Group Delay Controlled by the Decoherence of a Single Artificial Atom.

The ability to slow down light at the single-photon level has applications in quantum information processing and other quantum technologies. We demonstrate two methods, both using just a single artificial atom, enabling dynamic control over microwave light velocities in waveguide quantum electrodynamics (QED). Our methods are based on two distinct mechanisms harnessing the balance between radiative decay and nonradiative decoherence rates of a superconducting artificial atom in front of a mirror.

Rapid and sensitive acute leukemia classification and diagnosis platform using deep learning-assisted SERS detection.

Rapid identification and accurate diagnosis are critical for individuals with acute leukemia (AL). Here, we propose a combined deep learning and surface-enhanced Raman scattering (DL-SERS) classification strategy to achieve rapid and sensitive identification of AL with various subtypes and genetic abnormalities. More than 390 of cerebrospinal fluid (CSF) samples are collected as targets, encompassing healthy control, AL patients, and individuals with other diseases.

Fabrication of Hydrophilic Gadolinium Hydroxide Sheets via A Gadolinium-Based Precipitation Reaction.

In this work, we report a facile strategy for synthesizing hydrophilic Gd(OH) sheets via a Gd-based interfacial precipitation reaction at the interface of organosilane-modified GdO nanoparticles and a cation exchange resin. This strategy, independent of the specific organosilane used, produces two-dimensional sheets with a distinct lamellar structure and excellent aqueous dispersibility. Characterization confirms the formation of Gd(OH) sheets with promising fluorescent and magnetic properties.

Diverse Perovskite Solar Cells: Progress, Challenges, and Perspectives.

Perovskite materials have revolutionized optoelectronics by virtue of their tunable bandgaps, exceptional optoelectronic properties, and structural flexibility. Notably, the state-of-the-art performance of perovskite solar cells has reached 27%, making perovskite materials a promising candidate for next-generation photovoltaic technology. Although numerous reviews regarding perovskite materials have been published, the existing reviews generally focus on individual material systems (e.

The relationship between fear of negative evaluation and social anxiety in parents of children with ASD: The chain mediating role of perceived social support and coping styles.

Parents of children with ASD face significantly greater parenting challenges than those raising typically developing children due to prolonged exposure to their children's developmental disorders, emotional distress, and atypical behaviors, underscoring the urgency of addressing their mental health concerns. This study examined the relationship between fear of negative evaluation (FNE) and social anxiety in parents of children with ASD, with a focus on the mediating roles of perceived social support and coping styles. A cross-sectional survey was conducted among 585 parents of children with ASD using validated instruments: the Brief Fear of Negative Evaluation Scale (BFNE), the Social Anxiety Scale, the Perceived Social Support Scale, and the Simple Coping Style Questionnaire.

P-type buried layer DTSCR with predicted improved overshoot performance and discharge ability for ESD protections of advanced nanotechnology.

A novel P-type Buried Layer Diode-Triggered Silicon-Controlled Rectifier (PBL-DTSCR) with predicted good performance in electrostatic discharge (ESD) protection is proposed in this work. With P-type ESD implantations and silicide blocking layers applied to this novel structure, the efficiency of the diode triggering path is greatly improved, thus enhancing the discharge efficiency of the main path. Moreover, the parasitic SCR path is minimized by replacing the PNPN structure in conventional DTSCR to PNPNPN structure in PBL-DTSCR.

Hyperspectral anomaly detection leveraging spatial attention and right-shifted spectral energy.

In this research, we have proposed a novel anomaly detection algorithm for processing hyperspectral images (HSIs), called the Graph Attention Network-Beta Wavelet Graph Neural Network-based Hyperspectral Anomaly Detection (GAN-BWGNN HAD). This algorithm treats each pixel as a node in a graph, where edges represent pixel correlations and node attributes correspond to spectral features. The algorithm integrates spatial and spectral information, utilizing graph neural networks to identify nonlinear relationships within the image, thereby enhancing anomaly detection precision.

MSFI: Multi-timescale spatio-temporal features integration in spiking neural networks.

Dynamic vision sensors (DVS) asynchronously encode the polarity of brightness changes with high temporal resolution and a wide dynamic range, making them ideal for capturing temporal information. Spiking neural networks (SNNs) are well-suited for handling such event streams due to their inherent temporal information processing capability. However, existing SNNs only transmit membrane potential across timesteps, neglecting spatial dependencies and failing to extract complex temporal features.

Effect of the gut microbiota-blood metabolite axis on anti-influenza IgG levels after vaccination: A Mendelian randomization study.

While antibody responses to influenza viruses have been extensively studied, the immunogenicity of influenza vaccines remains highly variable among individuals. Growing evidence suggests that the gut microbiota (GM) and associated metabolites play a critical yet understudied role in shaping host immunity, including responses to vaccines. However, the mechanistic pathways linking microbial communities, blood metabolites, and influenza vaccine-induced antibody production remain poorly understood.

Non-iridescent yet angle-dependent structural colors on titanium surfaces induced by laser oxidation.

Optically variable features are widely used in product design and anti-counterfeiting. However, current industrial methods rely heavily on chemical inks, which pose environmental concerns and suffer from poor wear and corrosion resistance. We experimentally demonstrate the generation of non-iridescent yet angle-dependent structural colors on titanium surfaces using a nanosecond laser-induced oxidation.

Carbon Decorated Pd Species within Zeolite for Selective Furfural Hydrogenation.

Selective hydrogenation of biomass-derived furfural to furfuryl alcohol is fundamentally challenged by the dual adsorption of its reactive furan ring and carbonyl group on Pd catalysts, which drives nonselective pathways. To modulate the adsorption mode of furfural, we rationally incorporate carbon species onto Pd subnanoclusters encapsulated in a siliceous zeolite (Pd-C@S-1), achieving 98% selectivity for furfuryl alcohol at full furfural conversion, vastly outperforming the carbon-free Pd@S-1 (11.6% selectivity).

CRISPR-Driven Portable Piezoresistive Biosensor with Cascaded Signal Amplification for Ultrasensitive Osteocalcin Detection.

Low-turnover osteoporosis diagnosis urgently requires sensitive detection of low-abundance osteocalcin (OC), yet conventional methods remain constrained by insufficient sensitivity, cumbersome instrumentation, and laborious operations. We devise a CRISPR-driven pressure bioassay that synergistically integrates molecular recognition, enzymatic amplification, and signal transduction for dual-amplification-enhanced OC quantification. The system features an engineered "locked-to-activated" molecular switch, where target binding liberates CRISPR-activating DNA strands, initiating Cas14a-catalyzed cleavage of ssDNA tethers on FeO-ssDNA-Pt nanoassemblies.

Moisture-Resistant Scalable Ambient-Air Crystallization of Perovskite Films via Self-Buffered Molecular Migration Strategy.

Ambient-air, moisture-assisted annealing is widely used in fabricating perovskite solar cells (PSCs). However, the inherent sensitivity of perovskite intermediate-phase to moisture-due to fast and spontaneous intermolecular exchange reaction-requires strict control of ambient humidity and immediate thermal annealing treatment, raising manufacturing costs and causing fast nucleation of perovskite films. We report herein a self-buffered molecular migration strategy to slow down the intermolecular exchange reaction by introducing a n-butylammonium bromide shielding layer, which limits moisture diffusion into intermediate-phase film.

Discrete Actuation of Water-Responsive Crystalline Metal-Peptide Frameworks.

Engineering guest-responsive materials capable of controlled and precise sorption behavior and structural deformation in response to external stimuli is imperative for various applications. However, existing systems often exhibit complex, unpredictable dynamics, posing challenges for efficient control and utilization. Here, we design crystalline metal-peptide frameworks with tunable water-responsive (WR) dynamics by assembling glycine-threonine (Gly-Thr, GT) or glycine-serine (Gly-Ser, GS) peptides with zinc (Zn) ions, achieving either continuous or discrete threshold water-sorption-dependent phase transitions.

Language-guided multimodal domain generalization for outcome prediction of head and neck cancer.

Accurate prediction of head and neck cancer recurrence across medical institutions remains challenging due to inherent domain shifts in imaging data. Current domain generalization methods primarily focus on learning domain-invariant features from medical images, often overlooking structured clinical information that inherently exhibits cross-institutional consistency. To leverage clinical data and enhance the model's generalization, we propose an end-to-end Language-Guided Multimodal Domain Generalization (LGMDG) method.

Van der Waals β-GaO thin films on polycrystalline diamond substrates.

The self-heating effect in wide bandgap semiconductor devices makes epitaxial GaO on diamond substrates crucial for thermal management. However, the lack of wafer-scale single-crystal diamond and severe lattice mismatch limit its industrial application. This study presents van der Waals β-GaO (VdW-β-GaO) grown on high-thermal-conductivity polycrystalline diamond.

YModPred: an interpretable prediction method for multi-type RNA modification sites in S. cerevisiae based on deep learning.

Background: RNA post-transcriptional modifications involve the addition of chemical groups to RNA molecules or alterations to their local structure. These modifications can change RNA base pairing, affect thermal stability, and influence RNA folding, thereby impacting alternative splicing, translation, cellular localization, stability, and interactions with proteins and other molecules. Accurate prediction of RNA modification sites is essential for understanding modification mechanisms.

Observation of nonlinear edge states in an interacting atomic trimer array.

Exploring the interplay between topology and nonlinearity leads to an emerging field of nonlinear topological physics, which extends the study of fascinating properties of topological states to a regime where interactions between the particles cannot be neglected. For ultracold atomic systems, although many exotic topological states have been recently observed, the nonlinear effect remains elusive. Here, based on the laser-driven couplings of discrete atomic momentum states, we synthesize a topological trimer array, where the atomic interactions give rise to tunable nonlinearities.

Research on a General SER Rate Prediction Model Based on a Set of Configuration Parameters Related to SER.

This article comprehensively analyzes the new developments and challenges faced by several typical prediction models in the field of radiation effects in recent years. The models discussed include the RPP model, the extended RPP (rectangular parallelepiped) model, and the IRPP (integral rectangular parallelepiped) model. The article conducts a comprehensive analysis of the limitations of the assumption that uses the linear energy transfer (LET) of incident particles and the SEU (single-particle upset) cross-section (without considering the energy and type of ions) to predict the rate of single-particle effects (SEUs).

Total Ionizing Dose Effect Simulation Modeling and Analysis for a DCAP Power Chip.

In this paper, a systematic study on performance degradation of a 0.18 μm BCD-process DCAP (Direct connection to the output CAPacitor) power chip under a total-dose radiation environment is carried out. The effects of total-dose radiation on the electrical characteristics of an MOS device are analyzed through device-level simulation.

The Multi-Objective Optimization of a Dual C-Type Gold Ribbon Interconnect Structure Considering Its Geometrical Parameter Fluctuation.

With the increasing demand for high integration, low cost, and large capacities in satellite systems, integrating the antenna and microwave component into the same system has become appealing to the satellite engineer. The dual C-type gold ribbon, performing as the key electromagnetic signal bridge between the microwave component and the antenna, has a significant impact on the electrical performance of satellite antennas. However, during its manufacturing and operating, the interconnection geometry undergoes deformation due to mounting errors and environmental loads.

Research on Switching Current Model of GaN HEMT Based on Neural Network.

The switching characteristics of GaN HEMT devices exhibit a very complex dynamic nonlinear behavior and multi-physics coupling characteristics, and traditional switching current models based on physical mechanisms have significant limitations. This article adopts a hybrid architecture of convolutional neural network and long short-term memory network (CNN-LSTM). In the 1D-CNN layer, the one-dimensional convolutional neural network can automatically learn and extract local transient features of time series data by sliding convolution operations on time series data through its convolution kernel, making these local transient features present a specific form in the local time window.

Design and Fabrication of Embedded Microchannel Cooling Solutions for High-Power-Density Semiconductor Devices.

The rapid development of high-power-density semiconductor devices has rendered conventional thermal management techniques inadequate for handling their extreme heat fluxes. This manuscript presents and implements an embedded microchannel cooling solution for such devices. By directly integrating micropillar arrays within the near-junction region of the substrate, efficient forced convection and flow boiling mechanisms are achieved.

Integrated Additive Manufacturing of TGV Interconnects and High-Frequency Circuits via Bipolar-Controlled EHD Jetting.

Electrohydrodynamic (EHD) printing offers mask-free, high-resolution deposition across a broad range of ink viscosities, yet combining void-free filling of high-aspect-ratio through-glass vias (TGVs) with ultrafine drop-on-demand (DOD) line printing on the same platform requires balancing conflicting requirements: for example, high field strengths to drive ink into deep and narrow vias; sufficiently high ink viscosity to prevent gravity-induced leakage; and stable meniscus dynamics to avoid satellite droplets and charge accumulation on the glass surface. By coupling electrostatic field analysis with transient level-set simulations, we establish a dimensionless regime map that delineates stable cone-jetting regime; these predictions are validated by high-speed imaging and surface profilometry. Operating within this window, the platform achieves complete, void-free filling of 200 µm × 1.

A Review of Tunnel Field-Effect Transistors: Materials, Structures, and Applications.

The development of an integrated circuit faces the challenge of the physical limit of Moore's Law. One of the most important "Beyond Moore" challenges is the scaling down of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) versus their increasing static power consumption. This is because, at room temperature, the thermal emission transportation mechanism will cause a physical limitation on subthreshold swing (), which is fundamentally limited to a minimum value of 60 mV/decade for MOSFETs, and accompanied by an increase in off-state leakage current with the process of scaling down.