Semi-supervised wildfire smoke detection based on smoke-aware consistency

The semi-transparency property of smoke integrates it highly with the background contextual information in the image, which results in great visual differences in different areas. In addition, the limited annotation of smoke images from real forest scenarios brings more challenges for model training. In this paper, we design a semi-supervised learning strategy, named smokeaware consistency (SAC), to maintain pixel and context perceptual consistency in different backgrounds. Furthermore, we propose a smoke detection strategy with triple classification assistance for smoke and smoke-like object discrimination. Finally, we simplified the LFNet fire-smoke detection network to LFNet-v2, due to the proposed SAC and triple classification assistance that can perform the functions of some specific module. The extensive experiments validate that the proposed method significantly outperforms state-of-the-art object detection algorithms on wildfire smoke datasets and achieves satisfactory performance under challenging weather conditions.Peer ReviewedPostprint (published version

All-in-one aerial image enhancement network for forest scenes

Drone monitoring plays an irreplaceable and significant role in forest firefighting due to its characteristics of wide-range observation and real-time messaging. However, aerial images are often susceptible to different degradation problems before performing high-level visual tasks including but not limited to smoke detection, fire classification, and regional localization. Recently, the majority of image enhancement methods are centered around particular types of degradation, necessitating the memory unit to accommodate different models for distinct scenarios in practical applications. Furthermore, such a paradigm requires wasted computational and storage resources to determine the type of degradation, making it difficult to meet the real-time and lightweight requirements of real-world scenarios. In this paper, we propose an All-in-one Image Enhancement Network (AIENet) that can restore various degraded images in one network. Specifically, we design a new multi-scale receptive field image enhancement block, which can better reconstruct high-resolution details of target regions of different sizes. In particular, this plug-and-play module enables it to be embedded in any learning-based model. And it has better flexibility and generalization in practical applications. This paper takes three challenging image enhancement tasks encountered in drone monitoring as examples, whereby we conduct task-specific and all-in-one image enhancement experiments on a synthetic forest dataset. The results show that the proposed AIENet outperforms the state-of-the-art image enhancement algorithms quantitatively and qualitatively. Furthermore, extra experiments on high-level vision detection also show the promising performance of our method compared with some recent baselines.Award-winningPostprint (published version

Effect of rs1344706 in the ZNF804A gene on the brain network.

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = - 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

Increased IL-12 inhibits B cells' differentiation to germinal center cells and promotes differentiation to short-lived plasmablasts

B cells activated by antigen in T cell–dependent immune responses can become short-lived plasma cells, which remain in the spleen, or germinal center–derived memory or plasma cells, which show evidence of affinity maturation and, in the case of plasma cells, migrate to the bone marrow. We show that this cell fate decision can be governed by the cytokine environment engendered by activated dendritic cells (DCs). DCs from mice lacking the Fc receptor γ chain exhibited an activated phenotype in vitro. They secreted more of the proinflammatory cytokine IL-12, which led to the preferential generation of short-lived splenic plasma cells, with ensuing low affinity antibodies and a diminished recall response. Understanding the factors that regulate antigen-activated B cell differentiation and memory cell formation has implications for both antibody-mediated autoimmune disease and protective antibody responses

Different water and nitrogen level effects on soil microbial properties of spinach

Understanding the interactions of plant soil environment and rhizosphere microbial changes are necessary to develop new strategies for the sustainable agriculture. A field experiment with combination of three water levels and three nitrogen rates was conducted to investigate the effect of water and nitrogen management on the changes of soil microbial properties in non-rhizosphere and rhizosphere soils of spinach. Non-Rhizosphere and rhizosphere microbial diversities were affected by water and nitrogen applications. Evenness index in the no-nitrogen treatment was more than that of 85 and 170 kg ha–1 nitrogen treatments in the non-rhizosphere or rhizosphere soil. Microbial biomass carbon in non-rhizosphere soil or rhizosphere soil decreased with the increase of nitrogen application, but showed the highest value in 16.5% of soil water content, followed by 12.5% and 20.5% of soil water content. Soil microbial biomass phosphorus content of 85 kg ha–1 nitrogen treatment in the non-rhizosphere soil or rhizosphere soil was significantly different for 0 and 170 kg ha–1 nitrogen treatments. Nitrification rate increased with the increase of soil water content in 0 and 170 kg ha–1 treatments. Our results demonstrated that water and nitrogen could impact the soil fertility and microbial activity of spinach

TiAVox: Time-aware Attenuation Voxels for Sparse-view 4D DSA Reconstruction

Four-dimensional Digital Subtraction Angiography (4D DSA) plays a critical role in the diagnosis of many medical diseases, such as Arteriovenous Malformations (AVM) and Arteriovenous Fistulas (AVF). Despite its significant application value, the reconstruction of 4D DSA demands numerous views to effectively model the intricate vessels and radiocontrast flow, thereby implying a significant radiation dose. To address this high radiation issue, we propose a Time-aware Attenuation Voxel (TiAVox) approach for sparse-view 4D DSA reconstruction, which paves the way for high-quality 4D imaging. Additionally, 2D and 3D DSA imaging results can be generated from the reconstructed 4D DSA images. TiAVox introduces 4D attenuation voxel grids, which reflect attenuation properties from both spatial and temporal dimensions. It is optimized by minimizing discrepancies between the rendered images and sparse 2D DSA images. Without any neural network involved, TiAVox enjoys specific physical interpretability. The parameters of each learnable voxel represent the attenuation coefficients. We validated the TiAVox approach on both clinical and simulated datasets, achieving a 31.23 Peak Signal-to-Noise Ratio (PSNR) for novel view synthesis using only 30 views on the clinically sourced dataset, whereas traditional Feldkamp-Davis-Kress methods required 133 views. Similarly, with merely 10 views from the synthetic dataset, TiAVox yielded a PSNR of 34.32 for novel view synthesis and 41.40 for 3D reconstruction. We also executed ablation studies to corroborate the essential components of TiAVox. The code will be publically available.Comment: 10 pages, 8 figure

Does the Use of Antidepressants Accelerate the Disease Progress in Creutzfeldt–Jakob Disease Patients With Depression? A Case Report and A Systematic Review

Background: Creutzfeldt–Jakob disease (CJD) is a fatal neurodegenerative disorder characterized by rapidly progressive dementia. Growing evidence suggests that antidepressant usage was associated with dementia. Given the commonality of depression in CJD, it is necessary to investigate the effect of antidepressants on CJD.Methods: First, we report a case of sporadic CJD (sCJD) with depression where the condition worsened rapidly after using a serotonin and noradrenaline reuptake inhibitor (SNRI) antidepressant. Second, a systematic literature survey was conducted to investigate the effect of antidepressants on the survival time of sCJD patients with depression. Thirteen cases plus our case were included for qualitative analysis. Twelve subjects were included in the Kaplan–Meier survival and Cox regression analysis. Finally, we provide a postulation of pathophysiological mechanism in CJD.Results: The median survival time of all patients was 6.0 months, of which patients with SNRIs were significantly shorter than those with first-generation antidepressants (2.0 vs. 6.0 months; log rank, P = .008) and relatively shorter than those with nonselective serotonin reuptake inhibitors (SSRIs; 4.0 vs. 6.0 months; log rank, P = .090). In comparison with first-generation antidepressants, the use of SNRIs [hazard ratio (HR), 23.028; 95% confidence interval (CI), 1.401 to 378.461; P = .028] remained independently associated with shorter survival time.Conclusions: The use of antidepressants, especially SNRIs, was associated with a shorter survival time of sCJD patients. The possible changes in neurotransmitters should be emphasized. Scientifically, this study may provide insights into the mechanism of CJD. Clinically, it may contribute to the early diagnosis of CJD