Shurong Dong

Structural magnetic resonance imaging supports the characterization of Alzheimer’s disease (AD)-related cognitive impairment. But existing cross-cohort AD classification methods remain limited in addressing acquisition and population shifts when source data cannot be revisited and target-side adaptation is excluded. In particular, current cross-cohort AD classification may underutilize diverse disease-related information learned from source data, while explicit characterization of regional, scale-dependent gray-matter morphology remains limited. To address these gaps, we propose FSE-CNN for source-free cross-cohort classification of AD-related cognitive status. First, the neural pathway derives decision evidence from model states retained during source training, with the inference configuration determined exclusively from source data. Second, the spatial-scale geometric evidence encoding module characterizes gray-matter morphology through subject-relative spatial organization and finite physical scales, providing complementary geometric evidence for cross-cohort classification. Finally, the resulting neural and geometric evidence are combined through protocol-specific fusion. We evaluated FSE-CNN on two cross-cohort protocols. In OASIS-2 → OASIS-1, FSE-CNN achieved 83.48% accuracy, 85.14% balanced accuracy, and 88.60% AUC, numerically exceeding Harmonizing Flows by 1.70, 1.26, and 0.39 percentage points, respectively. In ADNI → OASIS-2, it achieved 85.79% accuracy, 85.55% balanced accuracy, and 85.03% AUC, with corresponding gains of 0.71, 0.67, and 0.21 percentage points. Overall, these results demonstrate the effectiveness of FSE-CNN for cross-cohort AD-related cognitive-status classification.

Single-cell transfection technologies hold tremendous promise for precision cell and immunotherapies. However, monolithic integration of cell isolation with targeted intracellular delivery remains technically challenging, especially within complex biological matrices. Herein, we present a microcapillary-assisted acoustoelectric single-cell selective isolation and sonoporative transfection platform (μC-ASSIST), which seamlessly sequences microcapillary-assisted dielectrophoresis (μC-DEP) for deterministic single-cell trapping with high-frequency surface acoustic waves (SAWs) for transient membrane poration within a unified workflow. We demonstrate the label-free, high-efficiency extraction of human non-small cell lung cancer (A549) cells from a complex white blood cell (WBC) background with a capture efficiency of 95%. Furthermore, we validate the highly efficient, contact-free intracellular delivery of diverse cargoes ranging from small dyes (PI) to functional small interfering RNA (siRNA) and large plasmid DNA (mRFP-C3), maintaining a high cell viability of 83.7% alongside a 78.1% transfection efficiency. Crucially, the targeted delivery of siBcl-xL significantly suppressed target mRNA expression and profoundly inhibited tumor cell motility. By circumventing off-target effects and cumbersome manual handling, the μC-ASSIST platform establishes a highly versatile, streamlined paradigm for precision single-cell engineering, holding immense potential for advancing functional genomics and next-generation gene therapies.

Film bulk acoustic resonators (FBARs) are widely used in radio frequency (RF) filters for wireless communication because of their high operating frequency and high quality factor. With the increase of high-power applications, ensuring device robustness has become a critical challenge. This study presents an investigation into the high-power failure behaviors and mechanisms of FBARs, specifically examining the role of active area, film thickness, and geometry. Experimental results demonstrate that small-area FBARs exhibit distinct failure characteristics compared to large-area devices. Small-area devices are governed by progressive spallation at electrode edges, which is induced by high-temperature oxidation and stress concentration, whereas large-area FBARs are prone to sudden structural fracture or short-circuiting caused by excessive thermal stress. Crucially, the study reveals a thickness-dependent transition in large-area devices, where short-circuiting and structural fracture correspond to distinct stress-severity regimes. Furthermore, dynamic evaluations demonstrate that these FBARs preserve strict electrical linearity right up to the point of catastrophic collapse. Based on these phenomenological findings, a thermo-mechanical coupling mechanism is proposed that goes beyond the conventional thermal-only model. Finally, we propose new design guidelines to enhance the power handling capability of FBAR devices.

A wideband high-selectivity bandpass filter based on a hybrid acoustic-electromagnetic architecture is proposed. The gold bonding-wire inductance is intentionally employed as a designable series element of the bulk acoustic wave (BAW) resonator to construct a dual band-stop notch network, enabling a single acoustic resonator branch to generate two controllable transmission zeros. The notch frequencies can be tuned by the BAW resonator area and bonding-wire geometry. The distributed microstrip/coupled-line circuit forms the wide passband, while three embedded dual band-stop notch networks sharpen the passband skirts and suppress out-of-band spurious responses. For verification, the hybrid filter is fabricated and measured. The fabricated filter achieves a center frequency of 3.29 GHz, a fractional bandwidth of 25.9%, a minimum insertion loss of 1.19 dB, lower-side and upper-side 3-to-20-dB roll-off bandwidths of approximately 235 MHz and 145 MHz, respectively, and out-of-band suppression exceeding 22 dB. The results validate the proposed parasitic-aware hybrid design for wideband, high-selectivity RF front-end applications.

Temperature monitoring underpins critical processes in electronics, energy systems, and biomedical applications. Piezoelectric resonant temperature sensors based on lead zirconate titanate (PZT) are widely favored for their rapid thermal response and compact size, yet their linear temperature dependence severely limits the sensitivity. Here, we introduce a novel approach to piezoelectric thermometry by applying non-Hermitian physics and anti-parity−time (APT) symmetry to PZT resonators. The system couples two PZT resonators through energy interactions with gain/loss, forming an APT-symmetric architecture that operates at an exceptional point (EP). This configuration dramatically amplifies minute temperature-induced perturbations, achieving an ultrahigh temperature coefficient of frequency (TCF) of −1500 ppm·K ^-1 indicating a 17-fold enhancement over conventional single PZT sensors (~88 ppm·K ^-1 ), and over twice the sensitivity of state-of-the-art resonant temperature sensors without sacrificing power consumption or device size. Experimental results confirm a 2× improvement in signal-to-noise ratio (SNR) and dynamic adaptability. Unlike its PT-symmetric counterparts, APT symmetry tolerates intrinsic mismatches between PZTs, enabling robust EP operation and reconfigurability across a wide temperature range. By uniting non-Hermitian physics with piezoelectric platforms, this work establishes a new framework for piezoelectric thermometry in advanced electronics, energy storage, and biomedical systems.

The continuous scaling of complementary metal oxide semiconductor process technology has necessitated a reduction in operating voltages, thereby diminishing the noise margins of chips. Consequently, the ground bounce induced by electrostatic discharge events is more likely to cause critical power supply fluctuations, leading to soft failures in the chip. To rapidly identify design vulnerabilities, this article developed a power supply noise simulation model and integrated it into the full microcontroller unit (MCU) performance simulation flow to predict noise levels and guide design modifications. A power supply noise measurement method that requires no additional circuitry is further proposed to monitor key signals associated with soft failures on the MCU. Through improvements in down-bond packaging and a redesign of the low-dropout regulator and phase-locked loop circuits, the chip’s soft failure level is enhanced by a factor of more than 10 without increasing die area or degrading chip performance.