Spatial separation of azimuthally and radially polarized beams from non-polarized light waves based on the electrically controlled birefringence effect.

Based on the electrically controlled birefringence effect in liquid crystal materials, an effective method for spatially separating azimuthally and radially polarized beams from non-polarized incident light waves is proposed. The radially polarized beam was highly converged by using a microhole-patterned electrode and a planar photo-alignment layer to shape the initial liquid-crystal radial alignment and a gradient refractive index distribution with central axial symmetry after applying a voltage signal. Due to the intrinsic polarization sensitivity of nematic liquid-crystal materials, the shaped gradient refractive index only applies to extraordinary light waves, which then converge into a spot. Thus, the azimuthally and radially polarized beams are effectively separated. The proposed method demonstrates some advantages, such as low cost, miniaturization, and easy fabrication and integration with other functional devices. Thanks to the wideband electrically controlled birefringence of liquid-crystal materials, this light-wave manipulation to spatially separate azimuthally and radially polarized beams can also be performed over a wide wavelength range.

The ratio of length at first maturity to maximum length across marine and freshwater fishes.

The prevailing determinant of maturation in fishes is thought to be a redirection of energy from growth to reproduction. Instead, the Gill Oxygen Limitation Theory predicts that maturation, and thus reproduction, is induced when a fish reaches a critical ratio of oxygen supply to demand (Qm /Qmaint ). The consistency of this critical ratio has been previously documented in many fishes, but a broader test was lacking. In this study, the authors assess if this critical ratio is consistent across 132 unique fish species, as measured by the slope of the relationship between Lmax D and Lm D , where Lmax is the maximum length reached in a given population, Lm is the mean size at first maturity in that population and D is a gill-related exponent which renders the Lmax D /Lm D ratio equivalent to the Qm /Qmaint ratio. The authors found that across all species, the Lmax D /Lm D ratio was 1.40 (95% c.i. 1.38-1.42), which was not significantly different from that previously estimated across other species groups (1.35, 95% c.i. 1.22-1.53), especially when phylogenetic relationships were considered (1.25, 95% Bayesian credible interval 1.09-1.40). The consistency of the Lmax D /Lm D ratio across taxa, which expresses the difference in metabolic rate at maturity and maximum size, suggests that the scaling of gill surface area is the factor that underlies this ratio, and which triggers the maturation in fishes.

Arrayed dual-mode integrated liquid crystal microlens driven jointly by both independent signal voltages.

A new type of liquid crystal microlens array (LCMLA) constructed by a single-layered LC material is proposed. The basic dual-mode integrated LC microlens includes a concentric microhole electrode and a central plate electrode. Compared with traditional LC microlenses driven electrically, the dual-mode integrated LC microlens presents a better light control effect, such as being flexibly adjusted between the beam convergence and divergence modes, enlarging both the tunable range of the signal voltage and the focal length and also reducing the focal spot assisted by a convex electric-field generated by the central plate electrode, acquiring a sharper beam diverging microring formed by the concave LC microlens assisted by a concave electric-field generated by the microhole electrode. At the same time, we have also verified that the electric-field filling factor of the dual-mode integrated LCMLA can be obviously increased through jointly tuning the signal voltages applied independently over both the microhole electrode and the central plate electrode. This research has laid a solid foundation for continuously developing LCMLA technology.

Antibacterial mechanism of metabolites of Lactobacillus plantarum against Pseudomonas lundensis and their application in dry-aged beef preservation.

In this study, the antibacterial mechanism of metabolites of Lactobacillus plantarum SCB2505 (MLp SCB2505) against Pseudomonas lundensis (P. lundensis) SCB2605 was investigated, along with evaluation of their preservative effects on dry-aged beef. The results demonstrated the effective inhibition of MLp SCB2505 on the growth and biofilm synthesis of P. lundensis. The treatment with MLp SCB2505 led to the compromised membrane integrity, as evidenced by reduced intracellular ATP content, increased extracellular AKPase, K+ and protein content, as well as disrupted cell morphology. Further metabolomics analysis revealed that MLp SCB2505 interfered amino acid metabolism, nucleotide metabolism, cofactor and vitamin metabolism, lipid metabolism and respiratory chain in P. lundensis, ultimately leading to the interrupted life activities and even death of the bacteria. Besides, MLp SCB2505 could effectively inhibit the growth of Pseudomonas in dry-aged beef and delay spoilage. These findings propose the potential application of MLp SCB2505 as an antibacterial agent in meat products.

Sex-specific effects of intermittent fasting on hippocampal neurogenesis via the gut-brain axis.

Intermittent fasting (IF) is a widely used dietary strategy that has shown several advantageous impacts on general health and aging. IF has recently been linked to the control of neurogenesis, a crucial process for emotional control, memory, and learning, in the hippocampus. Nevertheless, there is little knowledge about the sex-specific impacts of IF on hippocampal neurogenesis and the related mechanisms, which were investigated in this study among both male and female rats, together with analyzing the involvement of the flora-gut-brain axis in facilitating these effects. Our findings show that IF favorably affects hippocampus neurogenesis in female mice relative to male mice, suggesting a sex-specific mechanism. In addition, IF influenced the diversity of the gut microbiota and decreased the synthesis of fructose-1-phosphate (F-1-P), which is believed together with fructose metabolism to be linked to neurological damage and cognitive decline. Collectively, these data indicate that the connection between the flora-gut-brain axis and hippocampus neurogenesis is significant.

Association of Work Stress With Anxiety and Depression Among Adults in Wuhan, China: The Mediating Role of Job Satisfaction.

OBJECTIVE: This study aimed to explore the relationship of work stress with anxiety and depression and the mediation of job satisfaction. METHODS: We conducted a survey among gas station workers in Wuhan, China. Multivariate and bootstrap mediating analyses were conducted. RESULTS: The rate of effort-reward imbalance, overcommitment (OC), anxiety, and depression were 22.9%, 29.2%, 20.1%, and 19.9%. Work stress was positively associated with anxiety ( ß = 0.213 [95% confidence interval (CI), 0.156-0.270] for logarithmic effort-reward ratio [LgERR] and ß = 0.563 [95% CI, 0.505-0.621] for OC) and depression ( ß = 0.291 [95% CI, 0.227-0.356] for LgERR and ß = 0.417 [95% CI, 0.351-0.483] for OC). The mediation of job satisfaction from LgERR and OC to anxiety and depression were 14.93%, 9.05%, 24.34%, and 19.85%. CONCLUSIONS: We should concern the anxiety and depression, and work stress status of workers and improve the situation by improving job satisfaction.

Interactions of multiple stressors on the Bombay-duck Harpadon nehereus population in a complex estuarine ecosystem.

In an era marked by unprecedented anthropogenic change, marine systems are increasingly subjected to interconnected and dynamic external stressors, which profoundly reshape the behavior and resilience of marine ecological components. Nevertheless, despite widespread recognition of the significance of stressor interactions, there persist notable knowledge deficits in quantifying their interactions and the specific biological consequences that result. To bridge this crucial gap, this research detected and examined the causal relationships between five key exogenous stressors in a complex estuarine ecosystem. Furthermore, a Bayesian Hierarchical Spatio-temporal modeling framework was proposed to quantitatively evaluate the distinct, interactive, and globally sensitive effects of multiple stressors on the population dynamics of a crucial fish species: Harpadon nehereus. The results showed that interactions were detected between fisheries pressure (FP), the Pacific Decadal Oscillation index (PDO), runoff volume (RV), and sediment load (SL), with five of these interactions producing significant synergistic effects on H. nehereus biomass. The SL*PDO and RV*PDO interactions had positive synergistic effects, albeit through differing processes. The former interaction amplified the individual effects of each stressor, while the latter reversed the direction of the original impact. Indeed overall, the synergistic effect of multiple stressors was not favorable, with FP in particular posing the greatest threat to H. nehereus population. This threat was more pronounced at high SL or negative PDO phases. Therefore, local management efforts aimed at addressing multiple stressors and protecting resources should consider the findings. Additionally, although the velocity of climate change (VoCC) failed to produce significant interactions, changes in this stressor had the most sensitive impacts on the response of H. nehereus population. This research strives to enhance the dimensionality, generalizability, and flexibility of the quantification framework for marine multi-stressor interactions, aiming to foster broader research collaboration and jointly tackle the intricate pressures facing marine ecosystems.

Pancreatic cancer pathology image segmentation with channel and spatial long-range dependencies.

Based on deep learning, pancreatic cancer pathology image segmentation technology effectively assists pathologists in achieving improved treatment outcomes. However, compared to traditional image segmentation tasks, the large size of tissues in pathology images requires a larger receptive field. While methods based on dilated convolutions or attention mechanisms can enhance the receptive field, they cannot capture long-range feature dependencies. Directly applying self-attention mechanisms to capture long-range dependencies results in intolerable computational complexity. To address these challenges, we introduce a channel and spatial self-attention (CS) Module designed for efficiently capturing both channel and spatial long-range feature dependencies in pancreatic cancer pathological images. Specifically, the channel and spatial self-attention module consists of an adaptive channel self-attention module and a window-shift spatial self-attention module. The adaptive channel self-attention module adaptively pools features to a fixed size to capture long-range feature dependencies. While the window-shift spatial self-attention module captures spatial long-range dependencies in a window-based manner. Additionally, we propose a re-weighted cross-entropy loss to mitigate the impact of long-tail distribution on performance. Our proposed method surpasses state-of-the-art on both our Pancreatic Cancer Pathology Image (PCPI) dataset and the GlaS challenge dataset. The mDice and mIoU have achieved 73.93% and 59.42% in our PCPI dataset.

High-Matching and Low-Cost Realization of the FHN Neuron Model on Reconfigurable FPGA Board.

The main objectives of neuromorphic engineering are the research, modeling, and implementation of neural functioning in the human brain. We provide a hardware solution that can replicate such a nature-inspired system by merging multiple scientific domains and is based on neural cell processes. This work provides a modified version of the original Fitz-Hugh Nagumo (FHN) neuron using a simple 2V term called Hybrid Piece-Wised Base-2 Model (HPWBM), which accurately reproduces numerous patterns of the original neuron model. With reduced terms, we suggest modifying the original nonlinear term to achieve high matching accuracy and little computing error. Time domain and phase portraits are used to validate the proposed model, which shows that it can reproduce all of the FHN model's properties with high accuracy and little mistake. We provide an effective digital hardware approach for large-scale neuron implementations based on resource-sharing and pipelining strategies. The Hardware Description Language (HDL) is used to construct the hardware on an FPGA as a proof of concept. The recommended model hardly uses 0.48 percent of the resources on a Virtex 4 FPGA board, according to the results of the hardware implementation. The circuit can run at a maximum frequency of 448.236 MHz, according to the static timing study.

Serum metabolome perturbation in relation to noise exposure: Exploring the potential role of serum metabolites in noise-induced arterial stiffness.

Noise pollution has grown to be a major public health issue worldwide. We sought to profile serum metabolite expression changes related to occupational noise exposure by untargeted metabolomics, as well as to evaluate the potential roles of serum metabolites in occupational noise-associated arterial stiffness (AS). Our study involved 30 noise-exposed industrial personnel (Lipo group) and 30 noise-free controls (Blank group). The untargeted metabolomic analysis was performed by employing a UPLC-HRMS. The associations of occupational noise and significant differential metabolites (between Blank/Lipo groups) with AS were evaluated using multivariable-adjusted generalized linear models. We performed the least absolute shrinkage and selection operator regression analysis to further screen for AS's risk metabolites. We explored 177 metabolites across 21 categories significantly differentially expressed between Blank/Lipo groups, and these metabolites were enriched in 20 metabolic pathways. Moreover, 15 metabolites in 4 classes (including food, glycerophosphocholine, sphingomyelin [SM] and triacylglycerols [TAG]) were adversely associated with AS (all P < 0.05). Meanwhile, five metabolites (homostachydrine, phosphatidylcholine (PC) (32:1e), PC (38:6p), SM (d41:2) and TAG (45:1) have been proven to be useful predictors of AS prevalence. However, none of these 15 metabolites were found to have a mediating influence on occupational noise-induced AS. Our study reveals specific metabolic changes caused by occupational noise exposure, and several metabolites may have protective effects on AS. However, the roles of serum metabolites in noise-AS association remain to be validated in future studies.

Association of noise exposure, plasma microRNAs with metabolic syndrome and its components among Chinese adults.

AIMS: We aimed to evaluate the association of occupational noise with metabolic syndrome (MetS) and its components, and to assess the potential role of miRNAs in occupational noise-associated MetS. METHODS: A total of 854 participants were enrolled in our study. Cumulative noise exposure (CNE) was estimated in conjunction with workplace noise test records and research participants' employment histories. Logistic regression models adjusted for potential confounders were used to assess the association of CNE and miRNAs with MetS and its components. RESULTS: We observed linear positive dose-response associations between occupational noise exposure and the prevalence of MetS (OR: 1.031; 95 % CI: 1.008, 1.055). And linear and nonlinear relationship were also found for the association of occupational noise exposure with high blood pressure (OR: 1.024; 95 % CI: 1.007, 1.041) and reduced high-density lipoprotein (OR: 1.051; 95 % CI: 1.031, 1.072), respectively. MiR-200a-3p, miR-92a-3p and miR-21-5p were inversely associated with CNE, or the prevalence of MetS and its components (all P < 0.05). However, we did not find any statistically significant mediation effect of miRNAs in the associations of CNE with MetS. Furthermore, the prevalence of bilateral hearing loss in high-frequency increased (OR: 1.036; 95 % CI: 1.008, 1.067) with CNE level rising, and participants with bilateral hearing loss in high-frequency had a significantly higher risk of MetS (OR: 1.727; 95 % CI: 1.048, 2.819). CONCLUSION: Our study suggests that occupational noise exposure is associated with MetS and its components, and the role of miRNAs in noise-induced increasing MetS risk needs to be confirmed in future studies.

Learning Graph Convolutional Networks for Multi-Label Recognition and Applications.

The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model the label dependencies to improve the recognition performance. To capture and explore such important information, we propose graph convolutional networks (GCNs) based models for multi-label image recognition, where directed graphs are constructed over classes and information is propagated between classes to learn inter-dependent class-level representations. Following this idea, we design two particular models that approach multi-label classification from different views. In our first model, the prior knowledge about the class dependencies is integrated into classifier learning. Specifically, we propose Classifier Learning GCN (C-GCN) to map class-level semantic representations (e.g., word embeddings) into classifiers that maintain the inter-class topology. In our second model, we decompose the visual representation of an image into a set of label-aware features and propose prediction learning GCN (P-GCN) to encode such features into inter-dependent image-level prediction scores. Furthermore, we also present an effective correlation matrix construction approach to capture inter-class relationships and consequently guide information propagation among classes. Empirical results on generic multi-label image recognition demonstrate that both of the proposed models can obviously outperform other existing state-of-the-arts. Moreover, the proposed methods also show advantages in some other multi-label classification related applications.

Association of vitamins with hearing loss, vision disorder and sleep problem in the US general population.

Based on nationally representative samples from US, we aimed to assess the associations of vitamins with hearing loss, vision disorder and sleep problem. A total of 25,312, 8425 and 24,234 participants were included in this study to investigate the relationship of vitamins with hearing loss, vision disorder and sleep problem from National Health and Nutrition Examination Survey, respectively. Vitamins including niacin, folic acid, vitamin B6, A, C, E and carotenoids were considered in our study. Logistic regression models were used to assess the associations between all included dietary vitamin intake concentrations and the prevalence of specific outcomes. Increased lycopene (odds ratio [OR]: 0.904, 95% confidence interval [CI]: 0.829-0.985) intake was associated with a deceased prevalence of hearing loss. Higher dietary intake of folic acid (OR: 0.637, 95% CI: 0.443-0.904), vitamin B6 (0.667, 0.465-0.947), alpha-carotene (0.695, 0.494-0.968), beta-carotene (0.703, 0.505-0.969) and lutein + zeaxanthin (0.640, 0.455-0.892) were associated with a decreased prevalence of vision disorder. The inversely associations of sleeping problem with niacin (OR: 0.902, 95% CI: 0.826-0.985), folic acid (0.882, 0.811-0.959), vitamin B6 (0.892, 0.818-0.973), vitamin C (0.908, 0.835-0.987), vitamin E (0.885, 0.813-0.963) and lycopene (0.919, 0.845-0.998) were also observed. Our findings provide evidence that increased specific vitamin intake is associated with decreased prevalence of hearing loss, vision disorder and sleep problem.

Bioinspired rotary flight of light-driven composite films.

Light-driven actuators have great potential in different types of applications. However, it is still challenging to apply them in flying devices owing to their slow response, small deflection and force output and low frequency response. Herein, inspired by the structure of vine maple seeds, we report a helicopter-like rotary flying photoactuator (in response to 0.6 W/cm2 near-infrared (NIR) light) with ultrafast rotation (~7200 revolutions per minute) and rapid response (~650 ms). This photoactuator is operated based on a fundamentally different mechanism that depends on the synergistic interactions between the photothermal graphene and the hygroscopic agar/silk fibroin components, the subsequent aerodynamically favorable airscrew formation, the jet propulsion, and the aerodynamics-based flying. The soft helicopter-like photoactuator exhibits controlled flight and steering behaviors, making it promising for applications in soft robotics and other miniature devices.

Induction of detoxification enzymes by quercetin in the silkworm.

Quercetin is one of the most abundant flavonoids and the defense secondary metabolites in plants. In this study, the effect of quercetin on the growth of the silkworm larvae was investigated. Cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs), and carboxylesterases (COE) were assayed after exposure to different concentrations of quercetin for 3 d (short-term) and 7 d (long-term), respectively. The results showed that the weight gain of the silkworm larvae significantly decreased after the larvae were treated by different concentrations of quercetin except for the treatment with 0.5% quercetin. Activities of P450, GST, and COE were induced by 0.5 or 1% concentration of quercetin. In the midgut, the induction activity of P450s was reached to the highest level (2.3-fold) by 1% quercetin for 7 d, the highest induction activities of GSTs toward CHP and CDNB were 4.1-fold and 2.6-fold of controls by 1% quercetin after 7 d exposure, respectively. For COEs, the highest activity (2.3-fold) was induced by 0.5% quercetin for 7 d. However, P450s in whole body were higher inducible activities in short-term treatment than those in long-term treatment. The responses of eight cytochrome P450 (CYP) genes belonged to CYP6 and CYP9 families and seven GST genes were detected with real-time polymerase chain reaction. In addition, the genes induced by quercetin significantly were confirmed by qRT-PCR. CYP6AB5, CYP6B29, and GSTe8 were identified as inducible genes, of which the highest induction levels were 10.9-fold (0.5% quercetin for 7 d), 6.2-fold (1% quercetin for 7 d), and 7.1-fold (1% quercetin for 7 d), respectively.

SST: Spatial and Semantic Transformers for Multi-Label Image Recognition.

Multi-label image recognition has attracted considerable research attention and achieved great success in recent years. Capturing label correlations is an effective manner to advance the performance of multi-label image recognition. Two types of label correlations were principally studied, i.e., the spatial and semantic correlations. However, in the literature, previous methods considered only either of them. In this work, inspired by the great success of Transformer, we propose a plug-and-play module, named the Spatial and Semantic Transformers (SST), to simultaneously capture spatial and semantic correlations in multi-label images. Our proposal is mainly comprised of two independent transformers, aiming to capture the spatial and semantic correlations respectively. Specifically, our Spatial Transformer is designed to model the correlations between features from different spatial positions, while the Semantic Transformer is leveraged to capture the co-existence of labels without manually defined rules. Other than methodological contributions, we also prove that spatial and semantic correlations complement each other and deserve to be leveraged simultaneously in multi-label image recognition. Benefitting from the Transformer's ability to capture long-range correlations, our method remarkably outperforms state-of-the-art methods on four popular multi-label benchmark datasets. In addition, extensive ablation studies and visualizations are provided to validate the essential components of our method.

HCE: Hierarchical Context Embedding for Region-Based Object Detection.

State-of-the-art two-stage object detectors apply a classifier to a sparse set of object proposals, relying on region-wise features extracted by RoIPool or RoIAlign as inputs. The region-wise features, in spite of aligning well with the proposal locations, may still lack the crucial context information which is necessary for filtering out noisy background detections, as well as recognizing objects possessing no distinctive appearances. To address this issue, we present a simple but effective Hierarchical Context Embedding (HCE) framework, which can be applied as a plug-and-play component, to facilitate the classification ability of a series of region-based detectors by mining contextual cues. Specifically, to advance the recognition of context-dependent object categories, we propose an image-level categorical embedding module which leverages the holistic image-level context to learn object-level concepts. Then, novel RoI features are generated by exploiting hierarchically embedded context information beneath both whole images and interested regions, which are also complementary to conventional RoI features. Moreover, to make full use of our hierarchical contextual RoI features, we propose the early-and-late fusion strategies (i.e., feature fusion and confidence fusion), which can be combined to boost the classification accuracy of region-based detectors. Comprehensive experiments demonstrate that our HCE framework is flexible and generalizable, leading to significant and consistent improvements upon various region-based detectors, including FPN, Cascade R-CNN, Mask R-CNN and PA-FPN. With simple modification, our HCE framework can be conveniently adapted to fit the structure of one-stage detectors, and achieve improved performance for SSD, RetinaNet and EfficientDet.

Polyaniline/Carbon Dots Composite as a Highly Efficient Metal-Free Dual-Functional Photoassisted Electrocatalyst for Overall Water Splitting.

Photoassisted electrocatalytic (P-EC) water splitting for H2 production has received much attention. Here, we report a metal-free bifunctional photoassisted catalyst of a polyaniline/carbon dots (PANI/CDs) composite for overall water splitting. In a neutral electrolyte, under visible light, the overpotentials of the oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) for PANI/CDs/NF are reduced by 150 and 65 mV to reach the current densities of 30 and 20 mA cm-2, respectively. In a full water-splitting cell, under visible light, the current density is 13.27 mA cm-2 at 2.0 V, which increases by 62.8% compared with that under the dark conditions (8.15 mA cm-2). The in situ transient photovoltage (TPV) tests were used to study the light-induced effects on half-reactions of water splitting, as well as the charge-transfer kinetic characteristics at the catalyst interface.

A Band-Pass Filter Based on Half-Mode Substrate Integrated Waveguide and Spoof Surface Plasmon Polaritons.

In this paper, a band-pass filter based on half-mode substrate integrated waveguide (HMSIW) and double-layer spoof surface plasmon polaritons (SSPPs) consisting of two corrugated metal strips is proposed, which can realize band-pass transmission by etching periodic grooves at the top and bottom metal layers of the HMSIW. Moreover, the influences of important parameters on the performance of the proposed band-pass filter are analyzed by parametric study. By changing the key parameters, the low and high cut-off frequency can be controlled independently. The corresponding equivalent circuit of the proposed band-pass filter is put forward to explain the physical mechanism. Compared with the previous structures, this structure features smaller size, wider bandwidth and lower loss. Simulated results show that the proposed band-pass filter achieves a bandwidth (for |S11| < -10 dB and |S21| > -0.8 dB) of about 69.77% (15.6-32.1 GHz). The measured results have good agreements with the simulated ones, which verify that the proposed band-pass filter has good performances and potential applications at the microwave frequencies.