心源性猝死一级预防植入心律转复除颤器前非持续室性心动过速与植入后恰当治疗的关系

目的探讨植入型心律转复除颤器(implantable cardioverter defibrillator,ICD)用于心源性猝死一级预防时,植入前发生非持续性室性心动过速(non-sustained ventricular tachycardia,NSVT)与植入后ICD恰当治疗的关系。方法本研究为单中心回顾性队列研究,连续纳入2006年1月至2017年12月在北京协和医院住院植入ICD用于一级预防的心脏病患者,患者在住院期间ICD植入前均完善Holter检查。根据Holter检查是否出现NSVT,将患者分为NSVT组及无NSVT组。门诊或电话随访至2018年8月,随访事件包括全因死亡、植入后ICD放电治疗及抗心动过速起搏(antitachycardia pacing,ATP)治疗情况。结果纳入60例符合入选和排除标准的患者,随访时间37 (14～61)个月,KaplanMeier生存曲线及Log-Rank检验提示,NSVT组与无NSVT组相比,全因死亡率无统计学差异(P=0. 108),NSVT组恰当治疗的风险高于无NSVT组(P=0. 033),NSVT和左心室射血分数与ICD恰当治疗独立相关(NSVT:HR=5. 099,95%CI:1. 399～18. 588,P=0. 014;左心室射血分数:HR=1. 077,95%CI:1. 013～1. 145,P=0. 018)。结论 ICD一级预防患者植入前出现NSVT提示接受ICD恰当治疗的风险增加。     

A Complexing Agent to Enable a Wide-Temperature Range Bromine-Based Flow Battery for Stationary Energy Storage

Bromine-based flow batteries (Br-FBs) are considered one of the most promising energy storage systems due to their features of high energy density and low cost. However, they generally suffer from uncontrolled diffusion of corrosive bromine particularly at high temperatures. That is because the interaction between polybromide anions and the commonly used complexing agent (N–methyl–N–ethyl–pyrrolidinium bromide [MEP]) decreases with increasing temperatures, which causes serious self-discharge and capacity fade. Herein, a novel bromine complexing agent, 1–ethyl–2–methyl–pyridinium bromide (BCA), is introduced in Br-FBs to solve the above problems. It is proven that BCA can combine with polybromide anions very well even at a high temperature of 60 °C. Moreover, the BCA contributes to decreasing the electrochemical polarization of Br⁻/Br₂ couple, which in turn improves their power density. As a result, a zinc–bromine flow battery with BCA as the complexing agent can achieve a high energy efficiency of 84% at 40 mA cm⁻², even at high temperature of 60 °C and it can stably run for more than 400 cycles without obvious performance decay. This paper provides an effective complexing agent to enable a wide temperature range Br-FB.     

Hierarchical Attention for Part-Aware Face Detection

International Journal of Computer Vision - Expressive representations for characterizing face appearances are essential for accurate face detection. Due to different poses, scales, illumination,...     

电喷雾质谱法示踪钨回收过程离子的转化路径

将环隙式离心萃取器(ACCs)与电喷雾飞行时间质谱(ESI-TOF-MS)相结合，在线监测了回收过程中的钨萃取行为(宏观)和钨形态的转化路径(微观)，发现宏观萃取反应和微观离子形态转化同时发生并相互补充。伯胺N1923萃取钨在144 s内即可达到萃取平衡，萃取率高达98%以上，同时，酸钨比n(H)/n(W)是一个关键变量，当酸钨比n(H)/n(W)=2.4时，全流程钨回收率超过93%。最后，得到了基于钨形态监测的萃取机理，同时，减少原料液中W1含量，增加W10含量，可有效提高钨回收效率。     

Design and synthesis of side-chain optimized poly(2,6-dimethyl-1,4-phenylene oxide)-g-poly(styrene sulfonic acid) as proton exchange membrane for fuel cell applications: Balancing the water-resistance and the sulfonation degree

Side-chain optimized poly (2,6-dimethyl-1,4-phenylene oxide)-g-poly (styrene sulfonic acid) (PPO-g-PSSA) is designed with balanced water-resistance and sulfonation degree. The PPO-g-PSSA is synthesized by controlled atom-transfer radical polymerization (ATRP) from brominated poly (2,6-dimethyl-1,4-phenylene oxide) (PPO-xBr) and ethyl styrene-4-sulfonate and followed by hydrolysis. A series of PPO-g-PSSA are prepared possessing different bromination degree (x) of PPO-xBr and polymerization degree (m) of the side-chains and the water-resistances of the fabricated membranes are investigated. The results show that a PPO-g-PSSA at relatively low x (x < 0.2) and high m (m > 4) exhibits good balance between the water-resistance and the sulfonation degree. Namely, it displays suitable proton conductivity with compromised water-resistance. Moreover, a maximum ion exchange capacity (IEC) of 3.24 mmol g^?1 is reached without the sacrifice of water-resistance. In addition, PPO-g-0.08PSSA-13 and PPO-g-0.14PSSA-4 are chosen characterized by thermogravimetric analysis, proton conductivities and mechanical properties. At 90% RH, the optimized PPO-g-0.08PPSA-13 possesses a proton conductivity of 37.9 mS cm^?1 at 40 °C and 45.5 mS cm^?1 at 95 °C, respectively.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

Mitigating Hydrological Risk with Energy Derivatives

The variability of river inflows affects the energy production of hydropower generators and may result in reductions in revenues that can be financially disruptive for these producers. Recent climatic changes have highlighted the risks involved in hydroelectriciy production in Brazil. In this paper, we propose a different approach to formulating a collar derivative, namely an Inverted Collar, to mitigate hydrological risk considering the particularities of Brazil's energy regulatory environment. In addition, we propose a customized collar-by-difference as a variation of the collar model. The effect of these derivatives is analyzed considering electricity market price and power generation uncertainty for a typical hydro generator. The results suggest that these derivatives are effective tools to manage hydrological risk during period of great climatic volatility, such as the height of the drought period experienced by Brazil in 2016. The results also indicate that our models outperform traditional commercial hedging commonly practiced by hydropower producers in the country.     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

Improved Corrosion Resistance of Selective Laser Melted Ti–5Cu Alloy Using Atomized Ti–5Cu Powder

The different types of metal powder used for selective laser melting(SLM) process would cause distinct corrosion behavior due to the uniformity of the obtained microstructure.The SLM-produced Ti–5Cu alloy using atomized Ti–5Cu metal powder(SLMed Ti–5Cu) in this work reveals a relatively uniform microstructure with overwhelming acicular α/α′ phase and shows great advantages on corrosion resistance compared with the SLM-produced Ti–5Cu alloy using the mixture powder(SLMedM Ti–5Cu).The effect of the micro-galvanic cells decreases due to the undetectable Ti_2Cu phase in the microstructure of the SLMed Ti–5Cu.An apparent passivation behavior was observed for SLMed Ti–5Cu instead of severe pitting phenomenon for the SLMed-M Ti–5Cu.The charge transfer resistance of SLMed Ti–5Cu in this work is 10.09 ± 2.63 MΩ cm~2, which is significantly higher than that of SLMed-M Ti–5Cu(4.76 MΩ cm~2).The above result indicates the atomized Ti–5Cu powder plays an important role in the formation of the uniform microstructure of SLMed product, thereby enhancing its corrosion resistance in Hank's solution at 37 ℃.