Impedance matching optimization of SiCf/Si3N4–SiOC composites for excellent microwave absorption properties

SiC fiber reinforced ceramic matrix composites (SiC_f-CMCs) are considered to be one of the most promising materials in the electromagnetic (EM) stealth of aero-engines, which is expected to achieve strong absorption and broad-band performance. Multiscale structural design was applied to SiC_f/Si₃N₄–SiOC composites by construction of micro/nanoscale heterogeneous interfaces and macro double-layer impedance matching structure. SiC_f/Si₃N₄–SiOC composites were fabricated by using SiC fibers with different conductivities and SiOC–Si₃N₄ matrices with gradient impedance structures to improve impedance matching effectively. Owing to its unique structure, SiC_f/Si₃N₄–SiOC composites (A3-composites) achieved excellent EM wave absorption performance with a minimum reflection coefficient (RC_min) of ?25.1 dB at 2.45 mm and an effective absorption bandwidth (EAB) of 4.0 GHz at 2.85 mm in X-band. Moreover, double-layer SiC_f/Si₃N₄–SiOC with an improved impedance matching structure obtained an RC_min of ?56.9 dB and an EAB of 4.2 GHz at 3.00 mm, which means it can absorb more than 90% of the EM waves in the whole X-band. The RC is less than ?8 dB at 2.6–2.8 mm from RT to 600 °C in the whole X-band, displaying excellent high-temperature absorption performance. The results provide a new design opinion for broad-band EM absorbing SiC_f-CMCs at high temperatures.     

高光谱成像用高帧频CMOS图像传感器北大核心

针对高帧频、全局曝光和光谱平坦等成像应用需求,设计了一款高光谱成像用CMOS图像传感器。其光敏元采用PN型光电二极管,读出电路采用5T像素结构。采用列读出电路以及高速多通道模拟信号并行读出的设计方案来获得低像素固定图像噪声(FPN)和非均匀性抑制。芯片采用ASMC 0.35μm三层金属两层多晶硅标准CMOS工艺流片,为了抑制光电二极管的光谱干涉效应,后续进行了光谱平坦化VAE特殊工艺,并对器件的光电性能进行了测试评估。电路测试结果符合理论设计预期,成像效果良好,像素具备积分可调和全局快门功能,最终实现的像素规模为512×256,像元尺寸为30μm×30μm,最大满阱电子为400 ke^(-),FPN小于0.2%,动态范围为72 dB,帧频为450 f/s,相邻10 nm波段范围内量子效率相差小于10%,可满足高光谱成像系统对CMOS成像器件的要求。     

日本の寒地，北海道における2030年代の水稲生育への温暖化の影響予測とその対応(日语原文)

北海道では1980年代から2010年代まで，水稲圃場栽培期間である5–9月の気温は年代とともに上昇した。そこで，直近の2010年代（2010—2019年平均）と比べて， 2つの2030年代の予測気象から，既報の関係式より水稲生育を予測した。その結果，2030年代では2010年代に比べ，限界移植日（移植早限）が水稲栽培17地域の平均で8～9日早い。また，早限出穂期が1～5日早く，晩限出穂期が1～5日遅く，安全出穂期間が2～10日長い。出穂期は1～3日早い。出穂期から晩限出穂まで2～9日長いため，遅延型冷害の発生がやや少ない。生育期別気象は，出穂前24日以降30日間では生育が早いため平均気温が同じかやや低い。出穂前10日以降40日間および出穂期以降40日間では平均気温がやや高く，日射量はやや少ない。そのため，玄米収量は96～98％とやや低く，潜在収量性を示す気候登熟量示数は同じである。障害不稔発生に関係する穂ばらみ期冷害危険期の平均気温はわずかに低いかほぼ同じであるため，冷害発生の危険性は残る。一方，不稔発生をもたらす低温域の出現頻度には，地域間で差異がある。精米蛋白質含有率は同じであるが，アミロース含有率はやや低く，やや良食味である。米粒外観品質では被害粒歩合と着色粒歩合は一定の傾向がなく，未熟粒歩合はやや高い。精米白度は同じであるが，玄米白度はやや高い。以上の予測に対する技術的対応方向を示した。     

大数据环境下基于K中心点优化算法的Web服务组合

在当前Web服务海量增加、现有Web服务选择算法低效、用户匹配度差的基础上，针对K中心点算法存在的质点偏移、准确率低和容易发生畸变等问题，提出一种大数据环境下基于K中心点优化算法的Web服务组合方法。该方法是在大数据环境下，根据不同用户需求满意度及Web服务QoS参数，对基于优化初始聚类中心的K中心点算法的Web服务选择及最优Web服务组合进行研究。同时针对不同的选择方法对服务动态选择及组合的准确度、迭代更新次数、候选集选择时间及选择总时间进行实验分析，验证了本文研究方法的有效性和可靠性。     

全局力平衡PDC钻头布齿优化设计

针对聚晶金刚石复合片(PDC)钻头在钻井破岩过程中因受力不平衡，导致钻井倾斜、井径扩大、钻头产生横向振动和涡动，造成钻头早期失效的问题，基于已有PDC钻头切削力学知识，构建了PDC钻头弯曲力矩及全局力平衡布齿优化设计模型，并提出模型求解方法。布齿设计实例结果表明，采用全局力平衡布齿设计方法得到的布齿结构可使PDC钻头在不同进尺条件下均能保持全局力平衡状态，尤其低进尺（小于1 mm）时的力平衡状态得到极大改善，提高了PDC钻头的钻井稳定性，对于改善钻头受力、提升钻头使用寿命、提高钻井质量与效率具有重要意义。     

All the players in the game: driving home the global commitment for legitimate drugs

Substandard, falsified, and counterfeit medications are a concern for the industry and for the public’s health. Data collection and research on these illegitimate drugs must continue to be a priority and common recommendations must be implemented immediately. The health of the public continues to be at risk, and as such global consensus and collaboration must be swift. Process improvements and policy decisions can support expert recommendations while technology and research continue to drive home change. Addressing counterfeit and substandard drugs is cost effective, feasible, and the right thing to do.     

Hierarchical sampling optimization of particle filter for global robot localization in pervasive network environment

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.     

Global optimization of stiff dynamical systems

We present a deterministic global optimization method for nonlinear programming formulations constrained by stiff systems of ordinary differential equation (ODE) initial value problems (IVPs). The examples arise from dynamic optimization problems exhibiting both fast and slow transient phenomena commonly encountered in model-based systems engineering applications. The proposed approach utilizes unconditionally stable implicit integration methods to reformulate the ODE-constrained problem into a nonconvex nonlinear program (NLP) with implicit functions embedded. This problem is then solved to global optimality in finite time using a spatial branch-and-bound framework utilizing convex/concave relaxations of implicit functions constructed by a method which fully exploits problem sparsity. The algorithms were implemented in the Julia programming language within the EAGO.jl package and demonstrated on five illustrative examples with varying complexity relevant in process systems engineering. The developed methods enable the guaranteed global solution of dynamic optimization problems with stiff ODE–IVPs embedded.     

数据中心湖水源自然冷却系统现场性能测试分析

为解决数据中心冷却系统能耗高、能源利用效率低的问题,自然冷却技术得到了广泛应用。以东江湖数据中心湖水源自然冷却系统为测试对象,详细测试了系统的实际运行性能,并讨论了其节能性,旨在为数据中心自然冷却系统运行设计提供实际数据支撑。测试结果表明:湖水源自然冷却系统的综合性能系数高达11,相比国家政策要求(新建大型数据中心PUE≤1.3),其能耗可进一步降低16%;此外,末端精密空调能耗占自然冷却系统总能耗50%以上,是自然冷却进一步降低能耗的关键。