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Explicit intent enhanced contrastive learning with denoising networks for sequential recommendation
How artificial intelligence is transforming pathology
A virus based vaccine combined with IL12 gene therapy eradicates aggressive melanoma
Optimal tuning of PI based LF for three-phase SRF PLL synchronization system using pity beetle algorithm under grid abnormalities
Abstract The importance of grid synchronization in recent years is primarily driven by the widespread integration of renewable energy sources (RES). As nations transition toward carbon–neutral power systems, the variable nature of renewables and the increasing prevalence of non-linear loads introduce significant challenges for maintaining effective grid synchronization. At the core of this process, the synchronous reference frame phase lock loop (SRF PLL) has become a significant component of grid connected power electronic converters (PEC). Generally, PLL includes a proportional integral (PI) based loop filter (LF) that plays a critical role in ensuring precise phase angle and frequency alignment between the grid and PEC. Traditional PI controller tuning techniques like the symmetrical optimum (SO), optimum setting algorithm (OSA) and Ziegler-Nichol’s exhibit satisfactory performance under ideal grid conditions. However, their effectiveness diminishes in real-world scenarios characterized by grid disturbances. To overcome these limitations, this paper proposes a novel PI tuning approach based on the pity beetle algorithm (PBA) for the SRF PLL grid synchronization system. Inspired by the foraging character of the pityogenes chalcographus beetle, PBA optimizes the PI parameters of the LF, enhancing accurate synchronization and response speed. The proposed method is thoroughly assessed under challenging grid abnormalities such as harmonic distortion, amplitude fluctuations, phase jump and unbalanced phase differences. The SRF PLL with proposed PBA tuning for PI based LF is mathematically formulated and analyzed through numerical simulations using MATLAB tool. A comprehensive stability analysis is conducted through frequency response bode plots to validate the effectiveness of the tuning method for accurate grid synchronization. The results, encompassing phase margin (PM), accuracy, computational cost and adaptability derived from the suggested PBA tuned LF design for SRF PLL are compared with existing tuning methods.
Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization
Model tests of dynamic response of modified lateritic soil embankments under combined action of wetting and vibration
Abstract Modifying lateritic soils, which are widely distributed in humid and rainy regions around the world, for embankment construction is a practical necessity for highway and railway projects. These embankments are susceptible to infiltration of rainfall, wetting and vibration from earthquakes and traffic. Further study is required to investigate the dynamic response characteristics of these embankments under combined action of wetting and vibration. Two scaled-down physical models of embankments were built: one with unmodified lateritic soils, which are typical soils with high liquid limit in central-southern China, and the other with lateritic soils modified with lime at a content of 8%. A self-designed model test system was used to conduct model tests of both embankments under combined action of wetting and vibration. White noise excitation was employed to quantitatively compare the two types of embankments in terms of variations of dynamic properties, such as natural frequency and damping ratio, with wetting degrees. Three types of seismic waves—Chi_Chi, NCALIF and SFERN—were used to quantitatively compare the two types of embankments in terms of variations of dynamic response parameters, including PGA amplification effect, pore water pressure and earth pressure, with wetting degrees and acceleration amplitudes. The test results reveal significant differences in dynamic properties and responses of the two types of embankments. Compared to the unmodified embankment, the damping ratio and PGA amplification factor of the modified embankment are reduced by up to 53.5% and 37.5%, respectively, resulting in an effective mitigation of the combined action of wetting and vibration. Test values of natural frequency, damping ratio, PGA amplification factor, dynamic pore water pressure and dynamic earth pressure of both types of embankments are presented. The research findings provide a theoretical basis for highway and railway construction and for revision of technical specifications in regions with widespread lateritic soils.
Decoding dynamic brain networks in Parkinson’s disease with temporal attention
Abstract Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurological disorders. Conventional imaging analyses often overlook these subtle events due to computational demands. IMPACT (Integrative Multimodal Pipeline for Advanced Connectivity and Time-series) addresses this challenge by converting 3D/4D fMRI scans into time-series signals using a standardized brain atlas. This approach integrates regional signals, network patterns, and dynamic connectivity, and employs machine learning to detect subtle fluctuations. In Parkinson’s disease diagnosis across two independent cohorts (n=43 and n=40), it achieves high accuracy (area under the curve = 0.97-0.98), outperforming conventional methods. Analyses reveal transient connectivity disruptions that align with dopaminergic mechanisms, while interpretability highlights the critical time windows and regions driving classification. This reproducible, standardized pipeline is readily adaptable to other conditions where short-lived brain changes serve as key diagnostic markers.
Group personality, rather than acoustic noise, causes variation in group decision-making in guppy shoals
Abstract Group living has essential fitness benefits for many species. While numerous studies have explored how environmental conditions impact collective movement, their impact on decisions made in a social context—a central component of group-living—is poorly documented. In this study, we assess how acoustic noise impacts group decision-making, cohesion and activity in fish shoals, using Trinidadian guppies ( Poecilia reticulata ) as a model species. Movements within a radially symmetric five-armed maze were measured using high-resolution trajectory data from video-tracking software. The behaviour of groups with and without continuous acoustic white noise were measured over a four-day testing period in a repeated-measures design. We found no significant change in swimming speed or group cohesion with additional acoustic noise. However, there was evidence for fewer following events (moves into already occupied arms) in the noise treatment compared to the control, but this additional noise had no effect on leadership attempts (moves into empty arms). We found strong evidence for consistent, repeatable differences between groups in all behavioural parameters indicating strong personality variation at the group level. Rather than environmental factors, these results provide evidence that consistent group-level differences dominate variation in collective behaviour, including group decision-making, in fish shoals.
The application of computerized quadrato motor training in enhancing balance and executive performance in stroke patients
Relapse prediction using wearable data through convolutional autoencoders and clustering for patients with psychotic disorders
Abstract Relapse of psychotic disorders occurs commonly even after appropriate treatment. Digital phenotyping becomes essential to achieve remote monitoring for mental conditions. We applied a personalized approach using neural-network-based anomaly detection and clustering to predict relapse for patients with psychotic disorders. We used a dataset provided by e-Prevention grand challenge (SPGC), containing physiological signals for 10 patients monitored over 2.5 years (relapse events: 560 vs. non-relapse events: 2139). We created 2-dimensional multivariate time-series profiles containing activity and heart rate variability metrics, extracted latent features via convolutional autoencoders, and identified relapse clusters. Our model showed promising results compared to the 1st place of SPGC (area under precision-recall curve = 0.711 vs. 0.651, area under receiver operating curve = 0.633 vs. 0.647, harmonic mean = 0.672 vs. 0.649) and added to existing evidence of data collected during sleep being more informative in detecting relapse. Our study demonstrates the potential of unsupervised learning in identifying abnormal behavioral changes in patients with psychotic disorders using objective measures derived from granular, long-term biosignals collected by unobstructive wearables. It contributes to the first step towards determining relapse-related biomarkers that could improve predictions and enable timely interventions to enhance patients’ quality of life.
Fault-tolerant and mobility-aware loading via Markov chain in mobile cloud computing
Study on oscillation effect of wind power pile foundation on local scour
Abstract The pile-oscillation effect on foundation local scour cannot be neglected in the large-scale offshore wind turbine. To reveal the fluid dynamics and its influence on the bed shear stress of an oscillating pile foundation, the VOF two-phase flow model is used to study the effect of the transverse and vertical oscillation of pile foundations employed in offshore wind turbines. The changes in the flow field, horseshoe vortices, and bed shear stress are analyzed under different oscillation frequencies and amplitudes are monitored by two symmetry planes ahead of the pile and at pile side respectively. The results show that, at the longitudinal oscillation condition, the backflow in front of the pile is produced and is strengthened as increasing the frequency and amplitude of oscillation; the size of horseshoe vortex ahead of the pile, and the bed shear stress reach the maximum at the moment of T/2 (T is the oscillation cycle). At the transverse oscillation, horseshoe vortices are extended to the pile side, their sizes are increased as the oscillation frequency and amplitude increase, and the maximum size is generated at the moment of T/2; while the bed shear stress is the smallest at T/2, and the maximum is created at T. Both transverse and longitudinal oscillations increase the time-averaged bed shear stresses (TBSS), the longitudinal oscillation generates larger TBSS in the symmetry plane in front of the pile, conversely transverse oscillations generate larger TBSS in the side symmetry plane of the pile.