Quasi-optical Measurement for Low Loss Material Characterization in Submillimeter Wave Range

An accurate knowledge of dielectric constant of materials is required in many sub-millimeter wave applications. Free-space measurement of materials has always been one of the first choices due to their non-destructive nature and relatively simple sample preparation. However, free-space measurement systems at sub-millimeter frequency range suffer from two main problems: high loss because of divergent beam pattern and diffraction when the beam waist of the radiated beam is relatively large compared to the size of the sample under tests. In order to mitigate these issues, we set up a quasi-optical system using off-axis parabolic mirrors, which enhance the dynamic range and accuracy of the system. Mirrors are preferred over lenses because of their very low absorption loss. Signals from 75 GHz to 750 GHz are generated by using a vector network analyzer and a frequency extender system in six bands. Our setup consists of a pair of horn antennas operates as feed for two off-axis parabolic mirrors. Once a collimated beam is generated, we measure its characteristics using Gaussian beam mode analysis. The sample under test is then inserted midway between the two mirrors where the beam is collimated. We have measured electric permittivity of material like high-density polyethylene and polypropylene and our results highly agree with already published papers. In the future, we would like to measure some less well-known materials to see if they are suitable for sub-millimeter electronics applications

Facile Template In-Situ Fabrication of ZnCo2O4 Nanoparticles with Highly Photocatalytic Activities under Visible-Light Irradiation

High specific surface area ZnCo2O4 nanoparticles were prepared via a sacrificial template accelerated hydrolysis by using nanoparticles of ZnO with highly polar properties as a template. The obtained ZnCo2O4 nanoparticles were characterized by the method of scanning electron microscopy (SEM), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area measurements, Transmission electron microscopy (TEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The obtained nanoparticles were performed as a photocatalyst for the degradation of methylene blue in aqueous solution under visible irradiation. The photocatalytic degradation rate of methylene blue onto the synthesized ZnCo2O4 was higher than that of commercial ZnO and synthesized ZnO template. Copyright © 2019 BCREC Group. All rights reserved

Organiser Team at ImageCLEFlifelog 2020: A Baseline Approach for Moment Retrieval and Athlete Performance Prediction using Lifelog Data

For the LMRT task at ImageCLEFlifelog 2020, LIFER 3.0, a new version of the LIFER system with improvements in the user interface and system affordance, is used and evaluated via feedback from a user experiment. In addition, since both tasks share a common dataset, LIFER 3.0 borrows some features from the LifeSeeker system deployed for the Lifelog Search Challenge; which are free-text search, visual similarity search and elastic sequencing filter. For the SPLL task, we proposed a naive solution by capturing the rate of change in running speed and weight, then obtain the target changes for each subtask using average computation and linear regression model. The results presented in this paper can be used as comparative baselines for other participants in the ImageCLEFlifelog 2020 challenge.publishedVersio

Ventilator-associated respiratory infection in a resource-restricted setting: impact and etiology.

BACKGROUND: Ventilator-associated respiratory infection (VARI) is a significant problem in resource-restricted intensive care units (ICUs), but differences in casemix and etiology means VARI in resource-restricted ICUs may be different from that found in resource-rich units. Data from these settings are vital to plan preventative interventions and assess their cost-effectiveness, but few are available. METHODS: We conducted a prospective observational study in four Vietnamese ICUs to assess the incidence and impact of VARI. Patients ≥ 16 years old and expected to be mechanically ventilated > 48 h were enrolled in the study and followed daily for 28 days following ICU admission. RESULTS: Four hundred fifty eligible patients were enrolled over 24 months, and after exclusions, 374 patients' data were analyzed. A total of 92/374 cases of VARI (21.7/1000 ventilator days) were diagnosed; 37 (9.9%) of these met ventilator-associated pneumonia (VAP) criteria (8.7/1000 ventilator days). Patients with any VARI, VAP, or VARI without VAP experienced increased hospital and ICU stay, ICU cost, and antibiotic use (p < 0.01 for all). This was also true for all VARI (p < 0.01 for all) with/without tetanus. There was no increased risk of in-hospital death in patients with VARI compared to those without (VAP HR 1.58, 95% CI 0.75-3.33, p = 0.23; VARI without VAP HR 0.40, 95% CI 0.14-1.17, p = 0.09). In patients with positive endotracheal aspirate cultures, most VARI was caused by Gram-negative organisms; the most frequent were Acinetobacter baumannii (32/73, 43.8%) Klebsiella pneumoniae (26/73, 35.6%), and Pseudomonas aeruginosa (24/73, 32.9%). 40/68 (58.8%) patients with positive cultures for these had carbapenem-resistant isolates. Patients with carbapenem-resistant VARI had significantly greater ICU costs than patients with carbapenem-susceptible isolates (6053 USD (IQR 3806-7824) vs 3131 USD (IQR 2108-7551), p = 0.04) and after correction for adequacy of initial antibiotics and APACHE II score, showed a trend towards increased risk of in-hospital death (HR 2.82, 95% CI 0.75-6.75, p = 0.15). CONCLUSIONS: VARI in a resource-restricted setting has limited impact on mortality, but shows significant association with increased patient costs, length of stay, and antibiotic use, particularly when caused by carbapenem-resistant bacteria. Evidence-based interventions to reduce VARI in these settings are urgently needed

A novel machine learning approach to predict the export price of seafood products based on competitive information : The case of the export of Vietnamese shrimp to the US market

Predicting the export price of shrimp is important for Vietnam's fisheries. It not only promotes product quality but also helps policy makers determine strategies to develop the national shrimp industry. Competition in global markets is considered to be an important factor, one that significantly influences price. In this study, we predicted trends in the export price of Vietnamese shrimp based on competitive information from six leading exporters (China, India, Indonesia, Thailand, Ecuador, and Chile) who, alongside Vietnam, also export shrimp to the US. The prediction was based on a dataset collected from the US Department of Agriculture (USDA), the Food and Agriculture Organization of the United Nations (FAO), and the World Trade Organization (WTO) (May-1995 to May-2019) that included price, required farming certificates, and disease outbreak data. A super learner technique, which combined 10 single algorithms, was used to make predictions in selected base periods (3, 6, 9, and 12 months). It was found that the super learner obtained results in all base periods that were more accurate and stable than any candidate algorithms. The impacts of variables in the predictive model were interpreted by a SHapley Additive exPlanations (SHAP) analysis to determine their influence on the price of Vietnamese exports. The price of Indian, Thai, and Chinese exports highlighted the advantages of being a World Trade Organization member and the disadvantages of the prevalence of shrimp disease in Vietnam, which has had a significant impact on the Vietnamese shrimp export price