Effects of red light on sleep and mood in healthy subjects and individuals with insomnia disorder

IntroductionThis study aimed to determine the influence of red light on objective sleep and the relationship between mood and sleep among individuals with insomnia disorder (ID).Method57 individuals with insomnia symptoms and 57 healthy participants were randomly divided into three groups (red- and white-light groups, and the black control group), which received different light treatments for 1 h before bedtime. The emotions and subjective alertness of participants were evaluated using Positive and Negative Affect Schedule scales (PANAS) and Karolinska Sleepiness Scale (KSS), their sleeping data were recorded using polysomnography (PSG).ResultThe negative emotion scores were higher in the healthy subject-red light (HS-RL) group than in the HS-white light (WL) and HS-black control (BC) groups (p < 0.001). The anxiety and negative emotion scores were higher in the ID-RL group than in the ID-WL and ID-BC groups (p = 0.007 and p < 0.001, respectively). The KSS scores were lower in the RL group than in the WL and BC groups for both HS and ID group (both p < 0.001). The SOL was shorter in the HS-RL group than in HS-WL group (p = 0.019). Compared with the HS-BC group, the HS-RL group had an increase in microarousal index (MAI) and N1% (p = 0.034 and p = 0.021, respectively), while the total sleep time (TST) and sleep efficiency (SE) decreased (p = 0.001 and p < 0.001, respectively). Compared with the ID-WL group, the SOL was shorter in the ID-RL group (p = 0.043), while TST, SE, number of microarousals (NMA), and numbers of cycles of REM period were increased (p = 0.016, p = 0.046, p = 0.001, and p = 0.041, respectively). Compared with the ID-BC group, the ID-RL group had increases in the SOL, WASO, and the numbers of cycles and NMA in REM period (p = 0.038, p = 0.005, p = 0.045, and p = 0.033, respectively), and a decrease in SE (p = 0.014). The effects of ID-WL (vs. ID-RL group) and ID-BC (vs. ID-RL group) on SOL were mediated by negative emotions (mediating effects were − 37.626 and − 33.768, respectively).ConclusionRed light can increase subjective alertness, anxiety, and negative emotions in both healthy subjects and people with ID, which can affect sleep directly or indirectly via the mediating effect of negative emotions

Robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization

Non-negative matrix factorization (NMF) has been widely used in machine learning and data mining fields. As an extension of NMF, non-negative matrix tri-factorization (NMTF) provides more degrees of freedom than NMF. However, standard NMTF algorithm utilizes Frobenius norm to calculate residual error, which can be dramatically affected by noise and outliers. Moreover, the hidden geometric information in feature manifold and sample manifold is rarely learned. Hence, a novel robust capped norm dual hyper-graph regularized non-negative matrix tri-factorization (RCHNMTF) is proposed. First, a robust capped norm is adopted to handle extreme outliers. Second, dual hyper-graph regularization is considered to exploit intrinsic geometric information in feature manifold and sample manifold. Third, orthogonality constraints are added to learn unique data presentation and improve clustering performance. The experiments on seven datasets testify the robustness and superiority of RCHNMTF

Associations of Educational Attainment, Occupation, Social Class and Major Depressive Disorder among Han Chinese Women

Background The prevalence of major depressive disorder (MDD) is higher in those with low levels of educational attainment, the unemployed and those with low social status. However the extent to which these factors cause MDD is unclear. Most of the available data comes from studies in developed countries, and these findings may not extrapolate to developing countries. Examining the relationship between MDD and socio economic status in China is likely to add to the debate because of the radical economic and social changes occurring in China over the last 30 years. Principal findings We report results from 3,639 Chinese women with recurrent MDD and 3,800 controls. Highly significant odds ratios (ORs) were observed between MDD and full time employment (OR = 0.36, 95% CI = 0.25–0.46, logP = 78), social status (OR = 0.83, 95% CI = 0.77–0.87, logP = 13.3) and education attainment (OR = 0.90, 95% CI = 0.86–0.90, logP = 6.8). We found a monotonic relationship between increasing age and increasing levels of educational attainment. Those with only primary school education have significantly more episodes of MDD (mean 6.5, P-value = 0.009) and have a clinically more severe disorder, while those with higher educational attainment are likely to manifest more comorbid anxiety disorders. Conclusions In China lower socioeconomic position is associated with increased rates of MDD, as it is elsewhere in the world. Significantly more episodes of MDD occur among those with lower educational attainment (rather than longer episodes of disease), consistent with the hypothesis that the lower socioeconomic position increases the likelihood of developing MDD. The phenomenology of MDD varies according to the degree of educational attainment: higher educational attainment not only appears to protect against MDD but alters its presentation, to a more anxious phenotype

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Monitoring of Wind Effects on a Super-Tall Building under a Typhoon

Field measurements are critical to further understand the structural behavior of super-tall buildings under strong wind actions. This paper presents field measurements that reflect the wind characteristics and wind effects on Leatop Plaza under Typhoon Vicente. Wind field characteristics, including the turbulence intensity, gust factor, and power spectral density of wind speed in an urban area, were obtained on the basis of a statistical analysis of measured wind data. Subsequently, measured wind-induced accelerations were used to evaluate the dynamic characteristics of the building and the effects of wind on it. On the basis of the first several modes, the modal properties, i.e., the natural frequency and damping ratio, were identified via the fast Bayesian fast Fourier transform method and compared with those identified using the stochastic subspace method. The discrepancy between the identified results and finite element model predictions is presented and discussed. Finally, the variation in the modal parameters with respect to time and the vibration amplitude was analyzed while considering the associated posterior uncertainty

Recent advances in self-frequency-doubling crystals

The self-frequency-doubling (SFD) crystal is a representative of multifunctional crystals. In recent years, SFD crystals and lasers have gained renewed attention based on the progress on SFD crystals and lasers and Nd:RECa4O(BO3)3 (RE = Y or Gd) crystals, with SFD lasers becoming commercial products. Here, we review the advances of SFD crystals and lasers, including the basic selection rules, theoretical analysis and recent progress of some potential SFD crystals and lasers. The Nd:RECa4O(BO3)3 crystals and lasers are highlighted, and their applications are also proposed and discussed, which may provide some inspiration for the further development of the SFD field and multifunctional materials

Structure Tensor-Based Infrared Small Target Detection Method for a Double Linear Array Detector

The paper focuses on the mathematical modeling of a new double linear array detector. The special feature of the detector is that image pairs can be generated at short intervals in one scan. After registration and removal of dynamic cloud edges in each image, the image differentiation-based change detection method in the temporal domain is proposed to combine with the structure tensor edge suppression method in the spatial domain. Finally, experiments are conducted, and our results are compared with theoretic analyses. It is found that a high signal-to-clutter ratio (SCR) of camera input is required to obtain an acceptable detection rate and false alarm rate in real scenes. Experimental results also show that the proposed cloud edge removal solution can be used to successfully detect targets with a very low false alarm rate and an acceptable detection rate

Structure Tensor-Based Infrared Small Target Detection Method for a Double Linear Array Detector

The paper focuses on the mathematical modeling of a new double linear array detector. The special feature of the detector is that image pairs can be generated at short intervals in one scan. After registration and removal of dynamic cloud edges in each image, the image differentiation-based change detection method in the temporal domain is proposed to combine with the structure tensor edge suppression method in the spatial domain. Finally, experiments are conducted, and our results are compared with theoretic analyses. It is found that a high signal-to-clutter ratio (SCR) of camera input is required to obtain an acceptable detection rate and false alarm rate in real scenes. Experimental results also show that the proposed cloud edge removal solution can be used to successfully detect targets with a very low false alarm rate and an acceptable detection rate

Hybrid CNN-Transformer Feature Fusion for Single Image Deraining

Since rain streaks exhibit diverse geometric appearances and irregular overlapped phenomena, these complex characteristics challenge the design of an effective single image deraining model. To this end, rich local-global information representations are increasingly indispensable for better satisfying rain removal. In this paper, we propose a lightweight Hybrid CNN-Transformer Feature Fusion Network (dubbed as HCT-FFN) in a stage-by-stage progressive manner, which can harmonize these two architectures to help image restoration by leveraging their individual learning strengths. Specifically, we stack a sequence of the degradation-aware mixture of experts (DaMoE) modules in the CNN-based stage, where appropriate local experts adaptively enable the model to emphasize spatially-varying rain distribution features. As for the Transformer-based stage, a background-aware vision Transformer (BaViT) module is employed to complement spatially-long feature dependencies of images, so as to achieve global texture recovery while preserving the required structure. Considering the indeterminate knowledge discrepancy among CNN features and Transformer features, we introduce an interactive fusion branch at adjacent stages to further facilitate the reconstruction of high-quality deraining results. Extensive evaluations show the effectiveness and extensibility of our developed HCT-FFN. The source code is available at https://github.com/cschenxiang/HCT-FFN