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Clarifying the water invasion rule of edge and bottom water reservoirs can adjust the reservoir development mode and improve the recovery factor of edge and bottom water reservoirs in a timely manner. Influenced by the size of a reservoir water body, energy intensity and reservoir seepage capacity, the change model of reservoir water influx basically belongs to the exponential growth model of the GM (1,1) model or the self-constraint growth model of the logistic model. The above two models are used to predict and analyze the water inflow of edge and bottom water reservoirs, respectively, and it is found that the change in water inflow of the reservoir with sufficient edge and bottom water energy is more consistent with the prediction results of the GM (1,1) model, but it has a large error compared to the prediction results of the logistic model. The change in water influx in the reservoir with insufficient edge and bottom water energy is consistent with the prediction results of the logistic model and GM (1,1) model. The research shows that the strength of edge and bottom water energy of the reservoir can be determined by analyzing the error of the logistic model in predicting water influx. If we focus on the change in reservoir water influx, the improved GM (1,1) model formed by a Newton parabola interpolation polynomial is used to optimize its background value, which can further improve the prediction accuracy and reduce the prediction error of water inflow of edge and bottom water reservoirs. The method in this paper has certain reference significance for studying the water invasion rule and energy intensity of edge and bottom water reservoirs.

Background: Developing students’ metacognition awareness is a goal of university education as it can help equip students with life-long learning skills and promote holistic personal development. This study aimed to explore the effect of nursing comprehensive skill training course (NCST-C) on metacognitive awareness of nursing students in China, to provide a scientific foundation for improving metacognitive awareness.Design: A quasi-experimental two-group, matched pretest, post-test, and follow-up test.Methods: A total of 96 Junior nursing students were recruited using a convenience sampling and assigned to 2 groups by drawing lots with odd and even numbers in a nursing school at Huzhou University, China. The control group was received the traditional skill-training course. The intervention group was received training in NCST-C. Nursing students were evaluated metacognitive awareness inventory (MAI) at the baseline, 16-week, and 20-week follow-up points, respectively. A repeated-measures, two-way analysis of variance, and a simple effect test were used to compare each outcome measure of 2 groups.Results: The NCST-C resulted in a greater benefit for nursing students’ metacognition awareness and various dimensions (knowledge of cognition and regulation of cognition) in the intervention group. Combined with a simple effects test, the MAI and dimensions scores of those in the intervention groups significantly improved at 16 weeks after the baseline (F = 44.03-9.78); all P Conclusions: The NCST-C was an effective course to develop metacognition awareness of nursing students,which design provides a new form of experimental course to improve metacognition awareness.Trial registration: http://www.chictr.org.cn/listbycreater.aspxRegistration number:ChiCTR2200057910. First registration date 22/3/2022

During the no-load closing process, transformer will produce a magnetizing inrush current which will make the transformer relay malfunction and make adversely affect to the transformer equipment and power grid. Relative to a variety of external measures limiting the inrush current, the phase selection switch technology is more effective to reduce inrush current. The author analyzed inrush current by theory and dynamic simulation experiment. By controlling the closing angle to be less than 0° to 72° of the opening angle, inrush current is well suppressed.

Luliang oilfield has been in production since 2001 and was originally developed from vertical wells. To arrest production decline, operators embarked on a horizontal drilling campaign in 2006 to achieve ultimate field recovery from remaining oil. A proper geosolution to optimize reservoir exposure while maximizing distance from bottom and edge-water was recognized as the key for success in this field. From 2006 to 2015, the 10 years of field development was sustained through a close collaboration between the operator and service provider. However, production reviews indicate that the Luliang oilfield is approaching the end of its field life as the main underground reserve is drained away. As this mature oilfield becomes increasingly difficult to develop, well placement technologies become increasingly critical along with the commitment to service quality. With the challenge increasing, the well placement strategy and solutions must be reformed as well. Innovative use of well placement technology and workflows are crucial to ensure service quality while balancing drilling costs within the margin of economics. From 2006 to 2014, a total of 200 horizontal wells were successfully constructed, achieving net-to-gross over 94% and improving the field's recovery efficiency by over 96%. Both productivity and cumulative production of horizontal wells were significantly enhanced compared to the original objectives. In 2015, 14 horizontal wells are on going; thus, after 10 years, the extension of this mature field's vitality continuous to press on.

Protein kinase B (PKB) acts as a central node on the PI3K kinase pathway. Constitutive activation and overexpression of PKB have been identified to involve in various cancers. However, protein kinase A (PKA) sharing high homology with PKB is essential for metabolic regulation. Therefore, specific targeting on PKB is crucial strategy in drug design and development for antitumor. Here, we had revealed the selectivity mechanism for PKB inhibitors with molecular dynamics simulation and 3D-QSAR methods. Selective inhibitors of PKB could form more hydrogen bonds and hydrophobic contacts with PKB than those with PKA. This could explain that selective inhibitor M128 is more potent to PKB than to PKA. Then, 3D-QSAR models were constructed for these selective inhibitors and evaluated by test set compounds. 3D-QSAR model comparison of PKB inhibitors and PKA inhibitors reveals possible methods to improve the selectivity of inhibitors. These models can be used to design new chemical entities and make quantitative prediction of the specific selective inhibitors before resorting to in vitro and in vivo experiment.