Comparative genome analysis of rice-pathogenic Burkholderia provides insight into capacity to adapt to different environments and hosts

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Background In addition to human and animal diseases, bacteria of the genus Burkholderia can cause plant diseases. The representative species of rice-pathogenic Burkholderia are Burkholderia glumae, B. gladioli, and B. plantarii, which primarily cause grain rot, sheath rot, and seedling blight, respectively, resulting in severe reductions in rice production. Though Burkholderia rice pathogens cause problems in rice-growing countries, comprehensive studies of these rice-pathogenic species aiming to control Burkholderia-mediated diseases are only in the early stages. Results We first sequenced the complete genome of B. plantarii ATCC 43733T. Second, we conducted comparative analysis of the newly sequenced B. plantarii ATCC 43733T genome with eleven complete or draft genomes of B. glumae and B. gladioli strains. Furthermore, we compared the genome of three rice Burkholderia pathogens with those of other Burkholderia species such as those found in environmental habitats and those known as animal/human pathogens. These B. glumae, B. gladioli, and B. plantarii strains have unique genes involved in toxoflavin or tropolone toxin production and the clustered regularly interspaced short palindromic repeats (CRISPR)-mediated bacterial immune system. Although the genome of B. plantarii ATCC 43733T has many common features with those of B. glumae and B. gladioli, this B. plantarii strain has several unique features, including quorum sensing and CRISPR/CRISPR-associated protein (Cas) systems. Conclusions The complete genome sequence of B. plantarii ATCC 43733T and publicly available genomes of B. glumae BGR1 and B. gladioli BSR3 enabled comprehensive comparative genome analyses among three rice-pathogenic Burkholderia species responsible for tissue rotting and seedling blight. Our results suggest that B. glumae has evolved rapidly, or has undergone rapid genome rearrangements or deletions, in response to the hosts. It also, clarifies the unique features of rice pathogenic Burkholderia species relative to other animal and human Burkholderia species

Effects of Piston Bowl Geometries On Diesel and Gasoline Dual-Fuel Combustion under Low Load Conditions

This study investigated the combustion characteristics by changing the operating parameters and piston bowl geometries in diesel/gasoline dual-fuel combustion. The experiment was conducted in a light-duty single cylinder diesel engine satisfying the EURO-6 regulation adapted for dual-fuel operation. The engine was operated under a low load condition, which was 1,500 rpm and gross IMEP 5.2 bar, with compression ratio of 14. The effects of the operating parameters, namely, the fuel ratio, diesel injection timing, and pilot duration, were analyzed for three different piston bowl geometries. Based on each result, the optimization experiments were conducted to satisfy the various constraints. The gross indicated specific NOx (gISNOx) was restricted below 0.21 g/kWh, the soot emission was limited to below 0.2 FSN, and the maximum pressure rise rate (mPRR) was confined to below 5 bar/deg. Simultaneously, the gross indicated efficiency (GIE) was controlled over 40 %. As a result, these constraints were completely satisfied in all pistons.N

Numerical Analysis of the Combustion and Emission Characteristics of Diesel Engines with Multiple Injection Strategies Using a Modified 2-D Flamelet Model

The multiple injection strategy has been widely used in diesel engines to reduce engine noise, NOx and soot formation. Fuel injection developments such as the common-rail and piezo-actuator system provide more precise control of the injection quantity and time under higher injection pressures. As various injection strategies become accessible, it is important to understand the interaction of each fuel stream and following combustion process under the multiple injection strategy. To investigate these complex processes quantitatively, numerical analysis using CFD is a good alternative to overcome the limitation of experiments. A modified 2-D flamelet model is further developed from previous work to model multi-fuel streams with higher accuracy. The model was validated under various engine operating conditions and captures the combustion and emissions characteristics as well as several parametric variations. The model is expected to be used to suggest advanced injection strategies in engine development processes

MODELING OF SPRAY WALL IMPINGEMENT AND FUEL FILM FORMATION UNDER THE GASOLINE DIRECT INJECTION CONDITION

Direct-injection spark-ignition (DISI) engines, which have a better fuel economy than conventional gasoline engines, have been widely introduced in the market. However, in these engines, the rich air-fuel mixtures associated with fuel films during cold starts, caused by spray impingement, produce particulate matter. To predict soot formation, it is important to predict the mixture field precisely; thus, accurate spray and film models are prerequisites for creating a soot model. Previous wall impingement models were well matched with low Weber number collision conditions, such as those of diesel engines, which have relatively high ambient pressures and small Sauter mean diameters. In this study, the outliers of the previous model were observed to decrease as the collision distance increased and when a strong droplet dissipation occurred owing to a high ambient pressure. However, the kinetic energy in DISI engines is considerably larger than the dissipation energy calculated using the Weber number and surface tension; thus, the amount of dissipation energy should be determined within a realistic range. To analyze the two-dimensional (2D) spray-wall impingement phenomenon more accurately, a 2D child droplet generation was considered. Finally, the film and spray behaviors were measured to validate the SNU model. The Mie scattering images of the gasoline spray near the wall were captured to measure the rebound spray radius. Then, a laser-induced fluorescence with a total internal reflection was used to determine the film shape and thickness. Compared with existing models, the SNU model exhibits better agreement with the Mie experimental results without requiring case-dependent changes to the model constant. However, the film simulation part needs improvement in future work.N

Development of semi-empirical soot emission model for a CI engine

Soot is one of the main harmful emissions of diesel engines that is mainly generated in the reacting fuel jet of diesel injection. Over 99% of the engine-out soot can be filtered by a diesel particulate filter (DPF). However, when the soot load of the DPF is high, a regeneration process that oxidizes the accumulated soot reduces fuel economy. A real-time soot estimation model can contribute to real-time feedback soot control under transient conditions to minimize the engine-out soot emission and frequency of DPF regeneration. A zero-dimensional engine-out soot estimation model for a diesel engine is developed in this study. The semi-empirical soot model considers both the formation and oxidation of soot. In the model, soot formation was correlated with the cross-sectional average equivalence ratio at the lift-off length of the fuel spray. The equivalence ratio at the lift-off length is an indicator of how much air and vaporized fuel are mixed as the fuel reaches the reaction zone. The mass of the injected fuel and combustion duration were also correlated with soot formation. The Nagle and Strickland Constable mechanism, which calculates the soot oxidation rate was correlated with the soot oxidation in this study. The results of the soot estimation showed an R-2 of 0.901 and root mean square error of 10.8 mg/m(3) for steady-state experimental cases. The engine-out soot model was also combined with the in-cylinder pressure model proposed by the authors, and validated through the transient Worldwide Harmonized Light Vehicles Test Cycle (WLTC) mode. The estimates agreed with the measured soot, with an accumulated soot error of approximately 6% during the WLTC, even without using an in-cylinder pressure sensor. The soot model developed in this study can help minimize tailpipe-out soot emissions and improve fuel economy by influencing the real-time feedback control during transient and frequent DPF regeneration.N

Titania-Encapsulated Hybrid Nanocatalysts as Active and Thermally Stable Model Catalysts

Metal–oxide hybrid nanocatalysts with ultrathin oxide encapsulation can be a new platform to test the metal–support interaction. Metal nanoparticles (Ru, Rh, or Pt) capped with polymer/citrate were deposited on functionalized SiO2 and then an ultrathin layer of TiO2 was selectively coated on the SiO2 surface to prevent sintering and to provide high thermal stability while maximizing the metal–oxide interface for higher catalytic activity. Transmission electron microscopy studies confirmed that 2.1–2.3 nm metal nanoparticles were well dispersed and distributed throughout the surface of the 25 nm SiO2 nanoparticles, and that a 2 nm ultrathin TiO2 layer existed on the surface of the particles. The metal nanoparticles were still well exposed to the outer surface, thus allowing for surface characterization and catalytic activity. Even after calcination at 600 C, the structure and morphology of the hybrid nanocatalysts remained intact, confirming high thermal stability. The catalytic activities of the hybrid nanocatalysts with ultrathin oxide encapsulation (SiO2/M/ TiO2, M = Pt, Rh, or Ru) were evaluated using the CO oxidation reaction. Hybrid nanocatalysts encapsulated by the ultrathin oxide layer allowed us to obtain high thermal stability and better exposure of the metal active sites for a strong metal–support interaction between the metals and the ultrathin TiO2.1221sciescopu

Transcutaneous Carbon Dioxide Monitoring More Accurately Detects Hypercapnia than End-Tidal Carbon Dioxide Monitoring during Non-Intubated Video-Assisted Thoracic Surgery: A Retrospective Cohort Study

Transcutaneous carbon dioxide (PtcCO2) monitoring is known to be effective at estimating the arterial partial pressure of carbon dioxide (PaCO2) in patients with sedation-induced respiratory depression. We aimed to investigate the accuracy of PtcCO2 monitoring to measure PaCO2 and its sensitivity to detect hypercapnia (PaCO2 > 60 mmHg) compared to nasal end-tidal carbon dioxide (PetCO2) monitoring during non-intubated video-assisted thoracoscopic surgery (VATS). This retrospective study included patients undergoing non-intubated VATS from December 2019 to May 2021. Datasets of PetCO2, PtcCO2, and PaCO2 measured simultaneously were extracted from patient records. Overall, 111 datasets of CO2 monitoring during one-lung ventilation (OLV) were collected from 43 patients. PtcCO2 had higher sensitivity and predictive power for hypercapnia during OLV than PetCO2 (84.6% vs. 15.4%, p p = 0.002). Moreover, PtcCO2 was more in agreement with PaCO2 than PetCO2, indicated by a lower bias (bias ± standard deviation; −1.6 ± 6.5 mmHg vs. 14.3 ± 8.4 mmHg, p 2 monitoring allows anesthesiologists to provide safer respiratory management for patients undergoing non-intubated VATS