The utilization of deep learning techniques for decoding visual perception images from brain activity recorded by functional magnetic resonance imaging (fMRI) has garnered considerable attention in ...recent research. However, reconstructed images from previous studies still suffer from low quality or unreliability. Moreover, the complexity inherent to fMRI data, characterized by high dimensionality and low signal-to-noise ratio, poses significant challenges in extracting meaningful visual information for perceptual reconstruction. In this regard, we proposes a novel neural decoding model, named the hierarchical semantic generative adversarial network (HS-GAN), inspired by the hierarchical encoding of the visual cortex and the homology theory of convolutional neural networks (CNNs), which is capable of reconstructing perceptual images from fMRI data by leveraging the hierarchical and semantic representations. The experimental results demonstrate that HS-GAN achieved the best performance on Horikawa2017 dataset (histogram similarity: 0.447, SSIM-Acc: 78.9%, Peceptual-Acc: 95.38%, AlexNet(2): 96.24% and AlexNet(5): 94.82%) over existing advanced methods, indicating improved naturalness and fidelity of the reconstructed image. The versatility of the HS-GAN was also highlighted, as it demonstrated promising generalization capabilities in reconstructing handwritten digits, achieving the highest SSIM (0.783±0.038), thus extending its application beyond training solely on natural images.
We theoretically demonstrated a switchable, as well as tuneable, asymmetric transmission and reflective polarization conversion device in terahertz region. The proposed dual-function device composed ...of vanadium dioxide (VO2) and Dirac semimetal (DSM) metamaterials (MMs). Switching is achieved by exploiting the dielectric-to-metal phase transition of VO2 board. On the one hand, the hybrid MMs structure behave as a transmission device when VO2 board in its insulating phase and VO2 grating in its metallic phase. In this case, broadband asymmetric transmission of linear polarization has been realised in the range of 2.023–5.971 THz. On the other hand, this hybrid metamaterial acts as a reflective device when VO2 board in its metallic phase and VO2 grating in its insulating phase. In this situation, linear-to-circular polarization conversion has been achieved in the ranges 2.058–3.423 and 4.753–5.6 THz, and at 6.496 THz. In each of the above working modes, tuneable spectral response has been achieved by modifying the Fermi energy of DSM materials. The device also exhibits a robust polarization conversion performance with the incident angle less than 40°. Dual-function metamaterial like the one presented here may find applications in active polarization controller, asymmetric transmission device, broadband and multiband filters, and other tuneable modulators.
The reconstruction of visual stimuli from fMRI signals, which record brain activity, is a challenging task with crucial research value in the fields of neuroscience and machine learning. Previous ...studies tend to emphasize reconstructing pixel-level features (contours, colors, etc.) or semantic features (object category) of the stimulus image, but typically, these properties are not reconstructed together. In this context, we introduce a novel three-stage visual reconstruction approach called the Dual-guided Brain Diffusion Model (DBDM). Initially, we employ the Very Deep Variational Autoencoder (VDVAE) to reconstruct a coarse image from fMRI data, capturing the underlying details of the original image. Subsequently, the Bootstrapping Language-Image Pre-training (BLIP) model is utilized to provide a semantic annotation for each image. Finally, the image-to-image generation pipeline of the Versatile Diffusion (VD) model is utilized to recover natural images from the fMRI patterns guided by both visual and semantic information. The experimental results demonstrate that DBDM surpasses previous approaches in both qualitative and quantitative comparisons. In particular, the best performance is achieved by DBDM in reconstructing the semantic details of the original image; the Inception, CLIP and SwAV distances are 0.611, 0.225 and 0.405, respectively. This confirms the efficacy of our model and its potential to advance visual decoding research.
In this paper, we propose an approach to improve the sensitivity of an optical fiber surface plasmon resonance (SPR) sensor with a pure higher-order mode excited by a designed mode selective coupler ...(MSC). We calculate the proportion of the power of the higher-order mode in the cladding. Compared to the LP01 mode, the power proportion of the LP11 mode (LP21 mode) in the cladding theoretically improves by 100% (150%). To generate a relatively pure LP11 mode or LP21 mode, a mode selective coupler (MSC, 430–580 nm) is designed. The coupling efficiency of the LP01–LP11 mode coupler is over 80%, and that of the LP01–LP21 mode coupler is over 50%. The simulation results show that the sensitivity of the LP11 mode and the LP21 mode increases by approximately 330% and 360%, respectively, using the intensity modulation (n = 1.33–1.38, 430–580 nm); the resolution of the refractive indices of our sensor, using the LP11 mode (LP21 mode), is 2.6×10−4 RIU (2.4×10−4 RIU). The higher sensitivity and resolution of our presented fiber SPR sensor containing a visible MSC make it a promising candidate for the measurement of refractive indices.
The changing land use is one of the primary factors influencing the pattern of carbon sources/sinks, while climate change is a major driver for land use change. With global warming increasing, ...assessing the impact of climate extremes on land use carbon emissions remains a great challenge. Here, we explored the changes in climate extremes from 1961 to 2020 using the CN05.1 gridded observation dataset. The impact of climate extremes on land use carbon emissions was analyzed by Pearson correlation methodology. The results demonstrated that (1) extreme temperatures were trending upwards, and dry periods were long, but short periods of heavy precipitation were possible from 1961 to 2020. (2) In terms of the extreme temperature indices, the high temperatures indices were positively correlated with land use carbon emissions. For the extreme precipitation indices, the other seven indices except CDD were also positively correlated with land use carbon emissions. (3) Furthermore, the extreme heat indices were positively correlated with land use carbon emissions mainly on construction land. The wetness indices showed a positive correlation with land use carbon emissions in the middle of Shandong Province. (4) Additionally, the influence of extreme temperatures on land use carbon emissions in Shandong Province was larger than of extreme precipitation. Among all the extreme climate indices, TN10p had the largest effect on land use carbon emissions and was significantly negatively correlated. These findings will provide scientific references for regional responses to climate change and the promotion of carbon emission reduction.
•The impact of extreme temperatures on LUCE is larger than of extreme precipitation.•TN10p has the largest effect on LUCE and was significantly negatively correlated.•The extreme heat indices are positively correlated with land use carbon emissions mainly on construction land.•The wetness indices show a positive correlation with land use carbon emissions in the middle of Shandong Province.
We present a bifunctional polarization converter based on Dirac semimetals (DSMs) and vanadium dioxide (VO
2
), which consists of two layers of DSMs on both sides, a metal grating and a VO
2
board. ...The polarization converter frequency is dynamically tuned by changing the Fermi energy level of the DSMs. The result suggests that when VO
2
is in an insulated state, the device behaves as a transmissive polarization converter. The dual-band transmissive polarization conversion and asymmetric transmission (AT) function of circularly polarized (CP) waves are realized at 1.99 THz and 3.46 THz, with the polarization converter ratio (PCR) reached 97.6% and 95.8%, respectively. In addition, when VO
2
is in the metal state, the designed polarization converter is a reflective device, which can maintain the chirality of the reflected CP wave to the incident wave in a wide band. The polarization-maintaining ratio (PMR) in the range of 2 THz to 3.55 THz is higher than 88%. When the angle of incidence is less than 60°, the frequency band of the PMR is narrowed and the amplitude reaches more than 90%.
Changes in land use types in alpine meadow areas have significant impacts on the ecological environment in alpine areas. Exploring land use change is crucial for land use management and optimization ...in alpine regions. Thus, it is necessary to analyze land use evolution and its drivers in alpine meadow regions from a production–living–ecology space (PLES) perspective by using remote sensing data. We first constructed the PLES evaluation system for Gannan. Then, we analyzed the spatial and temporal evolution characteristics and coupling degree of PLES in the study area. Finally, the driving factors affecting PLES were explored with geodetector. The conclusions of the study reveal that the distribution of productive and ecological spaces is large and concentrated, while the distribution of living spaces is more decentralized. The PLES was mainly concentrated in the area above 2500 m but below 4000 m and with a slope of 40° or less. During the study period, the area of production space showed a decreasing trend, while the areas of living and ecological space both showed increasing trends, primarily occurring at the expense of production space. DEM and GDP were the main factors affecting the distribution of PLES. The coupling level and the degree of coupling coordination were relatively stable in general, showing a pattern of “high in the east and low in the west”. The study provides technical support and a theoretical basis for the future planning of land space and ecological environment optimization in the alpine meadow regions.
Single-cell RNA sequencing (scRNA-seq) experiments have become instrumental in developmental and differentiation studies, enabling the profiling of cells at a single or multiple time-points to ...uncover subtle variations in expression profiles reflecting underlying biological processes. Benchmarking studies have compared many of the computational methods used to reconstruct cellular dynamics; however, researchers still encounter challenges in their analysis due to uncertainty with respect to selecting the most appropriate methods and parameters. Even among universal data processing steps used by trajectory inference methods such as feature selection and dimension reduction, trajectory methods' performances are highly dataset-specific. To address these challenges, we developed Escort, a novel framework for evaluating a dataset's suitability for trajectory inference and quantifying trajectory properties influenced by analysis decisions. Escort evaluates the suitability of trajectory analysis and the combined effects of processing choices using trajectory-specific metrics. Escort navigates single-cell trajectory analysis through these data-driven assessments, reducing uncertainty and much of the decision burden inherent to trajectory inference analyses. Escort is implemented in an accessible R package and R/Shiny application, providing researchers with the necessary tools to make informed decisions during trajectory analysis and enabling new insights into dynamic biological processes at single-cell resolution.
A nanoparticle-based few-mode multi-core fiber (FM-MCF) localized surface plasmon resonance (LSPR) biosensor is proposed and analyzed using the finite element method (FEM). It’s critical to narrow ...the loss spectrum and improve the coupling efficiency, which makes it have high resolution and high sensitivity. With the aid of open air holes, the gold nanoparticles are easily assembled on the surface of this FM-MCF LSPR biosensor. Through multiple investigations, the performance of the sensor can be improved by properly setting gold nanoparticle configurations, such as radius, positions, shapes, and nanoparticle arrays. The simulation results show that when three circular gold nanoparticles with a radius of 150 nm are placed symmetrically in the open air hole and the angle between adjacent nanoparticles is 5°, the maximum sensitivity of 7,351.6 nm/RIU (LP
02y
mode n
a
= 1.38) can be obtained in the sensing range of 1.33–1.38, which covers the refractive index (RI) of biological fluids, such as bovine serum albumin (BSA) solution and human Immunoglobulin G.
The use of deep learning methods to decode visual perception images from brain activity recorded by fMRI has received a lot of attention. However, limited fMRI data make the task of visual ...reconstruction challenging. Inspired by hierarchical encoding of the visual cortex and the theory of brain homology with convolutional neural networks (CNNs), we propose a novel neural decoding model called hierarchical semantic generative adversarial network (HS-GAN). Specifically, we use CNN-based image encoder to extract hierarchical and semantic features of visually stimulus images. Then a neural decoder is used to decode hierarchical and semantic features from fMRI. In order to take full advantage of the information from different visual cortexes, we construct a generator with self-attention modules and skip connections to fuse the image features of different layers. In model training, adversarial learning is introduced to realize more natural image reconstruction. Compared to existing advanced methods, our method significantly improves the naturalness and fidelity of reconstructed images.
PDF
