药物相互作用研究在新药研发和审评决策中的应用

药物相互作用改变了剂量效应关系，可能会降低疗效或增加毒性，是临床应用中合并用药治疗时重要的考虑因素。预测具有临床意义的药物相互作用是药物研发过程中获益风险评估的重要环节。本文概述了药物研发过程中药物相互作用研究的目的和意义，体内和体外研究的主要内容；梳理分析了2020年国家药品监督管理局（National Medical Products Administration, NMPA）和美国食品药品监督管理局（Food and Drug Administration, FDA）批准上市的新药药物相互作用研究情况，旨在为我国药物研发过程中药物相互作用研究及其监管审评提供参考。     

High lithium storage of Co3O4 enabled by integrating hollow and porous carbon scaffolds

The Co₃O₄, as a potential anode of lithium-ion batteries, has gained considerable attention because of high theoretical capacity. However, the Co₃O₄ is suffering from serious structure deterioration and rapid capacity fading due to its bulky volume change during cyclic charge/discharge process. Herein, to stabilize the lithium storage performance of the Co₃O₄ nanoparticles, a characteristic carbon scaffold (HPC) integrating hollow and porous structures has been fabricated by a well-designed method for the first time. The ultrafine Co₃O₄ nanoparticles are cleverly anchored on the HPC (HPC@Co₃O₄) and hence achieve significantly improved electrochemical properties including high capacity, improved reaction kinetics and outstanding cycle stability, showing high capacity of 1084.7 mAh g^-1 after 200 cycles at 200 mA g^-1 as well as 681.4 mAh g^-1 after 300 cycles at 1000 mA g^-1. The HPC@Co₃O₄ therefore shows good promising for application in advanced lithium-ion battery anodes. The results of the systematically material and electrochemical characterizations indicate that the synergistic effects of ultrafine Co₃O₄ nanoparticles and well-designed HPC scaffolds are responsible for the outstand performance of the HPC@Co₃O₄ anode. Moreover, this work can enrich the understanding and development of stable and high-performance metal oxide-based lithium-ion battery anodes for advanced lithium storage.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

计算机网络办公自动化及安全策略探究

互联网通讯采取标准化模式主要以TCP/IP协议为载体,通讯的优越特性体现在同时具备便捷性与开放性,为办公提供很大的便利,但基于网络系统也会入侵病毒、也会给信息数据与办公体系安全性造成威胁,直接影响企业综合稳定发展。据此,为保障办公工作的顺利开展,本文对计算机网络办公自动化及安全策略进行详细分析。     

设计扶贫视角下西兰卡普的可持续设计策略研究

目的 探索湖北恩施地区西兰卡普的可持续设计策略。方法 分析隐身于贫困乡村的西兰卡普的文化价值和经济价值，对其进行设计转化的重要性与可行性分析；对湖北恩施地区西兰卡普进行实地考察与调研，梳理其可持续发展中所面临的传承主体和市场竞争方面的典型性困境与原由；以设计赋能传统手工艺作为设计扶贫的重要手段，基于西兰卡普所面临的困局系统性地提出其可持续性发展的设计策略。结论 在设计扶贫中，应构建多元主体参与、协同合作的再创新机制，注重强化造血能力，塑造地域名片，围绕当代消费需求，结合数字化技术进行展销模式、产品供给的升级和创新设计，并整合优势资源，实现产业的融合发展。总之，系统性地对西兰卡普进行设计赋能，是西兰卡普获得可持续性发展效力并助力当地贫困乡村经济发展的有效路径。     

广义正交码索引调制系统的性能分析

摘 要：为了提高码索引调制（code index modulation，CIM）系统的传输效率，提出了一种具有更低复杂度的单输入单输出（single input single output，SISO）的广义正交码索引调制（generalized orthogonal code index modulation，GQCIM）系统。CIM 系统使用扩频码和星座符号传输信息，但只能激活两个扩频码索引和一个调制符号。而 GQCIM 系统以一种新颖的方式克服了只激活一个调制符号的限制，同时充分利用了调制符号的正交性，增加扩频码索引以传输更多的额外信息位，提高了系统的传输效率。此外，分析了GQCIM系统的理论性能，推导了误码率性能的上界。通过蒙特卡罗仿真验证了GQCIM系统的性能，对比发现GQCIM系统的理论和仿真性能一致。而且在相同的传输效率下，结果显示GQCIM系统的性能优于同样具有正交性的调制系统，如广义码索引调制（generalized code index modulation，GCIM）系统、CIM系统、码索引调制-正交空间调制（code index modulation aided quadrature spatial modulation，CIM-QSM）系统、码索引调制-正交空间调制（code index modulation aided spatial modulation，CIM-SM）系统、脉冲索引调制（pulse index modulation，PIM）系统。     

Oxidation State Modulation of Bismuth for Efficient Electrocatalytic Nitrogen Reduction to Ammonia

Electrocatalytic nitrogen reduction reaction (NRR) is a promising strategy for ammonia (NH₃) production under ambient conditions. However, it is severely impeded by the challenging activation of the NN bond and the competing hydrogen evolution reaction (HER), which makes it crucial to design electrocatalysts rationally for efficient NRR. Herein, the rational design of bismuth (Bi) nanoparticles with different oxidation states embedded in carbon nanosheets (Bi@C) as efficient NRR electrocatalysts is reported. The NRR performance of Bi@C improves with the increase of Bi⁰/Bi³⁺ atomic ratios, indicating that the oxidation state of Bi plays a significant role in electrochemical ammonia synthesis. As a result, the Bi@C nanosheets annealed at 900  ° C with the optimal oxidation state of Bi demonstrate the best NRR performance with a high NH₃ yield rate and remarkable Faradaic efficiency of 15.10  ± 0.43% at − 0.4 V versus RHE. Density functional theory calculations reveal that the effective modulation of the oxidation state of Bi can tune the p-filling of active Bi sites and strengthen adsorption of *NNH, which boost the potential-determining step and facilitate the electrocatalytic NRR under ambient conditions. This work may offer valuable insights into the rational material design by modulating oxidation states for efficient electrocatalysis.     

Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time scheduling has become a problem to be solved. In this regard, automatic design for shop scheduling based on hyper-heuristics has been widely studied, and a number of reviews and scheduling algorithms have been presented. Few studies, however, have specifically discussed the technical points involved in algorithm development. This study, therefore, constructs a general framework for automatic design for shop scheduling strategies based on hyper-heuristics, and various state-of-the-art technical points in the development process are summarized. First, we summarize the existing types of shop scheduling strategies and classify them using a new classification method. Second, we summarize an automatic design algorithm for shop scheduling. Then, we investigate surrogate-assisted methods that are popular in the current algorithm field. Finally, current problems and challenges are discussed, and potential directions for future research are proposed.     

可重构智能表面辅助的四元数调制无线通信系统

四元数调制(Quaternion Modulation,QMod)是一种新型高传输速率的极化调制(Polarized Modulation,PMod)技术,是未来卫星通信系统中极具潜力的多元调制方案之一。QMod将数据块分成4块,其中两块是传输数据信号,另外两块则映射到极化状态部分。每个极化状态块均有一位比特,那么它们可以产生4个极化状态组合。这些状态组合可以用来确定传输数据块在四元数4个不同维度中的位置,从而获得两位额外的传输比特。相比于传统的PMod技术,QMod有着更高的频谱效率。为了进一步挖掘QMod的潜力,介绍了由可重构智能表面(Reconfigurable Intelligent Surface,RIS)辅助的QMod系统,同时推导了该系统的平均误码率理论上界,并在瑞利信道下进行了BER性能仿真。仿真结果表明,RIS辅助的PMod或者QMod系统即便在较低的SNR情况下仍有良好的BER性能,并且随着RIS单元数的增多,其BER性能会逐步提升。