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The diesel engine combustion process is mainly controlled by the fuel injection characteristics, which will have a direct impact on the performance of the diesel engine, more flexible injection strategy is the development direction of high pressure common-rail system. In order to obtain the change law of the performance of extra-high pressure common-rail diesel engine under variable injection strategy, and improve the overall performance of diesel engine, the effect of different post-injection parameters on the performance of diesel engine was studied on a self-designed extra-high pressure common-rail diesel engine experiment bench, and the relevant results were discussed and analyzed. The results show that: with the rise of post-injection fuel quantity, NOx concentration and soot concentration decrease gradually, and with the rise of post-injection interval angle, NOx concentration decreases gradually, while soot concentration first decreases and then increases. Therefore, choosing post-injection fuel quantity and post-injection interval angle rationally can achieve lower NOx and soot emission at the same time. Meanwhile, with the rise of post-injection fuel quantity or post-injection interval angle, the fuel consumption rate presents an increasing trend.

Although strategies of olefin hydroalkylation continue to emerge rapidly, the precise control of the regio- or chemoselectivity and the expansion of the reaction range are still challenges. Herein, a straightforward route for cobalt-catalyzed anti-Markovnikov hydroalkylation of unactivated olefins with alkyl iodides has been achieved. The developed reaction is compatible with oxa-, aza-, cyclo- and a series of other functional groups as well as the frameworks of some bioactive compounds. Mechanism studies confirm that an alkyl radical is involved and cobalt–alkyl insertion followed by protonation with water are possible pathways in this reaction. [ABSTRACT FROM AUTHOR]

Constructing accurate spatiotemporal correlations is a challenging task in joint prediction of multiple photovoltaic sites. Some advanced algorithms for incorporating other surrounding site information have been proposed, such as graph neural network-based methods, which are usually based on static or dynamic graphs to build spatial dependencies between sites. However, the possibility of the simultaneous existence of multiple spatial dependencies is not considered. This paper establishes a spatiotemporal prediction model based on hybrid spatiotemporal graph neural network. In this model, we apply adaptive hybrid graph learning to learn composite spatial correlations among multiple sites. A temporal convolution module with multi-subsequence temporal data input is used to extract local semantic information to better predict future nonlinear temporal dependencies. A spatiotemporal adaptive fusion module is added to address the issue of integrating diverse spatiotemporal trends among multiple sites. To assess the model's predictive performance, nine solar radiation observation stations were selected in two different climatic environments. The average root mean square error (RMSE) of the constructed model was 38.51 and 49.90 W/m2, with average mean absolute error (MAE) of 14.72 and 23.06 W/m2, respectively. Single-site and multi-site prediction models were selected as baseline models. Compared with the baseline models, the RMSE and MAE reduce by 3.1%–20.8% and 8.9%–32.8%, respectively, across all sites. The proposed model demonstrates the effectiveness of improving accuracy in forecasting solar irradiance through multi-site predictions. [ABSTRACT FROM AUTHOR]

Sugarcane yellow leaf virus (SCYLV), a member of the genus Polerovirus in the family Luteoviridae, causes severe damage and represents a great threat to sugarcane cultivation and sugar industry development. In this study, inoculation of Nicotiana benthamiana plants with a potato virus X (PVX)-based vector carrying the SCYLV P0 gene induced typical mosaic, leaf rolling symptoms and was associated with a hypersensitive-like response (HLR) necrosis symptom, which is accompanied with a systemic burst of H2O2 and also leads to higher PVX viral genome accumulation levels. Our results demonstrate that SCYLV P0 is a pathogenicity determinant and plays important roles in disease development. To further explore its function in pathogenic processes, a yeast two-hybrid assay was performed to screen the putative P0-interacting host factors. The recombinant plasmid pGBKT7-P0 was constructed as a bait and transformed into the yeast strain Y2HGold. The ROC22 cultivar (an important parental resource of the main cultivar in China) cDNA prey library was constructed and screened by co-transformation with the P0 bait. We identified 28 potential interacting partners including those involved in the optical signal path, plant growth and development, transcriptional regulation, host defense response, and viral replication. To our knowledge, this is the first time we have reported the host proteins interacting with the P0 virulence factor encoded by sugarcane yellow leaf virus. This study not only provides valuable insights into elucidating the molecular mechanism of the pathogenicity of SCYLV, but also sheds light on revealing the probable new pathogenesis of Polerovirus in the future.

Both glucose-regulated protein 78 kDa (GRP78) and glucose-regulated protein 94 kDa (GRP94) are important molecular chaperones that play critical roles in maintaining tumor survival and progression. This study investigated the effects in prostate cancer cells following the downregulation of GRP78 and GRP94.

Little is known about the influence of metabolic syndrome (MetS) on coronary artery calcification (CAC) in China. In this article, we aimed to explore the distribution of CAC in populations with and without MetS, and estimate the influence of MetS and its components on CAC in a community-based population of Beijing.A total of 1647 local residents of Beijing, age 40-77 years, were recruited for a cardiovascular risk factors survey and were determined fasting plasma glucose (FPG), blood lipids, and 64 multi-detector computed tomography (64-MDCT) coronary artery calcium score (CACS) measurement (Agatston scoring). The distribution of CAC was described, and the influence of MetS components on CAC was evaluated.In this population, the prevalence and extent of CAC increased with increasing age and both were higher in MetS subjects compared to nonMetS subjects (all P < 0.05), with the exception of those older than 65 years old. The risk of CAC increased with increasing numbers of MetS components, and the odds ratios for predicting positive CAC in subjects with 1, 2, 3, and = 4 MetS components were 1.60, 1.84, 2.12, and 3.12, respectively (all P < 0.05). Elevated blood pressure, elevated FPG, elevated triglycerides, and overweight increased the risk of CAC, yielding odds ratios of 2.64, 1.67, 1.32, and 1.37, respectively (all P < 0.05).In the Beijing community-based population, MetS increases the risk of CAC. The risk of CAC increases with increasing numbers of MetS components. Not only the number, but also the variety of risk factors for MetS is correlated with the risk of CAC. Elevated blood pressure, hyperglycemia, hypertriglyceridemia and overweight increase the risk of CAC.