Performance and emission characteristics of a vehicle fueled with enriched biogas and natural gases

This study aimed to investigate the characteristics of exhaust emissions and the fuel economy of a compressed natural gas (CNG) vehicle fueled with biogas and natural gases. A large CNG vehicle currently used as a city bus in Korea was tested on a chassis dynamometer under the European Transient Cycle (ETC) and the National Institute of Environmental Research (NIER) 06 cycles. One CH4-enriched biogas (97.6% CH4) and 5 natural gases with different CH4 contents (81.6-94.0% CH4) were used as test fuels. Total hydrocarbons (THC), CO, NOx and CO2 emissions in the NIER 06 cycle were higher than those in the ETC cycle for all tested fuels, while the fuel economy in the NIER 06 cycle was 43.7-51.5% lower than that in the ETC cycle. Total VOC emissions increased with increasing CH4 content in the fuel, with toluene being the highest proportion of the BTEX emissions in both the ETC cycle (72-80%) and the NIER 06 cycle (73-78%). Emissions of elemental/organic carbon exhibited a similar trend to that of nanoparticle emissions. Total organic carbon was mainly comprised of organic compounds at 97-99% (ETC cycle) and 95-99% (NIER 06 cycle). Polycyclic aromatic hydrocarbon emissions in the NIER 06 cycle were 133.3-577.8% higher than in the ETC cycle because of incomplete combustion and an increase in unburned fuel in the NIER 06 cycle, which is a low-speed driving mode. Nanoparticle number concentrations were lowest for M91 among the 6 tested fuels; the total number of particles in the NIER 06 cycle was 33.2-123.8% higher than in the ETC cycle.close7

Evaluation of regulated and unregulated emissions from a diesel powered vehicle fueled with diesel/biodiesel blends in Korea

The emission characteristics of diesel powered vehicles using conventional diesel fuel and six different biodiesel blends at proportions of 1% (B1), 3% (B3), 5% (B5), and 20% (B20) by volume were investigated. The emission tests were performed following the NEDC (New European Driving Cycle) and regulated and unregulated emissions were measured for two vehicles - one equipped with a DOC (diesel oxidation catalyst) and the other equipped with a DPF (diesel particulate filter). Emissions of THC (total hydrocarbon), CO, and PM (particulate matter) generally decreased with increasing biodiesel content in the fuel, while NOx emissions increased slightly in both vehicles. CO2 emissions were virtually identical. The extent of PM reduction in the DPF-equipped vehicle was almost 40 times higher than in the DOC-equipped vehicle. PAH (polycyclic aromatic hydrocarbon) emissions decreased with increasing biodiesel content in the fuel, with average reduction rates of the six biodiesels for particle-phase PAHs compared to the base diesel fuel in the range of 18.2-27.2% and 48.9-79.7% for the DOC- and DPF-equipped vehicles, respectively. Nanoparticle emissions from the DOC- and DPF-equipped vehicles were predominantly in the size range of 25.5-191.1 nm and <25.5 nm, respectively.close6

End-To-End Deep Learning Architecture for Continuous Blood Pressure Estimation Using Attention Mechanism

Blood pressure (BP) is a vital sign that provides fundamental health information regarding patients. Continuous BP monitoring is important for patients with hypertension. Various studies have proposed cuff-less BP monitoring methods using pulse transit time. We propose an end-to-end deep learning architecture using only raw signals without the process of extracting features to improve the BP estimation performance using the attention mechanism. The proposed model consisted of a convolutional neural network, a bidirectional gated recurrent unit, and an attention mechanism. The model was trained by a calibration-based method, using the data of each subject. The performance of the model was compared to the model that used each combination of the three signals, and the model with the attention mechanism showed better performance than other state-of-the-art methods, including conventional linear regression method using pulse transit time (PTT). A total of 15 subjects were recruited, and electrocardiogram, ballistocardiogram, and photoplethysmogram levels were measured. The 95% confidence interval of the reference BP was [86.34, 143.74] and [51.28, 88.74] for systolic BP (SBP) and diastolic BP (DBP), respectively. The R 2 values were 0.52 and 0.49, and the mean-absolute-error values were 4.06 &plusmn; 4.04 and 3.33 &plusmn; 3.42 for SBP and DBP, respectively. In addition, the results complied with global standards. The results show the applicability of the proposed model as an analytical metric for BP estimation

BL-11C Micro-MX: a high-flux microfocus macromolecular-crystallography beamline for micrometre-sized protein crystals at Pohang Light Source II

BL-11C, a new protein crystallography beamline, is an in-vacuum undulator-based microfocus beamline used for macromolecular crystallography at the Pohang Accelerator Laboratory and it was made available to users in June 2017. The beamline is energy tunable in the range 5.0–20 keV to support conventional single- and multi-wavelength anomalous-dispersion experiments against a wide range of heavy metals. At the standard working energy of 12.659 keV, the monochromated beam is focused to 4.1 µm (V) × 8.5 µm (H) full width at half-maximum at the sample position and the measured photon flux is 1.3 × 1012 photons s−1. The experimental station is equipped with a Pilatus3 6M detector, a micro-diffractometer (MD2S) incorporating a multi-axis goniometer, and a robotic sample exchanger (CATS) with a dewar capacity of 90 samples. This beamline is suitable for structural determination of weakly diffracting crystalline substances, such as biomaterials, including protein, nucleic acids and their complexes. In addition, serial crystallography experiments for determining crystal structures at room temperature are possible. Herein, the current beamline characteristics, technical information for users and some recent scientific highlights are described.11Nsciescopu