26 research outputs found

    Time-aware Random Walk Diffusion to Improve Dynamic Graph Learning

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    How can we augment a dynamic graph for improving the performance of dynamic graph neural networks? Graph augmentation has been widely utilized to boost the learning performance of GNN-based models. However, most existing approaches only enhance spatial structure within an input static graph by transforming the graph, and do not consider dynamics caused by time such as temporal locality, i.e., recent edges are more influential than earlier ones, which remains challenging for dynamic graph augmentation. In this work, we propose TiaRa (Time-aware Random Walk Diffusion), a novel diffusion-based method for augmenting a dynamic graph represented as a discrete-time sequence of graph snapshots. For this purpose, we first design a time-aware random walk proximity so that a surfer can walk along the time dimension as well as edges, resulting in spatially and temporally localized scores. We then derive our diffusion matrices based on the time-aware random walk, and show they become enhanced adjacency matrices that both spatial and temporal localities are augmented. Throughout extensive experiments, we demonstrate that TiaRa effectively augments a given dynamic graph, and leads to significant improvements in dynamic GNN models for various graph datasets and tasks.Comment: 16 page

    Gas-Phase Synthesis of Bimetallic Oxide Nanoparticles with Designed Elemental Compositions for Controlling the Explosive Reactivity of Nanoenergetic Materials

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    We demonstrate a simple and viable method for controlling the energy release rate and pressurization rate of nanoenergetic materials by controlling the relative elemental compositions of oxidizers. First, bimetallic oxide nanoparticles (NPs) with a homogeneous distribution of two different oxidizer components (CuO and Fe2O3) were generated by a conventional spray pyrolysis method. Next, the Al NPs employed as a fuel were mixed with CuO-Fe2O3 bimetallic oxide NPs by an ultrasonication process in ethanol solution. Finally, after the removal of ethanol by a drying process, the NPs were converted into energetic materials (EMs). The effects of the mass fraction of CuO in the CuO-Fe2O3 bimetallic oxide NPs on the explosive reactivity of the resulting EMs were examined by using a differential scanning calorimeter and pressure cell tester (PCT) systems. The results clearly indicate that the energy release rate and pressurization rate of EMs increased linearly as the mass fraction of CuO in the CuO-Fe2O3 bimetallic oxide NPs increased. This suggests that the precise control of the stoichiometric proportions of the strong oxidizer (CuO) and mild oxidizer (Fe2O3) components in the bimetallic oxide NPs is a key factor in tuning the explosive reactivity of EMs

    Analytical Investigation of the Effects of Secondary Structural Members on the Structural Behaviors of Transmission Towers

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    High-voltage transmission towers consist of structures that are designed to avoid the risk of electric shock and prevent the risk of collapse. Hence, for efficiency, they are generally designed as high-rise towers. The main tower posts are the primary structural members that resist loads under various load conditions. Therefore, the contribution of the secondary members to securing the stiffness and strength of the main posts by reducing the effective buckling length is an important one. However, we lack detailed secondary member design criteria. In this study, we observed the structural effects of the horizontal members and braces on the torsional stiffness, elastic buckling strength, and load-carrying capacity of a transmission tower using various structural analysis methods, including linear elastic, eigenvalue, and geometric nonlinear and inelastic analyses, under governing load combinations. According to the analytical results, it is the brace spacing rather than the horizontal members that substantially affects the structural performance. Therefore, we can minimize the number of horizontal members if we erect sufficient brace members. If the brace spacing is wide, then the horizontal members should be erected to create K bracing, thereby enhancing the buckling resistance of the main posts

    Deep Learning Improves Prediction of Cardiovascular Disease-Related Mortality and Admission in Patients with Hypertension: Analysis of the Korean National Health Information Database

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    Objective: The aim of this study was to develop, compare, and validate models for predicting cardiovascular disease (CVD) mortality and hospitalization with hypertension using a conventional statistical model and a deep learning model. Methods: Using the database of Korean National Health Insurance Service, 2,037,027 participants with hypertension were identified. Among them, CVD (myocardial infarction or stroke) death and/or hospitalization that occurred within one year after the last visit were analyzed. Oversampling was performed using the synthetic minority oversampling algorithm to resolve imbalances in the number of samples between case and control groups. The logistic regression method and deep neural network (DNN) method were used to train models for assessing the risk of mortality and hospitalization. Findings: Deep learning-based prediction model showed a higher performance in all datasets than the logistic regression model in predicting CVD hospitalization (accuracy, 0.863 vs. 0.655; F1-score, 0.854 vs. 0.656; AUC, 0.932 vs. 0.655) and CVD death (accuracy, 0.925 vs. 0.780; F1-score, 0.924 vs. 0.783; AUC, 0.979 vs. 0.780). Interpretation: The deep learning model could accurately predict CVD hospitalization and death within a year in patients with hypertension. The findings of this study could allow for prevention and monitoring by allocating resources to high-risk patients

    Effect of Low-Dose Triple Therapy Using Gabapentin, Amitriptyline, and a Nonsteroidal Anti-Inflammatory Drug for Overactive Bladder Symptoms in Patients With Bladder Pain Syndrome

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    Purpose: Patients with bladder pain syndrome/interstitial cystitis (BPS/IC) can have pain as a main symptom and overactive bladder (OAB) symptoms that are directly or indirectly related to a major mechanism that causes pain. The primary purpose of this study is firstly to identify the prevalence rate of OAB symptoms in patients with BPS/IC, secondly to identify changes in OAB symptoms after low-dose triple therapy, and thirdly to build a theoretical foundation to improve quality of life for patients. Methods: Patients who met the inclusion criteria of BPS/IC through basic tests including the O’Leary-Sant symptom index, overactive bladder symptom score (OABSS), and visual analog scale (VAS) were identified. Treatment-based changes in OAB symptoms were identified using the IC Symptom Index and IC Problem Index (ICSI/ICPI), OABSS, and VAS before, and 4 and 12 weeks after low-dose triple therapy. Results: The patients consisted of 3 men and 20 women, and their mean age was 61.9 years (41.0–83.2 years). Comparing values before treatment, and 4 and 12 weeks after treatment (baseline vs. 4 weeks to baseline vs. 12 weeks), the rates of improvement were as follows: ICSI, 44.2% to 63.7%; ICPI, 46.9% to 59.4%; OABSS, 34.3% to 58.2%; and VAS, 53.6% to 75.0%, which showed statistically significant differences (P0.05). Conclusions: Low-dose triple therapy in BPS/IC results in a clear decrease in OAB symptoms in the first 4 weeks after treatment, and additional treatment for 8 weeks had a partial effect with varied statistical significances depending on the questionnaires

    Essential oils from two Allium species exert effects on cell proliferation and neuroblast differentiation in the mouse dentate gyrus by modulating brain-derived neurotrophic factor and acetylcholinesterase

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    This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Abstract Background In the present study, we investigated the effects of oil products from two Allium species: Allium sativum (garlic) and Allium hookeri (Chinese chives) on cell proliferation and neuroblast differentiation in the mouse dentate gyrus. Methods Using corn oil as a vehicle, the essential oil from garlic (10 ml/kg), or Chinese chives (10 ml/kg) was administered orally to 9-week-old mice once a day for 3 weeks. One hour following the last treatment, a novel object recognition test was conducted and the animals were killed 2 h after the test. Results In comparison to the vehicle-treated group, garlic essential oil (GO) treatment resulted in significantly increased exploration time and discrimination index during the novel object recognition test, while Chinese chives essential oil (CO) reduced the exploration time and discrimination index in the same test. In addition, the number of Ki67-immunoreactive proliferating cells and doublecortin-immunoreactive neuroblasts significantly increased in the dentate gyrus of GO-treated animals. However, administration of CO significantly decreased cell proliferation and neuroblast differentiation. Administration of GO significantly increased brain-derived neurotrophic factor (BDNF) levels and decreased acetylcholinesterase (AChE) activity in the hippocampal homogenates. In contrast, administration of CO decreased BDNF protein levels and had no significant effect on AChE activity, compared to that in the vehicle-treated group. Conclusions These results suggest that GO significantly improves novel object recognition as well as increases cell proliferation and neuroblast differentiation, by modulating hippocampal BDNF protein levels and AChE activity, while CO impairs novel object recognition and decreases cell proliferation and neuroblast differentiation, by reducing BDNF protein levels in the hippocampus

    Potential Probiotic Acceptability of a Novel Strain of Paenibacillus konkukensis SK 3146 and Its Dietary Effects on Growth Performance, Intestinal Microbiota, and Meat Quality in Broilers

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    This study evaluates the in vitro probiotic characteristics of P. konkukensis sp. nov. SK-3146, which was isolated from animal feed, and its dietary effects on growth performance, intestinal characteristics, intestinal microbiota, and meat quality in broilers. In vitro experiments revealed that P. konkukensis was non-hemolytic with variable antibiotic susceptibility, and acid as well as bile tolerance. To assess the effect of P. konkukensis on broilers, a total of four hundred eighty 1-day-old Ross 308 broiler chicks were allocated to 3 treatment groups with 4 replicates of 40 birds each; the negative control group was fed a basal diet without any feed additives (NC), the positive control group was fed a basal diet containing 0.01% enramycin (PC), and the experimental group was fed a basal diet containing P. konkukensis bacterial culture (PK) at 104 CFU/g of the diet based on bacterial count. The experiment lasted for 35 days. Results indicated that there were no significant differences in any growth performance parameters among the dietary treatments (p > 0.05). In addition, the inclusion of P. konkukensis in the broilers’ diet did not affect meat cooking loss, color, and pH but increased the relative weight of breast meat (p < 0.05). The PK group showed heavier intestinal weight and shorter intestinal length than the NC group (p < 0.05). The ratio of the intestinal weight to length of jejunum was the highest in the PK group (p < 0.05). The PK group showed increased counts of Streptococcus thermophilus (p < 0.05) with no adverse effects of P. konkukensis on other intestinal microbiota in the jejunum. This study implies that P. konkukensis might have the potential to be applied as a probiotic feed additive in poultry
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