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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.

Efficient occlusion of particulate additives into a single crystal has garnered an ever‐increasing attention in materials science because it offers a counter‐intuitive yet powerful platform to make crystalline nanocomposite materials with emerging properties. However, precisely controlling the spatial distribution of the guest additives within a host crystal remains highly challenging. We herein demonstrate a unique, straightforward method to engineer the spatial distribution of copolymer nanoparticles within calcite (CaCO3) single crystals by judiciously adjusting initial [Ca2+] concentration used for the calcite precipitation. More specifically, polymerization‐induced self‐assembly is employed to synthesize well‐defined and highly anionic poly(3‐sulfopropyl methacrylate potassium)41‐block‐poly(benzyl methacrylate)500 [PSPMA41‐PBzMA500] diblock copolymer nanoparticles, which are subsequently used as model additives during the growth of calcite crystals. Impressively, such guest nanoparticles are preferentially occluded into specific regions of calcite depending on the initial [Ca2+] concentration. These unprecedented phenomena are most probably caused by dynamic change in electrostatic interaction between Ca2+ ions and PSPMA41 chains based on systematic investigations. This study not only showcases a significant advancement in controlling the spatial distribution of guest nanoparticles within host crystals, enabling the internal structure of composite crystals to be rationally tailored via a spatioselective occlusion strategy, but also provides new insights into biomineralization. [ABSTRACT FROM AUTHOR]

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]

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.