DLP-GAN: learning to draw modern Chinese landscape photos with generative adversarial network

Chinese landscape painting has a unique and artistic style, and its drawing technique is highly abstract in both the use of color and the realistic representation of objects. Previous methods focus on transferring from modern photos to ancient ink paintings. However, little attention has been paid to translating landscape paintings into modern photos. To solve such problems, in this paper, we (1) propose DLP-GAN (Draw Modern Chinese Landscape Photos with Generative Adversarial Network), an unsupervised cross-domain image translation framework with a novel asymmetric cycle mapping, and (2) introduce a generator based on a dense-fusion module to match different translation directions. Moreover, a dual-consistency loss is proposed to balance the realism and abstraction of model painting. In this way, our model can draw landscape photos and sketches in the modern sense. Finally, based on our collection of modern landscape and sketch datasets, we compare the images generated by our model with other benchmarks. Extensive experiments including user studies show that our model outperforms state-of-the-art methods.Comment: Corrected typo

Large-scale power inspection: A deep reinforcement learning approach

Power inspection plays an important role in ensuring the normal operation of the power grid. However, inspection of transmission lines in an unoccupied area is time-consuming and labor-intensive. Recently, unmanned aerial vehicle (UAV) inspection has attracted remarkable attention in the space-ground collaborative smart grid, where UAVs are able to provide full converge of patrol points on transmission lines without the limitation of communication and manpower. Nevertheless, how to schedule UAVs to traverse numerous, dispersed target nodes in a vast area with the least cost (e.g., time consumption and total distance) has rarely been studied. In this paper, we focus on this challenging and practical issue which can be considered as a family of vehicle routing problems (VRPs) with regard to different constraints, and propose a Diverse Trajectory-driven Deep Reinforcement Learning (DT-DRL) approach with encoder-decoder scheme to tackle it. First, we bring in a threshold unit in our encoder for better state representation. Secondly, we realize that the already visited nodes have no impact on future decisions, and then devise a dynamic-aware context embedding which removes irrelevant nodes to trace the current graph. Finally, we introduce multiply decoders with identical structure but unshared parameters, and design a Kullback-Leibler divergence based regular term to enforce decoders to output diverse trajectories, which expands the search space and enhances the routing performance. Comprehensive experiments on five types of routing problems show that our approach consistently outperforms both DRL and heuristic methods by a clear margin

A volume first maxima-finding algorithm

AbstractThe maxima-finding is a fundamental problem in computational geometry with many applications. In this paper, a volume first maxima-finding algorithm is proposed. It is proved that the expected running time of the algorithm is N+o(N) when choosing points from CI distribution, which is a new theoretical result when the points belong to d(>2) dimensional space. Experimental results and theoretical analysis indicate that the algorithm runs faster than the Move-To-Front maxima-finding algorithm

The Effects of Natural Window Views in Classrooms on College Students’ Mood and Learning Efficiency

Observing peaceful natural environments has been shown to restore cognitive abilities and reduce stress. As a result, visual access to natural environments is becoming increasingly common in educational settings. However, most current research on classroom window views has examined classroom environments in elementary and secondary schools, and only some university classrooms have been used as study sites. This study investigated the relationship between the naturalness of university classroom window views and physiological and emotional responses and standardized tests of attentional focus (learning efficiency) in university students. Thirty participants (undergraduates 21.16 ± 1.01 years old) viewed architectural window views and natural window views for 3 min each, and physiological measures of EEG, HRV index, and psychometric measures of Semantic Differences Questionnaire and Emotional State Questionnaire generated data. Measurements were generated. The results indicated that the natural window view significantly enhanced theta, alpha, and beta waves of brain activity, provided a sense of comfort, relaxation, and pleasure, and increased learning efficiency compared to the architectural window view. The findings support the beneficial associations between window views on university campuses and students’ mood and learning efficiency, emphasizing the importance of considering natural window views in the planning and designing of university classrooms

The association of a frailty index derived from laboratory tests and vital signs with clinical outcomes in critical care patients with septic shock: a retrospective study based on the MIMIC-IV database

Abstract Purpose Frailty is a vulnerable state to stressors due to the loss of physiological reserve as a result of multisystem dysfunction. The physiological and laboratory-based frailty index (FI-Lab), depending on laboratory values and vital signs, is a powerful tool to capture frailty status. The aim of this study was to assess the relationship between FI-Lab and in-hospital mortality in patients with septic shock. Methods Baseline data for patients with sepsis in the intensive care unit were retrieved from the Critical Care Medicine Database (MIMIC-IV, v2.2). The primary outcome was mortality during hospitalization. The propensity score matching (PSM) method was used to analyze the basic conditions during hospitalization between groups.The FI-Lab was analysed for its relationship with in-hospital mortality using logistic regression according to continuous and categorical variables, respectively, and described using the restricted cubic spline (RCS). Survival was compared between groups using Kaplan-Meier (KM) curves. Subgroup analyses were used to improve the stability of the results. Results A total of 9219 patients were included. A cohort score of 1803 matched patients was generated after PSM. The analyses showed that non-surviving patients with septic shock in the ICU had a high FI-Lab index (P<0.001). FI-Lab, whether used as a continuous or categorical variable, increased with increasing FI-Lab and increased in-hospital mortality (P<0.001).Subgroup analyses showed similar results. RCS depicts this non-linear relationship. KM analysis shows the cumulative survival time during hospitalisation was significantly lower as FI-Lab increased (log-rank test, P<0.001). Conclusion Elevated FI-Lab is associated with increased in-hospital mortality in patients with septic shock

Two C-type lectins from shrimp Litopenaeus vannamei that might be involved in immune response against bacteria and virus

C-type lectins play crucial roles in innate immunity to recognize and eliminate pathogens efficiently. In the present study, two C-type lectins from shrimp Litopenaeus vannamei (designated as LvLectin-1 and LvLectin-2) were identified, and their expression patterns, both in tissues and toward pathogen stimulation, were then characterized. The full-length cDNA of LvLectin-1 and LvLectin-2 was 567 and 625 bp, containing an open reading frame (ORF) of 471 and 489 bp, respectively, and deduced amino acid sequences showed high similarity to other members of C-type lectin superfamily. Both two C-type lectins encoded a single carbohydrate-recognition domain (CRD). The motif of Ca2+ binding site 2 in CRD, which determined carbohydrate-binding specificity, was QPN (GIn(122)-Pro(123)-Asn(124)) in LvLectin-1, but QPD (Gln(128)-Pro(129)-Asp(130)) in LvLectin-2. Two C-type lectins exhibited similar tissue expression pattern, for their mRNA were both constitutively expressed in all tested tissues, including hepatopancreas, muscle, gill, hemocytes, gonad and heart, furthermore they were both mostly expressed in hepatopancreas, though the expression level of LvLectin-2 was much higher than LvLectin-1. The expression level of two C-type lectins mRNA in hemocytes varied greatly after the challenge of Listonella anguillarum or WSSV. After L. anguillarum challenge, the expression of both C-type lectins were significantly (P &lt; 0.01) up-regulated compared with blank group, and LvLectin-1 exhibited higher level than LvLectin-2; while after the stimulation of WSSV, the expression of LvLectin-2 was significantly up-regulated at 6 h (P &lt; 0.01) and 12 h (P &lt; 0.05), but the expression level of LvLectin-1 down-regulated significantly (P &lt; 0.01) to 0.4-fold at 6 and 12 h post-stimulation. The results indicated that the two C-type lectins might be involved in immune response toward pathogen infection, and they might perform different recognition specificity toward bacteria or virus.C-type lectins play crucial roles in innate immunity to recognize and eliminate pathogens efficiently. In the present study, two C-type lectins from shrimp Litopenaeus vannamei (designated as LvLectin-1 and LvLectin-2) were identified, and their expression patterns, both in tissues and toward pathogen stimulation, were then characterized. The full-length cDNA of LvLectin-1 and LvLectin-2 was 567 and 625 bp, containing an open reading frame (ORF) of 471 and 489 bp, respectively, and deduced amino acid sequences showed high similarity to other members of C-type lectin superfamily. Both two C-type lectins encoded a single carbohydrate-recognition domain (CRD). The motif of Ca2+ binding site 2 in CRD, which determined carbohydrate-binding specificity, was QPN (GIn(122)-Pro(123)-Asn(124)) in LvLectin-1, but QPD (Gln(128)-Pro(129)-Asp(130)) in LvLectin-2. Two C-type lectins exhibited similar tissue expression pattern, for their mRNA were both constitutively expressed in all tested tissues, including hepatopancreas, muscle, gill, hemocytes, gonad and heart, furthermore they were both mostly expressed in hepatopancreas, though the expression level of LvLectin-2 was much higher than LvLectin-1. The expression level of two C-type lectins mRNA in hemocytes varied greatly after the challenge of Listonella anguillarum or WSSV. After L. anguillarum challenge, the expression of both C-type lectins were significantly (P < 0.01) up-regulated compared with blank group, and LvLectin-1 exhibited higher level than LvLectin-2; while after the stimulation of WSSV, the expression of LvLectin-2 was significantly up-regulated at 6 h (P < 0.01) and 12 h (P < 0.05), but the expression level of LvLectin-1 down-regulated significantly (P < 0.01) to 0.4-fold at 6 and 12 h post-stimulation. The results indicated that the two C-type lectins might be involved in immune response toward pathogen infection, and they might perform different recognition specificity toward bacteria or virus. (C) 2011 Elsevier Ltd. All rights reserved

Transmission Line Equipment Infrared Diagnosis Using an Improved Pulse-Coupled Neural Network

In order to detect the status of power equipment from infrared transmission line images under the spatial positioning relationship of the transmission line equipment, such as corridor, substation equipment, and facilities, this paper presents an improved PCNN model which merges an optimized parameter setting method. In this PCNN model, the original iteration mechanism is abandoned, and instead, the thresholding model is built by the maximum similarity thresholding rule. To ensure similarity during classifying neighboring neurons into cluster centers, a local clustering strategy is used for setting the linking coefficient, thus improving the efficiency of the method to detect the power equipment in infrared transmission line images. Finally, experimental results on transmission line infrared images show that the proposed method can provide the basis for the diagnosis of power equipment, preventing the casualties and property damage caused by the thermal damage of power equipment, and effectively improving the safety risk identification and operation control ability of power grid engineering

Study on Laminar Combustion Characteristics of Ammonia/ Hydrogen Premixed Based on Chemical Reaction Kinetics

The combustion characteristics of ammonia/hydrogen premixed laminar flow and the effect of hydrogen on the combustion performance of ammonia fuel were studied. First, the corresponding model of ammonia/ hydrogen premixed laminar combustion is established by using GRI3.0 mechanism, Konnov mechanism, Mei mechanism, Okafor mechanism, and Otomo mechanism respectively. Second, the simulation results are compared with the experimental results. It is found that the Mei mechanism and Okafor mechanism are more suitable for ammonia/ hydrogen premixed laminar combustion. On this basis, the effects of equivalent ratio, hydrogen ratio, and initial temperature on laminar flame velocity, maximum combustion temperature, and NO mole fraction were studied. The results show that the laminar flame velocity, the maximum combustion temperature, and the mole fraction of NO first increase and then decrease with the increase of the equivalent ratio, and the laminar flame velocity reaches the maximum when the equivalent ratio is 1.1. At the same time, with the increase of hydrogen ratio and initial temperature, the maximum combustion temperature increases first and then decreases. The mole fraction of NO increased with the increase of hydrogen ratio and initial temperature. The results show that mixing hydrogen in ammonia can improve the combustion characteristics of ammonia

Oscillatory Shear Stress Induces Oxidative Stress via TLR4 Activation in Endothelial Cells

Background. Oscillatory shear stress (OSS) disrupts endothelial homeostasis and promotes oxidative stress, which can lead to atherosclerosis. In atherosclerotic lesions, Toll-like receptor 4 (TLR4) is highly expressed. However, the molecular mechanism by which TLR4 modulates oxidative changes and the cell signaling transudation upon OSS is yet to be determined. Methods and Results. Carotid artery constriction (CAC) surgery and a parallel-plate flow chamber were used to modulate shear stress. The results showed that OSS significantly increased the oxidative burden, and this was partly due to TLR4 activation. OSS activated NOX2 and had no significant influence to NOX1 or NOX4 in endothelial cells (ECs). OSS phosphorylated caveolin-1, promoted its binding with endothelial nitric oxide synthase (eNOS), and resulted in deactivation of eNOS. TLR4 inhibition restored levels of nitric oxide (NO) and superoxide dismutase (SOD) in OSS-exposed cells. Conclusion. TLR4 modulates OSS-induced oxidative stress by activating NOX2 and suppressing eNOS