Objective.Closed-loop responsive neurostimulators, such as the NeuroPace responsive neurostimulation (RNS) system, continuously monitor brain activity and deliver electrical stimulation in response to abnormal electrographic activity in patients with drug-resistant epilepsy. Practical technical constraints limit the temporal resolution of these devices, reducing the quality of EEG recordings.Approach.In this work, we introduce a novel technique to convert high-resolution intracranial electroencephalography (iEEG) obtained from inpatient monitoring into the same format, parameters, and resolution produced by the RNS system, allowing direct comparison of iEEG with RNS system data. We validated this technique using data from patients who had both iEEG and RNS. Electrodes from the iEEG and RNS system were co-registered onto the same 3D coordinate grid, and vector math was applied to determine the iEEG electrodes closest to the operational RNS electrodes.Main results.Through spectral analysis, we derived a transfer function that accounts for all filtering and data processing produced by the RNS system. Comparison of the recorded data using visual and spectral analysis from iEEG and RNS confirmed that EEG characteristics were correctly transformed by the filtering function, allowing analysis of how iEEG signals would appear within the RNS system. We demonstrate two examples from the extreme edges of the spectra, showing how DC shifts and high frequency oscillations would be transformed by the RNS. We provide a tutorial to tune this method to local device parameters, a process that can be applied to other devices as well.Significance.This tool allows researchers and clinicians to extract EEG biomarkers from high-resolution iEEG and determine if/how they can be detected in lower-resolution RNS. This provides an opportunity to develop patient-specific seizure detection parameters and investigate the long-term effects of neurostimulation therapy.

Abstract To realize high-resolution electric field visualization and insulation assessment in direct bonding copper (DBC) substrates, this work systematically compares the electroluminescence and discharge luminescence characteristics of ZnS:Cu under square wave excitation and elucidates their respective mechanisms. First, the differences in temporal resolution, spectral response and emission color between electroluminescence and discharge luminescence are identified through temporal resolution tests, integral spectral analysis, and RGB spatial color analysis. Subsequently, barrier experiments conducted under the needle–plate electrode reveals that the discharge luminescence is jointly excited by the ultraviolet radiation and charges generated during the discharge. Moreover, the emission color exhibits a blue shift with increasing discharge intensity, providing insights for the quantification of discharge intensity. Finally, in combination with the carrier motion model, the dynamic response mechanism and physical process of ZnS:Cu electroluminescence under square wave excitation are clarified. This work provides a new perspective for insulation assessment in power modules.

Impact of interoception and multisensory integration on functional and physical activities in aging.

Ultrafast magnetization dynamics represents a forefront area in modern spintronics and magnetic materials research, addressing the response and evolution of magnetic moments in magnetic systems over femtosecond to nanosecond timescales. To elucidate such ultrafast magnetic processes, a variety of time-resolved experimental techniques have been developed. Among them, synchrotron-based X-ray ferromagnetic resonance (XFMR) combines microwave-driven ferromagnetic resonance (FMR) with X-ray magnetic circular dichroism (XMCD) detection, enabling element-, valence-, and lattice space- resolved measurements of magnetization precession on the picosecond timescale and providing direct access to both the amplitude and phase of the dynamic magnetic moment. This work developed a picosecond time-resolved XFMR platform at the BL07U vector magnet beamline of the Shanghai Synchrotron Radiation Facility (SSRF). The system employs a lock-in modulation detection scheme precisely synchronized with the storage-ring master clock, realizing stable excitation and detection of spin precession in magnetic materials up to 6 GHz, with the background noise effectively suppressed to 30 fA, and an overall phase time resolution better than 10 ps. The successful implementation of this technique establishes a state-of-the-art XFMR capability in China, achieving internationally competitive performance in both temporal resolution and detection sensitivity. This development provides a powerful experimental foundation for future investigations of spin current and orbital current detection, as well as ferrimagnetic and antiferromagnetic dynamics.

Monitoring gene activity at high spatial and temporal resolution is key to understanding the regulation of developmental programs. It allows researchers to uncover developmental trajectories in complex organs or tissues and to determine the expression of genes in rare cell or tissue types, such as the cells of the plant female reproductive lineages (germline), which are embedded within the sporophytic tissues of the flower. Investigations into plant germlines are of scientific interest in order to gain an understanding of transcriptional processes governing reproduction. Moreover, in general terms, plant germlines are well suited as models for investigating gene regulatory programs underlying organogenesis, as they are typically composed of only a small number of highly specialized cell types. In recent years, a number of transcriptome analyses have uncovered regulatory programs underlying major steps of germline development during both sexual and asexual reproduction through seeds (apomixis). Apomixis is of great interest, as it leads to a formation of clonal embryos by omission or alteration of meiosis by the cell specified as first cell of the female germline combined with parthenogenesis (absence of fertilization of the egg cell). To overcome the long-faced challenge of the inaccessibility of the cells for cell type-specific investigations, the establishment of laser-assisted microdissection (LAM) has been an important methodological advance. The method has been improved for isolation of high-quality RNA for RNA-Seq analyses for investigations on Arabidopsis thaliana and sexual and apomictic accessions from the closely related genus Boechera. In this chapter, the method from tissue fixation to RNA isolation is detailed.

Comparing human annotation and machine learning models for optimizing zebrafish behavioral classification in seizure analysis.

GraSTI-ACL: Graph spatial-temporal infomax with adversarial contrastive learning for brain disorders diagnosis based on resting-state fMRI.

Brain-wide hemodynamic responses to precise transcranial ultrasound neuromodulation.

Production of three-dimensional metallic parts through integration of an articulated robot and gas metal arc welding, also known as wire arc additive manufacturing (WAAM), can produce large-scale components with moderate geometrical complexity. This technology is particularly appealing due to its high deposition rates, scalability, and cost-effective feedstock compared to other AM processes. Despite its advantages, WAAM adoption is hindered by challenges in ensuring geometric conformity without extensive distortion, defect-free structures, and consistent mechanical properties. Finite element analysis (FEA) is often used to address the challenge of geometrical conformity. As the size of parts increases, the best practices for mesh size and temporal resolution known in the literature become computationally unviable. This research examined the effects of mesh and time-step resolutions during transient FEA of a large-scale (248 layers) metallic part. The impact of computational parameters on the thermal history, displacement, and residual stress distributions were evaluated. The results showed that predicted distortion was consistent across resolutions, while time-step length significantly affected predicted thermal history, and mesh size influenced residual stress distributions. To investigate this relationship further, directionally biased meshes were considered and analyzed. The results indicated that increasing mesh resolution perpendicular to the welding path yielded stress predictions that aligned closely with higher-resolution models while offering substantial computational savings. The significances of this research are related to verification and validation of WAAM models for widespread industrial adoption and pragmatic guidelines for optimizing computation parameters for balancing computational efficiency and predictive accuracy of residual stress and distortion.

Topological materials, characterized by symmetry-protected nontrivial band structures such as Dirac cones and Weyl nodes, exhibit a rich variety of quantum states and novel physical phenomena. These materials hold great promise for applications in quantum transport, spintronics, and nonlinear optics. In recent years, ultrafast pump-probe spectroscopy has become a powerful tool for studying nonequilibrium dynamics in quantum materials. With femtosecond temporal resolution, this technique enables direct observation of charge, spin, orbital, and lattice interactions on their intrinsic timescales, offering new insights into the coupling mechanisms in topological systems. This review summarizes the latest progress in applying ultrafast spectroscopy to topological insulators, topological semimetals, and magnetic topological materials. We first discuss the distinct relaxation pathways of surface and bulk electronic states after photoexcitation, focusing on electron-phonon scattering, surface-bulk charge transfer, and ultrafast spin conversion. We then describe population inversion phenomena in Dirac and Weyl semimetals, spin polarization dynamics induced by tilted Weyl bands, and the influence of magnetic order on topological states, including coherent phonon and magnon excitations, magnetically driven topological transitions, and terahertz pulse generation. Furthermore, we review photoinduced topological phase transitions driven by electronic correlations, lattice distortions, and magnetic order under strong optical fields, highlighting the potential for nonthermal optical control of quantum phases. Finally, we discuss future research directions, emphasizing the integration of multidimensional ultrafast spectroscopic techniques—spanning temporal, energy, momentum, and spin resolution—with advanced theoretical simulations to construct a comprehensive picture of nonequilibrium topological states. This work aims to serve as a reference for studies on the ultrafast dynamics of topological quantum materials and to promote their practical applications in high-speed, low-power information processing, spintronics, and quantum computation.

In silico assessment of aortic hemodynamic sensitivity to inlet boundary conditions: Comparative analysis of 4D MRI, patient-specific, and modified generic waveforms.

Spatio-temporal registration of multi-perspective 3D echocardiography for improved strain estimation.

Abstract A competitive dual-tapered Φ-OTDR sensor is proposed to enhance the sensitivity of the fiber under test (FUT). Experimental results demonstrate that employing two 1.5 cm-long tapers with a 20 µm diameter embedded in a 20 m fiber sensor not only improves overall performance but also increases its efficiency. The sensor was experimentally characterized by immersing the dual-tapered 20 m fiber in a distilled water bath with a gradually increasing temperature starting from 20 °C. It exhibited an extended dynamic temperature range of approximately 20 °C, achieving a minimum temporal shift resolution of 0.14 µs/°C, a minimum detectable phase shift of 3.89×10 -3 ±6×10 -4 rad, and a minimum detectable sensitivity of 0.01 V/°C. However, due to a saturation effect, the operational temperature range of the fabricated Φ-OTDR sensor was limited to below 40 °C. The refractive index measurements obtained from the raw Φ-OTDR signals as a function of temperature were compared with theoretical values, showing a maximum deviation of 1.52×10⁻² % at 36 °C. These findings highlight the enhanced performance, precision, and reliability of the proposed sensor design

Real-time multislice-to-volume motion correction for task-based EPI-fMRI at 7T.

Measuring greenhouse gas emissions from composting: A comparative review of methods.

Subsampled azimuthal scanning excitation surface plasmon resonance holographic microscopy for enhancing temporal resolution

Combining fast and slow fMRI sampling rates can enhance predictive power in resting-state data.

Transformers have been successfully applied in the field of video-based 3D human pose estimation. However, the high computational costs of these video pose transformers (VPTs) make them impractical on resource-constrained devices. In this paper, we present a hierarchical plug-and-play pruning-and-recovering framework, called Hierarchical Hourglass Tokenizer (H2OT), for efficient transformer-based 3D human pose estimation from videos. H2OT begins with progressively pruning pose tokens of redundant frames and ends with recovering full-length sequences, resulting in a few pose tokens in the intermediate transformer blocks and thus improving the model efficiency. It works with two key modules, namely, a Token Pruning Module (TPM) and a Token Recovering Module (TRM). TPM dynamically selects a few representative tokens to eliminate the redundancy of video frames, while TRM restores the detailed spatio-temporal information based on the selected tokens, thereby expanding the network output to the original full-length temporal resolution for fast inference. Our method is general-purpose: it can be easily incorporated into common VPT models on both seq2seq and seq2frame pipelines while effectively accommodating different token pruning and recovery strategies. In addition, our H2OT reveals that maintaining the full pose sequence is unnecessary, and a few pose tokens of representative frames can achieve both high efficiency and estimation accuracy. Extensive experiments on multiple benchmark datasets demonstrate both the effectiveness and efficiency of the proposed method.

Revealing early subchondral bone structural changes in osteoarthritis progression in a collagenase-induced mouse model using microCT.

The preparation of ratio-fluorescent/T1 weight dual mode imaging material PAA/manganese dioxide/graphene quantum dots composites and its application on quantitative analysis of H3PO4.