: Our multivariate models identified that a higher baseline TAR in the lesioned hemisphere was consistently associated with poorer motor outcomes across all five assessments. Conversely, a higher improvement in the TAR was positively associated with improvements in FMA and 9HPT. Additionally, an increased TMS motor-evoked potential (MEP) amplitude in the non-lesioned hemisphere correlated with greater FMA-diff, while a lower TMS Short Intracortical Inhibition (SICI) in the non-lesioned hemisphere was linked to better PST improvements. These findings suggest the potential of the TAR and TMS metrics as biomarkers for predicting motor recovery in stroke patients. Conclusion: Our findings highlight the significance of the TAR in the lesioned hemisphere as a predictor of motor function recovery post-stroke and also a potential signature for compensatory oscillations. The observed relationships between the TAR and motor improvements, as well as the associations with TMS metrics, underscore the potential of these neurophysiological measures in guiding personalized rehabilitation strategies for stroke patients. Full article

To assess the viability of locations for wave energy farms and design effective coastal protection measures, knowledge of local wave regimes is required. The work described herein aims to develop a low-cost, self-powering wave-measuring device that comprises a floating buoy with a central moonpool. The relative motion of the water level in the moonpool to the buoy will pressurise and depressurise the air above the water column. The variation in air pressure may then be used to estimate the sea-state incident upon the buoy. Small-scale proof of concept tank testing was conducted at a 1:20 scale and at a larger 1:2.4 scale before a full-scale prototype was deployed at the Smartbay test site facility in Galway Bay, Ireland. A number of techniques by which full-scale sea states may be estimated from the pressure spectrum are explored. A successful technique, based on the average of multiple linear squared magnitude of the transfer functions obtained under different wave regimes is developed. The applicability of this technique is then confirmed using validation data obtained during the full-scale sea trials. While the technique has proven useful, investigation into potential seasonal bias has been conducted, and suggestions for further improvements to the technique, based on further calibration testing in real sea states, are proposed. Full article

The cosmological lepton asymmetry, i.e., an excess of leptons over antileptons, is still only loosely constrained, and might be much larger than its tiny baryonic counterpart. If this is the case, charge neutrality requires the lepton asymmetries to be confined in the neutrino sector. We recall the observational effects of neutrino asymmetries on the abundance of light elements produced during Big Bang Nucleosynthesis and on the pattern of cosmic microwave background anisotropies. We point to the necessity of solving the neutrino transport equations, taking into account the effect of flavour oscillation, to derive general and robust constraints on lepton asymmetries. We review the current bounds and briefly discuss prospects for next-generation CMB experiments. Full article

The high speeds seen in rapidly rotating pulsars after supernova explosions present a longstanding puzzle in astrophysics. Numerous theories have been suggested over the years to explain this sudden "kick" imparted to the neutron star, yet each comes with its own set of challenges and limitations. Key explanations for pulsar kicks include hydrodynamic instabilities in supernovae, anisotropic neutrino emission, asymmetries in the magnetic field, binary system disruption, and physics beyond the Standard Model. Unraveling the origins of pulsar kicks not only enhances our understanding of supernova mechanisms but also opens up possibilities for exploring new physics. In this brief review, we will introduce pulsar kicks, examine the leading hypotheses, and explore future directions for this intriguing phenomenon. Full article

This article reports a 110.2 MHz ultra-low-power phase-locked loop (PLL) for MEMS timing/frequency reference oscillator applications. It utilizes a 6.89 MHz MEMS-based oscillator as an input reference. An ultra-low-power, high-resolution phase-frequency detector (PFD) is utilized to achieve low-noise performance. Eliminating the reset feedback path used in conventional PFDs leads to dead/blind zone-free phase characteristics, which are crucial for low-noise applications within a wide operating frequency range. The PFD operates up to 2.5 GHz and achieves a linear resolution of 100 ps input time difference ($\Delta t_{in}$), without the need for any additional calibration circuits. The linearity of the proposed PFD is tested over a phase difference corresponding to aa $\Delta t_{in}$ ranging from 100 ps to 50 ns. At a 1 V supply voltage, it shows an error of <±1.6% with a resolution of 100 ps and a frequency-normalized power consumption ($P_n$) of 0.106 pW/Hz. The PLL is designed and fabricated using a TSMC 65 nm CMOS process instrument and interfaced with the MEMS-based oscillator. The system reports phase noises of −106.21 dBc/Hz and −135.36 dBc/Hz at 1 kHz and 1 MHz offsets, respectively. It consumes 6.709 $\mathsf{\mu }$W at a 1 V supply and occupies an active CMOS area of 0.1095 mm². Full article

This paper examines oscillations governed by the generic nonlinear differential equation ${u^{″}=\omega }_{p0}^2\left(1-u\mp {\displaystyle \frac{2{\beta }^2}{u^{\gamma }}}\right),$ where ${\omega }_{p0},\beta$ and $\gamma$ are positive constants. The aforementioned differential equation is of particular importance, as it describes electron plasma oscillations influenced by temperature effects and large oscillation amplitudes. Since no analytical solution exists for the oscillation period in terms of ${\omega }_{p0},\beta ,\gamma$ and the oscillation amplitude, accurate approximations are derived. A modified He’s approach is used to account for the non-symmetrical oscillation around the equilibrium position. The motion is divided into two parts: $u_{min}\le u<u_{eq}$ and $u_{eq}<u\le u_{max}$, where $u_{min}$ and $u_{max}$ are the minimum and maximum values of $u$, and $u_{eq}$ is its equilibrium value. The time intervals for each part are calculated and summed to find the oscillation period. The proposed method shows remarkable accuracy compared to numerical results. The most significant result of this paper is that He’s approach can be readily extended to strongly non-symmetrical nonlinear oscillations. It is also demonstrated that the same approach can be extended to any case where each segment of the function $f\left(u\right)$ in the differential equation $u^{″}+f\left(u\right)=0$ (for $u_{min}\le u<u_{eq}$ and for $u_{eq}<u\le u_{max}$) can be approximated by a fifth-degree polynomial containing only odd powers. Full article

This study evaluates machine learning models for stock market prediction in the European stock market EU50, with emphasis on the integration of key technical indicators. Advanced techniques, such as ANNs, CNNs and LSTMs, are applied to analyze a large EU50 dataset. Key indicators, such as the simple moving average (SMA), exponential moving average (EMA), moving average convergence/divergence (MACD), stochastic oscillator, relative strength index (RSI) and accumulation/distribution (A/D), were employed to improve the model’s responsiveness to market trends and momentum shifts. The results show that CNN models can effectively capture localized price patterns, while LSTM models excel in identifying long-term dependencies, which is beneficial for understanding market volatility. ANN models provide reliable benchmark predictions. Among the models, CNN with RSI obtained the best results, with an RMSE of 0.0263, an MAE of 0.0186 and an R² of 0.9825, demonstrating high accuracy in price prediction. The integration of indicators such as SMA and EMA improves trend detection, while MACD and RSI increase the sensitivity to momentum, which is essential for identifying buy and sell signals. This research demonstrates the potential of machine learning models for refined stock prediction and informs data-driven investment strategies, with CNN and LSTM models being particularly well suited for dynamic price prediction. Full article

Wave energy, as a renewable energy source, plays a significant role in sustainable energy development. This study focuses on a dual-chamber offshore oscillating water column (OWC) wave energy device and performs numerical simulations to analyze the influence of chamber geometry on hydrodynamic characteristics and wave energy conversion efficiency. Unlike existing studies primarily focused on single-chamber configurations, the hydrodynamic characteristics of dual-chamber OWCs are relatively underexplored, especially regarding the impact of critical design parameters on performance. In this study, STAR-CCM+ V2302 software (Version 2410, Siemens Digital Industrial Software, Plano, TX, USA) is utilized to systematically evaluate the effects of key design parameters (including turbine configuration, mid-wall draught depth, and wall angles) on the hydrodynamic performance, wave energy capture efficiency, and wave reflection and loading characteristics of the device. The findings aim to provide a reference framework for the optimal design of dual-chamber OWC systems. The results show that the dual-chamber, dual-turbine (2C2T) configuration offers a 31.32% improvement in efficiency compared to the single-chamber, single-turbine (1C1T) configuration at low wave frequencies. In terms of reducing wave reflection and transmission, the 2C2T configuration outperforms the dual-chamber, single-turbine configuration. When the wall angle increases from 0° to 40°, the total efficiency increases by 166.37%, and the horizontal load decreases by 20.05%. Additionally, optimizing the mid-wall draught depth results in a 9.6% improvement in efficiency and a reduction of vertical load by 11.69%. Full article

In the past 42 years from 1980 to 2021, 103 regional strong cooling events (RSCEs) occurred in winter in Northeast China, and the frequency has increased significantly in the past 10 years, averaging 2.45 per year. The longest (shortest) duration is 10 (2) days. The minimum temperature series in 60 events exists in 10–20 d of significant low-frequency (LF) periods. The key LF circulation systems affecting RSCEs include the Lake Balkhash–Baikal ridge, the East Asian trough (EAT), the robust Siberian high (SH) and the weaker (stronger) East Asian temperate (subtropical) jet, with the related anomaly centers moving from northwest to southeast and developing into a nearly north–south orientation. The LF wave energy of the northern branch from the Atlantic Ocean disperses to Northeast China, which excites the downstream disturbance wave train. The corresponding LF positive vorticity enhances and moves eastward, leading to the formation of deep EAT. The enhanced subsidence motion behind the EAT leads to SH strengthening. The cold advection related to the northeast cold vortex is the main thermal factor causing the local temperature to decrease. The Scandinavian Peninsula is the primary cold air source, and the Laptev Sea is the secondary one, with cold air from the former along northwest path via the West Siberian Plain and Lake Baikal, and from the latter along the northern path via the Central Siberian Plateau, both converging towards Northeast China. Full article