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The robustness of repetition-based illusory truth and certainty effects in social media contexts
Abstract In the past, cognitive illusions, such as the repetition-based illusory truth and certainty effects, were primarily studied in experimental settings that were far removed from real-world conditions. However, information channels – particularly social media – provide competing cues (e.g., likes) that may influence such cognitive phenomena. In the present study ( N = 165), participants were assigned to one of two groups that viewed Instagram-like posts either with visible like counts (experimental condition) or without them (control condition). In addition, within the experimental group ( N = 82), the number of likes was systematically manipulated. Results showed no moderating effect of like visibility on the repetition-based illusory truth or certainty effects. However, especially when repetition-based cues were absent, low (compared to high) like counts substantially reduced both subjective truth and confidence (experimental condition), highlighting the dominant role of information repetition in shaping perceived truth and confidence in truth evaluations.
A privacy-preserving federated learning approach with multilevel differential privacy for lung cancer detection
Study on the friction distribution characteristics of directional long-hole drill pipe systems
Epacadostat and Olaparib synergistically inhibit pancreatic cancer growth through downregulation HR-associated proteins
No association of childhood maltreatment experiences and attention to facial emotions in men
Abstract A recent study investigated the relationship between childhood trauma and attention to emotions as a function of type and severity of maltreatment in a sample of women. It was found that high levels of physical and emotional abuse severity were associated with a diminished attentional preference for happy faces. Given that men exhibit distinct patterns of childhood maltreatment and often show lower accuracy and attention toward facial emotions compared to women, investigating these relationships specifically in male populations is warranted. In the present study, we examined the relationship between childhood trauma and attention to emotions in a sample of men. Gaze behavior of 98 men with a history of childhood trauma was analyzed in a free-viewing task. Pairs of faces with an emotional (happy, surprised, angry, disgusted, fearful, and sad) and a neutral face were shown for 5 s. An attentional bias score was calculated by subtracting the total fixation duration on the neutral face from that on the emotional face. To assess childhood maltreatment experiences, the Childhood Trauma Questionnaire was employed. Linear mixed models were used to investigate research questions. The attentional bias scores exhibited high reliability. For all emotion categories, participants looked longer at the emotional compared to the neutral face. The highest attentional preference was found for happy faces. Results indicated neither a significant main effect of childhood maltreatment type, nor a significant interaction effect between childhood maltreatment type and emotion category. Similarly, no main effect or interaction involving overall childhood maltreatment severity was found. The present findings reveal no significant relationship between childhood experiences of maltreatment (including emotional, sexual, and physical abuse, as well as emotional neglect) and visual attention to facial emotions in men. Our data do not support the hypothesis that early life trauma may lead to alterations in attentional processing of emotional facial expressions in men.
Reducing computational complexity in nonlinear power system state estimation via ANN-assisted linear Kalman filtering
Abstract This paper proposes a computationally efficient dynamic state estimation algorithm for nonlinear power networks using synchronized phasor measurements and a combination of an artificial neural network and a linear Kalman filter. The methodology involves using both the predicting abilities of the artificial neural network (ANN) and the iterative correction properties of the linear Kalman filter to estimate system states under dynamic operating conditions. Instead of using the nonlinear estimation approaches requiring the repeated computation of Jacobians and matrices, the presented approach significantly reduces the computational complexity while maintaining accurate estimation. The ANN is first trained on PMU measurement data and generates predictive state values for the system, which are corrected using the linear Kalman filter to remove the effect of noise and increase resistance to measurement corruption and malicious attacks. Numerical simulation experiments carried out on the IEEE 6-bus test network have shown that the hybrid state estimator provides more accurate results in terms of reduced RMSE and faster convergence when compared to the conventional state estimation methods.
Biomechanics-informed inertial tracking achieves the accuracy of marker-based kinematics
Intrinsically unidirectional stepwise chemically fueled rotary molecular motors
Enhanced and directional light emission from two-dimensional excitons using Mie voids
Abstract Controlling light emission at the nanoscale has important applications in solid-state lighting, displays, and quantum light sources. Achieving this control requires both enhanced local electromagnetic fields to boost emission intensity and engineered radiation patterns to direct photons efficiently. Mie voids, consisting of an air cavity surrounded by a high-index semiconductor, are particularly suited for this purpose because they expose their strongest fields in an accessible region for nearby emitters while supporting resonances that shape directional emission through interference. Here, we demonstrate an all-van der Waals nanophotonic platform that couples excitons in atomically thin WS 2 to Mie void resonators formed in WSe 2 . Guided by electromagnetic simulations, we identify void geometries that maximize photoluminescence through synergistic enhancement of excitation and emission processes. We also introduce a two-step fabrication approach that leverages van der Waals assembly to independently control the void diameter and depth. Experimentally, we observe up to a 600-fold increase in photoluminescence intensity from monolayer WS 2 placed on individual voids compared to unstructured WSe 2 , along with pronounced out-of-plane beaming of light that yields a forward-to-off-axis enhancement of 2.6 dB. These results establish Mie voids in van der Waals semiconductors as a versatile platform for controlling light-matter interactions at the nanoscale.
DMS-Vmunet: dynamic multi-scale vision Mamba Unet for non-small cell lung cancer CT image segmentation
Abstract The CT image segmentation task of non-small cell lung cancer (NSCLC) suffers from the challenges of small target and severe background noise interference, etc. Current research incorporates a variety of neural network architectures to improve the overall segmentation performance, but most of the frameworks still have difficulty in balancing local detail preservation and global background modeling, especially the lack of ability to perceive small nodules. Therefore, this paper proposes dynamic multi-scale vision Mamba UNet (DMS-Vmunet). HDVSS modules for enhancing the segmentation performance on small targets are proposed in this framework, including Multi-SS2D module and IDConv module. The Multi-SS2D module enhances the local sensing bias and perception of small targets through multi-scale parallel branching design, while the IDConv module focuses the convolution operation on the important regions of small targets through adaptive dynamic convolution. In addition, in order to ensure the effective fusion of local and global features in parallel branches, a dual-path feature fusion (DFC) module is introduced to fuse the multi-scale feature information from multiple branches. Experimental results show that the proposed framework can effectively improve the performance of CT image segmentation for non-small cell lung cancer, especially for small target segmentation.
Atomically dispersed Ti on MnOx-Fe2O3 tailors O 2p orbitals for CO oxidation and H2O/SO2 resistance
A physics-informed PointNet + + for hand gesture recognition using radar point cloud
Boosting genome editing in perennial plants by CRISPR-Combo mediated morphogenic gene activation
Prothrombin time predicts mortality in hypothermic sepsis and links hypothermia to impaired hepatic coagulation factor synthesis
In situ NIR-IIb imaging of endogenous H2S signaling for high-resolution abiotic stress visualization in plants
Development and external validation of a nomogram for overall survival in oral tongue squamous cell carcinoma using machine learning-assisted feature selection
Solvation-engineering-enabled quasi-solid positive electrode for four-electron aqueous Zn||Br batteries
The perception of realism is correlated with physical gamuts
Neutrophil NADPH oxidase breaks the inflammatory IL-1β/IL-17A circuit to enhance pathogen clearance during respiratory virus infections
Abstract Respiratory virus infections are invariably accompanied by an increase in oxidative stress through elevated production of Reactive Oxygen Species (ROS), which contribute to both host defence and pathogenesis. Using mouse models, we identify neutrophil NADPH Oxidase 2 (Nox2) as the major early source of ROS during Influenza A Virus (IAV) infection. Surprisingly, neutrophil Nox2-derived ROS display multifaceted effects, not only unleashing oxidative stress but also limiting pro-inflammatory IL-1β signalling. Absence of neutrophil Nox2 enhances IL-1β production, promoting the proliferation of IL-17-producing gamma delta (γδ) T cells. This early self-amplified augmentation of the IL-1β/IL-17 axis is associated with increased viral burden and reduced IFNα expression in the lung. We extend our findings to humans. Similar patterns of ROS production and cytokine regulation are observed in human neutrophils when exposed to IAV and the viral RNA analogue poly(I:C). Our discovery highlights that ROS, often associated with harm, play a dual role by regulating cytokine signalling and thus influencing the immune response against respiratory viruses.