Increased Risk of Ischemic Stroke during Sleep in Apneic Patients.

BACKGROUND AND PURPOSE:The literature indicates that obstructive sleep apnea (OSA) increases the risk of ischemic stroke. However, the causal relationship between OSA and ischemic stroke is not well established. This study examined whether preexisting OSA symptoms affect the onset of acute ischemic stroke. METHODS:We investigated consecutive patients who were admitted with acute ischemic stroke, using a standardized protocol including the Berlin Questionnaire on symptoms of OSA prior to stroke. The collected stroke data included the time of the stroke onset, risk factors, and etiologic subtypes. The association between preceding OSA symptoms and wake-up stroke (WUS) was assessed using multivariate logistic regression analysis. RESULTS:We identified 260 subjects with acute ischemic strokes with a definite onset time, of which 25.8% were WUS. The presence of preexisting witnessed or self-recognized sleep apnea was the only risk factor for WUS (adjusted odds ratio=2.055, 95% confidence interval=1.035-4.083, p=0.040). CONCLUSIONS:Preexisting symptoms suggestive of OSA were associated with the occurrence of WUS. This suggests that OSA contributes to ischemic stroke not only as a predisposing risk factor but also as a triggering factor. Treating OSA might therefore be beneficial in preventing stroke, particularly that occurring during sleep

Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning

Compositional zero-shot learning (CZSL) aims to recognize unseen compositions with prior knowledge of known primitives (attribute and object). Previous works for CZSL often suffer from grasping the contextuality between attribute and object, as well as the discriminability of visual features, and the long-tailed distribution of real-world compositional data. We propose a simple and scalable framework called Composition Transformer (CoT) to address these issues. CoT employs object and attribute experts in distinctive manners to generate representative embeddings, using the visual network hierarchically. The object expert extracts representative object embeddings from the final layer in a bottom-up manner, while the attribute expert makes attribute embeddings in a top-down manner with a proposed object-guided attention module that models contextuality explicitly. To remedy biased prediction caused by imbalanced data distribution, we develop a simple minority attribute augmentation (MAA) that synthesizes virtual samples by mixing two images and oversampling minority attribute classes. Our method achieves SoTA performance on several benchmarks, including MIT-States, C-GQA, and VAW-CZSL. We also demonstrate the effectiveness of CoT in improving visual discrimination and addressing the model bias from the imbalanced data distribution. The code is available at https://github.com/HanjaeKim98/CoT.Comment: ICCV 202

Manipulating nutrient composition of microalgal growth media to improve biomass yield and lipid content of Micractinium pusillum

Biodiesel production from microalgae depends on the algal biomass and lipid content. Both biomass production and lipid accumulation are limited by several factors in which nutrients play a key role. We investigated the influences of micronutrients on biomass, and lipid content of Micractinium pusillum GU732425 cultivated in bold basal media (BBM). The average dry biomass of microalgal strain in control medium reached 0.34 ± 0.01 g /L, while doubling (2X) the levels of Mn and Cu concentration increased the dry biomass to 0.38 ± 0.01 and 0.37 ± 0.02 g /L, respectively. M. pusillum cultivated in control medium had a biomass of 0.82 ± 0.05 g/L and a lipid productivity of 0.33 ± 0.02 g/L after 17 day cultivation. The alga cultivated in BBM with 4X Mn or 4X Cu produced more biomass (1.25 ± 0.01 or 1.28 ± 0.04 g dw/L) and lipid productivity (0.45±0.04 or 0.47±0.05 g/L), respectively. M. pusillum cultivated in different growth media had fatty acid compositions mainly comprising linoleic (49-54%), palmitic (24-29%), linolenic (16-22%), and oleic acids (2-5%). These results can be used to maximize the production of microalgal biomass and lipids in optimally designed  photobioreactors.Key words: Micractinium pusillum, biomass, lipid production, media composition, fatty acids, trace metals

Chiral electroluminescence from thin-film perovskite metacavities

Chiral light sources realized in ultracompact device platforms are highly desirable for various applications. Among active media employed for thin-film emission devices, lead-halide perovskites have been extensively studied for photoluminescence due to their exceptional properties. However, up to date, there have been no demonstrations of chiral electroluminescence with a substantial degree of circular polarization (DCP), being critical for the development of practical devices. Here, we propose a new concept of chiral light sources based on a thin-film perovskite metacavity and experimentally demonstrate chiral electroluminescence with DCP approaching 0.38. We design a metacavity created by a metal and a dielectric metasurface supporting photonic eigenstates with close-to-maximum chiral response. Chiral cavity modes facilitate asymmetric electroluminescence of pairs of left and right circularly polarized waves propagating in the opposite oblique directions. The proposed ultracompact light sources are especially advantageous for many applications requiring chiral light beams of both helicities.Comment: 20 pages, 4 figure

Cu2Se-based thermoelectric cellular architectures for efficient and durable power generation

Thermoelectric power generation offers a promising way to recover waste heat. The geometrical design of thermoelectric legs in modules is important to ensure sustainable power generation but cannot be easily achieved by traditional fabrication processes. Herein, we propose the design of cellular thermoelectric architectures for efficient and durable power generation, realized by the extrusion-based 3D printing process of Cu2Se thermoelectric materials. We design the optimum aspect ratio of a cuboid thermoelectric leg to maximize the power output and extend this design to the mechanically stiff cellular architectures of hollow hexagonal column- and honeycomb-based thermoelectric legs. Moreover, we develop organic binder-free Cu2Se-based 3D-printing inks with desirable viscoelasticity, tailored with an additive of inorganic Se-8(2-) polyanion, fabricating the designed topologies. The computational simulation and experimental measurement demonstrate the superior power output and mechanical stiffness of the proposed cellular thermoelectric architectures to other designs, unveiling the importance of topological designs of thermoelectric legs toward higher power and longer durability

Finite element analysis of coupled heat and mass transfer in harvested cucumber fruit to predict transpirational water loss during storage

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Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

In this study, we performed seismic vulnerability assessment and mapping of the ML5.8 Gyeongju Earthquake in Gyeongju, South Korea, as a case study. We applied logistic regression (LR) and four kernel models based on the support vector machine (SVM) learning method to derive suitable models for assessing seismic vulnerabilities; the results of each model were then mapped and evaluated. Dependent variables were quantified using buildings damaged in the 9.12 Gyeongju Earthquake, and independent variables were constructed and used as spatial databases by selecting 15 sub-indicators related to earthquakes. Success and prediction rates were calculated using receiver operating characteristic (ROC) curves. The success rates of the models (LR, SVM models based on linear, polynomial, radial basis function, and sigmoid kernels) were 0.652, 0.649, 0.842, 0.998, and 0.630, respectively, and the prediction rates were 0.714, 0.651, 0.804, 0.919, and 0.629, respectively. Among the five models, RBF-SVM showed the highest performance. Seismic vulnerability maps were created for each of the five models and were graded as safe, low, moderate, high, or very high. Finally, we examined the distribution of building classes among the 23 administrative districts of Gyeongju. The common vulnerable regions among all five maps were Jungbu-dong and Hwangnam-dong, and the common safe region among all five maps was Gangdong-myeon

Effective Dose of Ramosetron for Prophylaxis of Postoperative Nausea and Vomiting in High-Risk Patients

Background. Postoperative nausea and vomiting (PONV) are common adverse events with an incidence of up to 80% in high-risk patients. Ramosetron, a selective 5-HT3 receptor antagonist, is widely used to prevent PONV. The purpose of this study was to evaluate the effective dose of ramosetron for the prevention of PONV in high-risk patients. Methods. Fifty-one patients were randomly allocated to 3 groups and were administered ramosetron 0.3 mg (group A), 0.45 mg (group B), or 0.6 mg (group C), at the end of their surgery. The episodes of PONV were assessed 1, 6, 24, and 48 hours after the injection and all the adverse events were observed. Results. The complete response rate in the postoperative period 6–24 hours after the anesthesia was higher in group C than in group A: 93% versus 44%. Group C’s experience score of Rhodes index was lower than group A’s: 0.81 ± 2.56 versus 3.94 ± 5.25. No adverse drug reaction could be observed in all groups. Conclusions. The effective dose of ramosetron to be injected for the near-complete prophylaxis of PONV 6 to 24 hours after surgery in high-risk patients is a 0.6 mg bolus injection at the end of the surgery

COMBUSTION INSTABILITY CHARACTERISTICS UNDER VARIOUS FUEL AND AIR FLOW RATES IN A PARTIALLY PREMIXED MODEL GAS TURBINE COMBUSTOR

In this study, the combustion instability characteristics are experimentally investigated in a partially premixed gas turbine model combustor. The combustor is operated with methane and preheated air as the fuel and oxidizer, respectively, at atmospheric pressure. The experiment is carried out at various equivalence ratios and flow rates of fuel and air to investigate the effect on the combustion instability frequency transition. According to the experimental results, the transition of the combustion instability frequency to higher longitudinal mode occurs because of the flow rate variation. To explain the frequency shift phenomenon, the concept of convection time is introduced, which is mostly affected by the flame position and exit velocity of the fuel-air mixture. The flame positions are measured using OH planar laser-induced fluorescence (OH-PLIF), and the flow field information is obtained using particle image velocimetry to calculate the convection time. The measurement results show that the injection velocities of fuel and air are also important factors in determining the combustion instability frequency as well as the equivalence ratio, which is a crucial parameter of the flame position. As a result, it is found that the decrease in convection time owing to a closer distance from the dump plane to the flame and a faster exit velocity of the fuel-air mixture causes the combustion instability frequency mode shift. Additionally, the structural characteristics of the flame are analyzed using high-speed OH-PLIF measurement. The differences in the flame structure between the stable and unstable flames in the 2(nd) and 3(rd) longitudinal modes are analyzed. The change in the unburned mixture is mainly observed and the relationship between the dynamic pressure, heat release rate, and length of the unburned region is also analyzed.N