Enhancing fake news detection with transformer-based deep learning: A multidisciplinary approach.

The widespread dissemination of fake news presents a critical challenge to the integrity of digital information and erodes public trust. This urgent problem necessitates the development of sophisticated and reliable automated detection mechanisms. This study addresses this gap by proposing a robust fake news detection framework centred on a transformer-based architecture.

Preparation and Recognition Performance of Fleroxacin Ratio Fluorescent Paper-based Sensor Based On Molecularly Imprinted Polymer.

The pervasive concern regarding veterinary drug residues in food necessitates advanced detection solutions, particularly addressing limitations of conventional methods reliant on large-scale instrumentation that incur prolonged analysis duration, complex sample preparation, and lack of real-time on-site capability. A portable "single response-on" molecularly imprinted ratiometric fluorescent paper-based sensor was developed for quantifying fleroxacin (FLX) residues in animal-derived foods, wherein B, N-co-doped MXene quantum dot (B, N-MQD) was synthesized and combined with BCP-Eu as dual-emission fluorophores, while FLX- molecularly imprinted polymer (FLX-MIP) was engineered using functionalized Nano-SiO as the carrier. Concentration-dependent fluorescence enhancement at 574 nm was exhibited with invariant reference signal at 411 nm, achieving a 36-fold lower detection limit (0.

Real-time corneal image segmentation for cataract surgery based on detection framework.

Objective: Cataract surgery is among the most frequently performed procedures worldwide. Accurate, real-time segmentation of the cornea and surgical instruments is vital for intraoperative guidance and surgical education. However, most existing deep learning-based segmentation methods depend on pixel-level annotations, which are time-consuming and limit practical deployment.

Data-Driven Insights in Single-Molecule Break Junction Studies: A Comprehensive Review of the Data Analysis Methods.

Single-molecule electronics has emerged as a transformative field at the intersection of chemistry, physics, and nanotechnology, enabling the direct probing of charge transport phenomena at the molecular scale. The break junction technique, which measures conductance across metal-molecule-metal junctions, has become a cornerstone for studying single-molecule dynamics and quantum transport. However, interpreting the large-scale unlabeled conductance traces poses significant challenges.

A bidirectional interfacial engineering strategy for highly stable sodium metal batteries.

Sodium (Na) metal batteries (SMBs) are regarded as some of the most promising next-generation energy storage systems due to their high energy density. However, their practical application is severely hindered by interfacial instabilities at both the anode and cathode, which result in rapid capacity degradation during cycling. Here, we proposed a bidirectional interfacial regulation strategy that simultaneously stabilizes both electrode interfaces.

Experiment and Simulation Study of Automatic Temperature Control FAIMS Chip.

The temperature of the carrier gas will affect the performance of high-field asymmetric ion waveform mobility spectrometry (FAIMS), changing the height and position of the peaks of the FAIMS spectrum. In this study, we explored the influence of temperature on the FAIMS spectrum through experiment and simulation. In the experiment, the PCB self-heating temperature control FAIMS system was used to study the effects of temperature changes on the FAIMS spectra of ethanol, acetic acid, acetone, and ethyl acetate, and the coefficient solving methods of mobility and were derived in detail.

Spectroscopic characterization of three fungicides using terahertz spectroscopy and DFT theory, combined with convolutional neural networks for quantitative analysis of tebuconazole.

Fungicides are essential agrochemicals for the prevention and control of plant diseases. Counterfeit products, often lacking enough active ingredients, can compromise disease management and pose risks to agricultural safety. Precise quantification of the chemical structure and concentration of active components enables reliable authentication of fungicide formulations, ensuring their efficacy in crop protection and supporting the quality and safety of agricultural production.

Vision transformer network discovers the prognostic value of pancreatic cancer pathology sections via interpretable risk scores.

Pathological sections hold rich diagnostic information, yet their prognostic potential is underutilized. This study leverages deep learning to predict outcomes, advancing precision oncology of pathological sections with focus on pancreatic cancer. We analyzed H&E-stained whole section images of 125 cases from public databases as well as 28 real-world patients with pancreatic cancer and precancerous lesions.

Alginate-encapsulated ZIF-67 composite gel spheres for enhanced tetracycline removal and fixed-bed application.

The pervasive accumulation of tetracycline (TC) in aquatic ecosystems poses severe ecological and health threats, yet conventional technologies rarely achieve reliable removal under continuous-flow conditions. To overcome the intrinsic brittleness, aggregation and leaching of powdered ZIF-67, this study developed novel alginate-encapsulated MOF composite gel spheres (ALG/ZIF-67) via in-situ crystallization. This simple strategy generates hierarchical pores, anchors Co-N active sites and imparts mechanical robustness without sacrificing adsorption kinetics.

Photonic terahertz phased array via selective excitation of nonlinear Pancharatnam-Berry elements.

Phased arrays are crucial in various technologies, such as radar and wireless communications, due to their ability to precisely control and steer electromagnetic waves. This precise control improves signal processing and enhances imaging performance. However, extending phased arrays to the terahertz (THz) frequency range has proven challenging, especially for high-frequency operation, broadband performance, two-dimensional (2D) phase control with large antenna arrays, and flexible phase modulation.

Altered neural reward activation predicts clinical depression improvement after a novel loving-kindness meditation: a multimodal neuroimaging study.

Objective: Major depressive disorder (MDD) has become the second largest risk factor affecting human health, with a progress in its treatment especially non-pharmacological therapies. The loving-kindness meditation (LKM) has been introduced to depression but is not popular due to requirement on awareness and concentration, and its utilization in clinical MDD is absent as well as exploration on neural mechanism. This study aims to develop a more feasible novel therapy-loving-kindness meditation integrating cognition and behavior (LKM-CB), examine its effect on clinical depression, and further explore its neural mechanism by multimodal neuroimaging.

Reducing ion implantation in focused ion beam nanofabrication.

The focused ion beam (FIB) technique has been established as a powerful nanofabrication tool. The application of this technique is limited due to the implantation of beam ions into the substrate, which is difficult to overcome and can be detrimental in many cases. Herein, we report that in comparison with the commonly used smooth milling process, the amount of implanted gallium atoms in the near-surface region of fabricated structures can be significantly reduced when the ions strike a highly inclined sputtering front wall formed on the substrate surface during the edge milling process of the line-by-line beam scanning strategy.

Investigation on the Interfacial Delamination of Glass Substrate Packaging Using Cohesive Zone Models.

This study aligns with the development trend of glass substrate packaging. The research aims to analyze the delamination of the substrate-adhesive layer-chip trilayer structure in packaging through experimental testing to obtain interface strength parameters. Subsequently, an iterative process combining experiments and simulations was applied to establish a cohesive zone model characterizing crack initiation and propagation.

Wireless Communication Using a Radiation-Type Metasurface.

The rapid development of metasurfaces offers new possibilities to establish novel wireless communication systems with simplified architectures. However, the current demonstration systems are based on the reflection-type metasurfaces, which suffer from high profiles and integration challenges in practice. Such configurations are also inefficient for handling multiple subcarriers during beam scanning and beam tracking.

Research on Displacement Tracking Device Inside Hybrid Materials Based on Electromagnetic Induction Principle.

Magnetic induction imaging technology, as a non-invasive detection method based on the principle of electromagnetic induction, has a wide range of applications in the field of materials science and engineering with the advantages of no radiation and fast imaging. However, it has not been improved to address the problems of high contact measurement interference and low spatial resolution of traditional strain detection methods in bulk materials engineering. For this reason, this study proposes a magnetic induction detection technique incorporating metal particle assistance and designs a hardware detection system based on an eight-coil sensor to improve the sensitivity and accuracy of strain detection.

A Reliability Fault Diagnosis Method for Diesel Engines Based on the Belief Rule Base with Data-Driven Initialization.

Diesel engines serve as critical power sources across transportation and industrial fields, and their fault diagnosis is essential for ensuring operational safety and system reliability. However, acquiring sufficient and effective operational data remains a significant challenge due to the high complexity of the systems. As a modeling method that incorporates expert knowledge, the belief rule base (BRB) demonstrates strong potential in resolving such challenges.

CViT Weakly Supervised Network Fusing Dual-Branch Local-Global Features for Hyperspectral Image Classification.

In hyperspectral image (HSI) classification, feature learning and label accuracy play a crucial role. In actual hyperspectral scenes, however, noisy labels are unavoidable and seriously impact the performance of methods. While deep learning has achieved remarkable results in HSI classification tasks, its noise-resistant performance usually comes at the cost of feature representation capabilities.

Anisotropic Behavior in Microstructures and Properties of Refractory Tungsten Metal Produced by Laser Powder Bed Fusion.

This work employed laser powder bed fusion (LPBF) technology to prepare pure tungsten (W) metal components and investigated their internal defects, microstructural characteristics and mechanical properties within the horizontal and vertical planes to evaluate their anisotropic behavior. The steep temperature gradient and extremely rapid cooling rate during the LPBF process caused the as-deposited W grains to grow in a columnar crystal structure along the vertical height direction, with cracks propagating along the high-angle grain boundaries (HAGBs). Although the near-equiaxed W grains within the horizontal plane were finer than the epitaxial grains within the vertical plane, the increased number of cracks within the horizontal plane weakened the fine-grained strengthening effect, resulting in lower hardness and wear resistance within the horizontal plane than within the vertical plane.

Graph-based feature learning methods for subject-dependent and subject-independent motor imagery EEG decoding.

Unlabelled: The significant intra-individual variability and inter-individual differences in scalp electroencephalogram (EEG) make it difficult to learn task-distinguishable features, posing a challenge for motor imagery brain-computer interfaces. Current feature learning methods often produce an incomplete feature space, struggling to accommodate these variations and differences. Additionally, the weak discriminative nature of this feature space results in diminished EEG classification performance.

Interface Thermal Resistance in Heterostructures of Micro-Nano Power Devices: Current Status and Future Challenges.

As micro-nano power devices have evolved towards high frequency, high voltage, and a high level of integration, the issue of thermal resistance at heterointerfaces has become increasingly prominent, posing a key bottleneck that limits device performance and reliability. This paper presents a systematic review of the current state of research and future challenges related to interface thermal resistance in heterostructures within micro and nano power devices. First, based on phonon transport theory, we conducted an in-depth analysis of the heat transfer mechanisms at typical heterointerfaces, such as metal-semiconductor and semiconductor-semiconductor, and novel low-dimensional materials.

Buried-Gate Flexible CNT FET with HZO Dielectric on Mica Substrate.

Carbon nanotube field-effect transistors (CNT FETs) are considered strong candidates for next-generation flexible electronics due to their excellent carrier mobility and mechanical flexibility. However, the fabrication of CNT FETs on conventional flexible substrates such as PI or PET is often limited by surface roughness, chemical incompatibility, and poor mechanical robustness, resulting in degraded device performance. In this study, we report the fabrication of buried-gate CNT FETs incorporating HfZrO as the gate dielectric on mica substrates, which offer high surface flatness, low defect density, and superior mechanical durability.

SABE-YOLO: Structure-Aware and Boundary-Enhanced YOLO for Weld Seam Instance Segmentation.

Accurate weld seam recognition is essential in automated welding systems, as it directly affects path planning and welding quality. With the rapid advancement of industrial vision, weld seam instance segmentation has emerged as a prominent research focus in both academia and industry. However, existing approaches still face significant challenges in boundary perception and structural representation.

Detection of GNSS spoofed signals based on the weighted moving average bias correction method.

Spoofing intrusions pose a major threat to user security by delivering incorrect information. The detection rate of existing signal quality monitoring (SQM) metrics notably decreases when faced with numerous specific combinations of code phases and carrier phases in spoofing signal instances. To increase the detection rate and coverage, we exploit the offset detection capability of different correlators and propose metrics: multipoint slope differential (MuSD) and multipoint slope differential averaging (MuSDA).

Synthesis, dyeing performance and surface finishing effects of aminoethyl methacrylate functionalized stilbene fluorescent whitening agents.

Six novel stilbene fluorescent whitening agents bearing aminoethyl methacrylate groups were synthesized. Their molecular orbital energy levels, thermal stability, dyeing performance, and surface-finishing efficacy on cotton fibers were systematically characterized. The resulting compounds 6a-f exhibited high thermal decomposition temperatures and low orbital energy differences, contributing to exceptional whitening and surface finishing effects on pure cotton.