Unsupervised Low Light Image Enhancement Using SNR-Aware Swin Transformer

Image captured under low-light conditions presents unpleasing artifacts, which debilitate the performance of feature extraction for many upstream visual tasks. Low-light image enhancement aims at improving brightness and contrast, and further reducing noise that corrupts the visual quality. Recently, many image restoration methods based on Swin Transformer have been proposed and achieve impressive performance. However, On one hand, trivially employing Swin Transformer for low-light image enhancement would expose some artifacts, including over-exposure, brightness imbalance and noise corruption, etc. On the other hand, it is impractical to capture image pairs of low-light images and corresponding ground-truth, i.e. well-exposed image in same visual scene. In this paper, we propose a dual-branch network based on Swin Transformer, guided by a signal-to-noise ratio prior map which provides the spatial-varying information for low-light image enhancement. Moreover, we leverage unsupervised learning to construct the optimization objective based on Retinex model, to guide the training of proposed network. Experimental results demonstrate that the proposed model is competitive with the baseline models

Plasma kinetics: Discrete Boltzmann modelling and Richtmyer-Meshkov instability

A discrete Boltzmann model (DBM) for plasma kinetics is proposed. The constructing of DBM mainly considers two aspects. The first is to build a physical model with sufficient physical functions before simulation. The second is to present schemes for extracting more valuable information from massive data after simulation. For the first aspect, the model is equivalent to a magnetohydrodynamic model plus a coarse-grained model for the most relevant TNE behaviors including the entropy production rate. A number of typical benchmark problems including Orszag-Tang (OT) vortex problem are used to verify the physical functions of DBM. For the second aspect, the DBM use non-conserved kinetic moments of (f-feq) to describe non-equilibrium state and behaviours of complex system. The OT vortex problem and the Richtmyer-Meshkov instability (RMI) are practical applications of the second aspect. For RMI with interface inverse and re-shock process, it is found that, in the case without magnetic field, the non-organized momentum flux shows the most pronounced effects near shock front, while the non-organized energy flux shows the most pronounced behaviors near perturbed interface. The influence of magnetic field on TNE effects shows stages: before the interface inverse, the TNE strength is enhanced by reducing the interface inverse speed; while after the interface inverse, the TNE strength is significantly reduced. Both the global average TNE strength and entropy production rate contributed by non-organized energy flux can be used as physical criteria to identify whether or not the magnetic field is sufficient to prevent the interface inverse.Comment: 20 pages, 15 figure

The GATA factor HANABA TARANU promotes runner formation by regulating axillary bud initiation and outgrowth in cultivated strawberry

A runner, as an elongated branch, develops from the axillary bud (AXB) in the leaf axil and is crucial for the clonal propagation of cultivated strawberry (Fragaria x ananassa Duch.). Runner formation occurs in at least two steps: AXB initiation and AXB outgrowth. HANABA TARANU (HAN ) encodes a GATA transcription factor that affects AXB initiation in Arabidopsis and promotes branching in grass species, but the underlying mechanism is largely unknown. Here, the function of a strawberry HAN homolog FaHAN in runner formation was characterized. FaHAN transcripts can be detected in the leaf axils. Overexpression (OE) of FaHAN increased the number of runners, mainly by enhancing AXB outgrowth, in strawberry. The expression of the strawberry homolog of BRANCHED1 , a key inhibitor of AXB outgrowth in many plant species, was significantly downregulated in the AXBs of FaHAN -OE lines, whereas the expression of the strawberry homolog of SHOOT MERISTEMLESS, a marker gene for AXB initiation in Arabidopsis, was upregulated. Moreover, several genes of gibberellin biosynthesis and cytokinin signaling pathways were activated, whereas the auxin response pathway genes were repressed. Further assays indicated that FaHAN could be directly activated by FaNAC2, the overexpression of which in strawberry also increased the number of runners. The silencing of FaNAC2 or FaHAN inhibited AXB initiation and led to a higher proportion of dormant AXBs, confirming their roles in the control of runner formation. Taken together, our results revealed a FaNAC2-FaHAN pathway in the control of runner formation and have provided a means to enhance the vegetative propagation of cultivated strawberry.Peer reviewe

Enhancing heat stress tolerance in Lanzhou lily (Lilium davidii var. unicolor) with Trichokonins isolated from Trichoderma longibrachiatum SMF2

Lanzhou lily (Lilium davidii var. unicolor) is a renowned edible crop produced in China and relatively sensitive to high temperature (HT). Trichokonins (TKs) are antimicrobial peptaibols secreted from Trichoderma longibrachiatum strain SMF2. Here, we report that TKs application improves the thermotolerance of Lanzhou lily. The activity of the antioxidant enzyme system (SOD, CAT, and POD), the level of heat-resistance-associated phytohormones (ABA, SA, and JA), the relative water content (RWC), the content of chlorophyll (Chl), and the net photosynthetic rate (Pn) were promoted by TKs treatment in Lanzhou lily plants subjected to heat stress (HS). TKs treatment also mitigated cell injury as shown by a lower accumulation of malondialdehyde (MDA) and relative electrolyte leakage (REL) under HS conditions. RNA-seq data analysis showed that more than 4.5 times differentially expressed genes (DEGs) responded to TKs treatment under HS compared to non-HS, and TKs treatment reduced protein folding and enhanced cellular repair function under HS conditions. The analyses of DEGs involved in hormone (ABA, SA and JA) synthesis and signaling pathways suggested that TKs might improve Lanzhou lily heat tolerance by promoting ABA synthesis and signal transduction. TKs highly induced DEGs of the HSF-HSP pathway under HS, in which HSFA2 accounted for most of the HSF family. Furthermore, TKs treatment resulted in the upregulation of heat-protective genes LzDREB2B, LzHsfA2a, LzMBF1c, LzHsp90, and LzHsp70 involved in HSF-HSP signal pathway after long-term HS. LzHsfA2a-1 likely plays a key role in acquisition of TKs-induced thermotolerance of Lanzhou lily as evidenced by the sustained response to HS, the enhanced response to TKs treatment under long-term HS, and the high sequence similarity to LlHsfA2a which is a key regulator for the improvement of heat tolerance in Lilium longiflorum. Our results reveal the underlying mechanisms of TKs-mediated thermotolerance in Lanzhou lily and highlight an attractive approach to protecting crop plants from damage caused by HS in a global warming future

Chromosome-level genome assembly of the largefin longbarbel catfish (Hemibagrus macropterus)

The largefin longbarbel catfish, Hemibagrus macropterus, is an economically important fish species in southwestern China, with males growing faster than females. This study presents a high-quality chromosome-level genome assembly of the largefin longbarbel catfish, generated by integrating Illumina short reads, PacBio HiFi long reads, and Hi-C data. The assembled genome size was 858.5 Mb, with a contig and scaffold N50 of 5.8 Mb and 28.4 Mb, respectively. A total of 656 contigs were successfully anchored to 30 pseudochromosomes with a BUSCO score of 97.7%, consistent with the number of chromosomes analyzed by karyotype. The genome contained 29.5% repeat sequences, and a predicted total of 26,613 protein-coding genes, of which 25,769 (96.8%) were functionally annotated in different databases. Evolutionary analysis showed that H. macropterus was most closely related to H. wyckioides, with a divergence time of approximately 16.3 million years. Chromosomal syntenic relationships among H. macropterus, H. wyckioides, and Pelteobagrus fulvidraco revealed a one-to-one relationship for most chromosomes, except for break, fission, and inversion of some chromosomes. The first high-quality reference genome will not only provide a valuable genetic resource for the study of sex determination mechanisms and genetic breeding of largefin longbarbel catfish, but also contribute to comparative analyses of genome and chromosome evolution within Siluriformes

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically-developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3-16 years of age underwent eight walking/running activities, including five 25 meters walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-minute walk test (6MWT), a 100 meters fast-walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens

Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime

The Chinese government recently proposed ammonia (NH3) emission reductions (but without a specific national target) as a strategic option to mitigate fine particulate matter (PM2.5) pollution. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas (SO2 and NOx) emissions. We found that PM2.5 concentrations decreased from 2000 to 2019, but annual mean PM2.5 concentrations still exceeded 35 µg m−3 at 74 % of 1498 monitoring sites during 2015–2019. The concentration of PM2.5 and its components were significantly higher (16 %–195 %) on hazy days than on non-hazy days. Compared with mean values of other components, this difference was more significant for the secondary inorganic ions SO, NO, and NH (average increase 98 %). While sulfate concentrations significantly decreased over this period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50 % NH3 emission reduction for controlling secondary inorganic aerosol (SIA) concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the COVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8 % lower than those in 2017. In addition, the reduction in SIA concentrations in 2017 was greater for 50 % acid gas reductions than for the 50 % NH3 emission reductions. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by emissions of acid gases, while an additional control of NH3 emissions would become more important as reductions of SO2 and NOx emissions progress

Trends in secondary inorganic aerosol pollution in China and its responses to emission controls of precursors in wintertime

The Chinese government recently proposed ammonia (NH3) emissions reductions (but without a specific national target) as a strategic option to mitigate PM2.5 pollution. We combined a meta-analysis of nationwide measurements and air quality modelling to identify efficiency gains by striking a balance between controlling NH3 and acid gas (SO2 and NOx) emissions. We found that PM2.5 concentrations decreased from 2000 to 2019, but annual mean PM2.5 concentrations still exceeded 35 µg m−3 at 74 % of 1498 monitoring sites in 2015–2019. Secondary inorganic aerosols (SIA) were the dominant contributor to ambient PM2.5 concentrations. While sulfate concentrations significantly decreased over the time period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50 % NH3 emission reduction for controlling SIA concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the CoVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8 % lower than that in 2017. In addition, the reduction of SIA concentrations in 2017 was greater for 50 % acid gas reductions than for the 50 % NH3 emissions reduction. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by acid gases emissions, while an additional control on NH3 emissions would become more important as reductions of SO2 and NOx emissions progress