生物酶辅助氧化镁碳化过程砂土加固试验研究

基于微生物或酶诱导碳酸盐沉积(即MICP和EICP)过程的固土技术具备固化强度高、环境友好等特点,但是目前也存在处理效率低、耗时长等局限。为克服这些局限,研究一种新型高效的生物固土技术,即基于植物脲酶辅助氧化镁碳化(酶辅助碳化)过程的固土法,探索其处理方法、效果和作用机理,并与单纯的氧化镁碳化、EICP和水泥等方法进行比较。结果表明,采用酶辅助碳化加固法时,一遍处理强度可达0.92 MPa,且试样的强度显著高于单纯氧化镁处理(0.30 MPa)、EICP处理(0.28 MPa)和水泥处理(0.69 MPa)。酶辅助碳化加固法处理试样的制备方式对强度影响较大。与注入法相比,采用拌和法处理的试样强度高了3倍。此外,添加少量脱脂奶粉后,酶辅助碳化加固法处理试样的强度进一步提升了约70%,达到1.30 MPa。通过微观结构和矿物成分分析发现,酶辅助碳化处理后,固化物填满了砂颗粒之间的孔隙,将砂颗粒结合在一起,形成稳定网格空间结构,与不添加脲酶的试样相比,其中的水合碳酸镁混合物含量较高,中间产物水镁石含量较低。

创新生态竞争视角下新型研发机构发展策略研究

为进一步综合研究分析新型研发机构发展策略,以1321家全国新型研发机构为研究对象,在系统总结新型研发机构发展现状的基础上,基于有关文献及有关理论研究,构建新型研发机构核心竞争力六维评价指标体系,通过人工蜂群(ABC)算法优化后的BP神经网络模型对新型研发机构核心竞争力进行评估。结果表明,35.30%的新型研发机构核心竞争力处于较强水平,总体上新型研发机构核心竞争力具有良好的发展基础和前景;新型研发机构主要通过延长创新服务链条、创新科技成果对接机制等策略占据有利的生态位。新型研发机构未来要进一步强化科技人才培养能力,创新企业孵化机制,激发科技金融竞争力来进一步推动新型研发机构高质量发展。

新生育政策背景下常州市育龄妇女生育意愿及影响因素分析

目的:探索新生育政策背景下常州市育龄妇女的生育意愿和影响因素。方法:通过配额和方便抽样方式对常州市育龄妇女进行现况调查,共调查4500人,对4426人(98.4%)的有效问卷进行分析。结果:调查对象的理想子女数(1.41±0.637)个,现有子女数(1.01±0.685)。调整肯定不生的混杂因素,与41~49岁年龄组相比,≤25岁年龄组有生育计划OR=48.849,95%CI 14.336~166.453;26~30岁组OR=52.416,95%CI 16.152~170.100;31~35岁组OR=31.525,95%CI 9.657~102.910;36~40岁组OR=10.104,95%CI 2.771~36.842。与个体/私营企业雇员组相比,无业组有生育计划OR=2.126,95%CI 1.370~3.302;机关事业单位/国企组的OR=1.572,95%CI 1.056~2.338;个体户/私营企业主OR=1.902,95%CI 1.123~3.224。与现有1孩组相比,现无子女组有生育计划的OR=4.872,95%CI 3.198~7.423;现有2孩组OR=0.203,95%CI 0.117~0.353;现有3孩组的OR=0.515,95%CI 0.185~1.428。年龄、就业状况和现有子女数是生育计划的影响因素。结论:常州市育龄妇女的生育意愿较低,未来生育形式不乐观,建议增加生育补贴、创新产假模式、完善配套福利措施和加强宣传引导,营造生育的友好社会氛围,真正提高育龄妇女的生育意愿。

基于CHAID决策树方法探讨生育多孩的影响因素

目的了解常州市育龄妇女的生育现状和生育意愿水平,探索主要影响因素。方法通过配额抽样,对20~49岁常住育龄妇女使用自行设计的电子问卷进行现场调查,采用CHAID决策树方法进行多因素分析。结果回收4426份有效问卷,平均生育子女数为(1.16±0.63)个,平均理想生育子女数为(1.41±0.66)个。建立的决策树模型显示,影响育龄妇女生育意愿的主要因素为:对多孩有利于成长的看法、现有孩子数、配偶及长辈对生育多孩的态度、对生育影响身体健康和身材的焦虑等。该决策树对是、否愿意生育多孩的预测正确率分别为75.98%和84.44%,总体正确预测百分比80.77%,标准误差0.007;是、否愿意生育多孩的最优路线预测正确率分别为96.42%和90.60%。结论决策树模型可有效预测育龄妇女生育意愿。当前常州市育龄妇女的生育率和生育意愿较低,对多孩有利于成长的看法是影响生育意愿的首要关键因素。

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017,it was first used for machine translation tasks and achieved the state of the art at that time.Although the current neural machine translation model can generate high quality translation results,there are still mistranslations and omissions in the translation of key information of long sentences.On the other hand,the most important part in traditional translation tasks is the translation of key information.In the translation results,as long as the key information is translated accurately and completely,even if other parts of the results are translated incorrect,the final translation results’quality can still be guaranteed.In order to solve the problem of mistranslation and missed translation effectively,and improve the accuracy and completeness of long sentence translation in machine translation,this paper proposes a key information fused neural machine translation model based on Transformer.The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder.After the same encoding as the source language text,it is fused with the output of the source language text encoded by the encoder,then the key information is processed and input into the decoder.With incorporating keyword information from the source language sentence,the model’s performance in the task of translating long sentences is very reliable.In order to verify the effectiveness of the method of fusion of key information proposed in this paper,a series of experiments were carried out on the verification set.The experimental results show that the Bilingual Evaluation Understudy(BLEU)score of the model proposed in this paper on theWorkshop on Machine Translation(WMT)2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset.The experimental results show the advantages of the model proposed in this paper.

Formal Verification Platform as a Service:WebAssembly Vulnerability Detection Application

In order to realize a general-purpose automatic formal verification platform based on WebAssembly technology as a web service(FVPS),which aims to provide an automated report of vulnerability detections,this work builds a Hyperledger Fabric blockchain runtime model.It proposes an optimized methodology of the functional equivalent translation from source program languages to formal languages.This methodology utilizes an external application programming interface(API)table to replace the source codes in compilation,thereby pruning the part of housekeeping codes to ease code inflation.Code inflation is a significant metric in formal language translation.Namely,minor code inflation enhances verification scale and performance efficiency.It determines the efficiency of formal verification,involving launching,running,and memory usage.For instance,path explosion increases exponentially,resulting in out-of-memory.The experimental results conclude that program languages like golang severely impact code inflation.FVPS reduces the wasm code size by over 90%,achieving two orders of optimization magnitude,from 2000 kilobyte(KB)to 90 KB.That means we can cope with golang applications up to 20 times larger than the original in scale.This work eliminates the gap between Hyperledger Fabric smart contracts and WebAssembly.Our approach is pragmatic,adaptable,extendable,and flexible.Nowadays,FVPS is successfully applied in a Railway-Port-Aviation blockchain transportation system.

化妆品防腐剂氯苯甘醚复配体的制备

对化妆品防腐剂氯苯甘醚、乙基己基甘油和苯氧乙醇进行复配试验,并得出微生物抑菌圈实验最佳配比,然后进行了最小抑菌浓度(MIC)值的测定和微生物挑战试验及毒理性试验。结果表明,复配防腐剂的氯苯甘醚、乙基己基甘油和苯氧乙醇配比为1∶1∶3时抑菌效果最佳,并通过了毒理性测试。该复配防腐剂是优良的化妆品防腐剂。

一类季节交替下具有一般功能反应的捕食-食饵模型的动力学分析

研究一类季节交替下带有一般功能反应的捕食-食饵模型.基于季节环境变化,将模型分为2个过程:第1个过程中种群间存在捕食关系;第2个过程中种群间无捕食关系.利用分析手段及比较定理等方法研究模型的有界性和持久性等动力学行为,并给出了具有积分形式的判定条件.最后通过数值模拟验证了所得结论的有效性.

油田污水分离处理法

目前中国大部分油田已进入开发的中后产期,产出液中的平均含水率已经达到80%,这种现状导致了大量的油田污水的产生。本文概述了油田注水井污水分离处理方法以及研制进展情况,阐述了目前国内油田污水处理技术的现状及发展趋势。

Hyperparameter Optimization for Machine Learning Models Based on Bayesian Optimization

Hyperparameters are important for machine learning algorithms since they directly control the behaviors of training algorithms and have a significant effect on the performance of machine learning models. Several techniques have been developed and successfully applied for certain application domains. However, this work demands professional knowledge and expert experience. And sometimes it has to resort to the brute-force search.Therefore, if an efficient hyperparameter optimization algorithm can be developed to optimize any given machine learning method, it will greatly improve the efficiency of machine learning. In this paper, we consider building the relationship between the performance of the machine learning models and their hyperparameters by Gaussian processes. In this way, the hyperparameter tuning problem can be abstracted as an optimization problem and Bayesian optimization is used to solve the problem. Bayesian optimization is based on the Bayesian theorem. It sets a prior over the optimization function and gathers the information from the previous sample to update the posterior of the optimization function. A utility function selects the next sample point to maximize the optimization function.Several experiments were conducted on standard test datasets. Experiment results show that the proposed method can find the best hyperparameters for the widely used machine learning models, such as the random forest algorithm and the neural networks, even multi-grained cascade forest under the consideration of time cost.

Field trial on use of soybean crude extract for carbonate precipitation and wind erosion control of sandy soil

Wind erosion is a major cause of land desertification and sandstorm formation in arid and semi-arid areas.The objective of this study was to evaluate the potential of soybeans crude extract induced calcium carbonate precipitation(SICP)on reducing wind erosion risk of sandy soil.Field tests were carried out in Ulan Buh Desert,Ningxia Hui Autonomous Region,China.Results showed that the SICP method could significantly enhance the surface strength and wind erosion resistance of the topsoil.The optimal cementation solution(urea-CaCl2)concentration and spraying volume,according to experiments conducted on sandy land,were 0.2 mol/L and 4 L/m^2,respectively.Under this condition,the CaCO3 content was approximately 0.45%,the surface strength of sandy soil could reach 306.2 kPa,and the depth of wind erosion was approximately zero,after 30 d completion of SICP treatment.Soil surface strength declined with the increase of time,and long-term sand fixation effects of SICP treatment varied depending on topography.Whereas wind erosion in the top area of the windward slope was remarkable,sandy soils on the bottom area of the windward slope still maintained a relatively high level of surface strength and a low degree of wind erosion 12 month after SICP treatment.Scanning electron microscopy(SEM)tests with energy dispersive X-ray(EDX)confirmed the precipitation of CaCO3 and its bridge effect.These findings suggested that the SICP method is a promising candidate to protect sandy soil from wind erosion in desert areas.

Coordination and interface engineering to boost catalytic property of two-dimensional ZIFs for wearable Zn-air batteries

Metal organic frameworks(MOFs) have been considered as compelling precursor for miscellaneous applications. However, their unsatisfied electrocatalytic performance limits their direct application as electrocatalyst. Herein, by incorporating the cobalt-oxide bonds and polyaniline(PANI) with two-dimension zeolitic imidazolate frameworks(ZIFs), a novel bifunctional catalyst(Co-O-ZIF/PANI) for Zn-air battery was designed based on a facile and eco-friendly method. This Co-O-ZIF/PANI with optimized surface adsorption effect and suitable Co^(3+)/Co^(2+)ratio, exhibits eminent electrocatalytic activity toward both oxygen reduction and evolution reaction. The as-assembled liquid ZABs based on Co-O-ZIF/PANI achieves a remarkable maximum power density of 123.1 m W cm^(-2) and low discharge-charge voltage gap of 0.81 V at 5 m A cm^(-2) for over 300 cycles. Operando Raman spectroscopy reveals that the excellent performance origins from the optimized surface chemisorption property of O_(2) and H_(2)O brought by Co–O bonds and PANI. This work provides a novel prospect to develop efficient MOF derived bifunctional electrocatalysts by optimizing surface chemisorption properties.

县级公立医院护理人员工作场所暴力与职业倦怠研究

文章探究县级公立医院护理人员工作场所暴力与职业倦怠情况。利用系统抽样方式选取某一县域内县级医院886名护理人员开展横断面调查,运用描述性统计分析暴力及职业倦怠情况,对不同特征研究对象的倦怠得分差异进行方差分析,利用多元分层回归分析探究工作场所暴力对职业倦怠的影响。研究结果显示,样本县级医院暴力发生率为73.02%,情感虐待是最主要的暴力形式。研究对象的职业倦怠得分高于M氏常模,职业倦怠情况不容忽视,护龄5~14年、身为独生子女、中级职称、加班天数较多的护理人员倦怠情况更为突出。遭受工作场所暴力是影响职业倦怠的一个重要变量。应重视县级医院的工作场所暴力和职业倦怠情况,建立安全机制有效防范化解工作场所暴力,合理分配工作负荷,激励工作成效,构建职业发展规划,创建社会支持系统,降低职业倦怠。

微生物诱导碳酸钙沉积联合黄原胶加固砂土室内试验研究

微生物诱导碳酸钙沉积加固法(MICP法)和黄原胶均能够有效地改善砂土的力学特性。然而,一次微生物固化处理在砂土中产生的碳酸钙含量往往较少,对砂土力学特性的增强作用有限。黄原胶对土体的加固效果受水流的影响较大。因此,本文通过无侧限单轴压缩试验,探究微生物诱导碳酸钙沉积联合黄原胶对砂土力学特性的加固效果。在无侧限单轴压缩试验中,微生物诱导碳酸钙沉积联合黄原胶固化砂的无侧限抗压强度,高于微生物诱导碳酸钙沉积固化砂或黄原胶固化砂的强度,并且随着处理液中黄原胶浓度的增加,微生物诱导碳酸钙沉积联合黄原胶固化砂的无侧限抗压强度增大。

Insights on the mechanism of Na-ion storage in expanded graphite anode

Currently,Na-ion battery(NIB) has become one of the most potential alternatives for Li-ion batteries due to the safety and low cost.As a promising anode for Na-ion storage,expanded graphite has attracted considerable attention.However,the sodiation-desodiation process is still unclear.In our work,we obtain expanded graphite through slight modified Hummer's method and subsequent thermal treatment,which exhibits excellent cycling stability.Even at a high current density of 1 A g^(-1),our expanded graphite still remains a high reversible capacity of 100 mA h g^(-1) after 2600 cycles.Furthermore,we also investigate the electrochemical mechanism of our expanded graphite for Na-ion storage by operando Raman technique,which illuminate the electrochemical reaction during different sodiation-desodiation processes.

Partitioned k-Exclusion Real-Time Locking Protocol Motivated by Multicore Multi-GPU Systems

Graphic processing units （GPUs） have been widely recognized as cost-efficient co-processors with acceptable size, weight, and power consumption. However, adopting GPUs in real-time systems is still challenging, due to the lack in framework for real-time analysis. In order to guarantee real-time requirements while maintaining system utilization ~in modern heterogeneous systems, such as multicore multi-GPU systems, a novel suspension-based k-exclusion real-time locking protocol and the associated suspension-aware schedulability analysis are proposed. The proposed protocol provides a synchronization framework that enables multiple GPUs to be efficiently integrated in multicore real-time systems. Comparative evaluations show that the proposed methods improve upon the existing work in terms of schedulability.

车用大功率燃料电池低温冷启动分析

质子交换膜燃料电池低温冷启动被认为是影响燃料电池汽车商业化的主要因素之一。文章根据某款燃料电池车型开发目标需求,对匹配的120 kW大功率燃料电池在-30°C低温启动热平衡初步分析,基于电堆外加热控制策略,经初步匹配计算,在理想情况下需要13 min才能启动,为拟开发目标设定提供了依据。文章对开发大功率燃料电池乘用车具有参考意义。

SET-MRTS:An Empirical Experiment Tool for Real-Time Scheduling and Synchronization

In the real-time scheduling theory,schedulability and synchronization analyses are used to evaluate scheduling algorithms and real-time locking protocols,respectively,and the empirical synthesis experiment is one of the major methods to compare the performance of such analyses.However,since many sophisticated techniques have been adopted to improve the analytical accuracy,the implementation of such analyses and experiments is often time-consuming.This paper proposes a schedulability experiment toolkit for multiprocessor real-time systems(SET-MRTS),which provides a framework with infrastructures to implement the schedulability and synchronization analyses and the deployment of empirical synthesis experiments.Besides,with well-designed peripheral components for the input and output,experiments can be conducted easily and flexibly on SET-MRTS.This demonstration further proves the effectiveness of SET-MRTS in both functionality and availability.

Balanced Functional Maps for Three-Dimensional Non-Rigid Shape Registration

Three-dimensional(3D)shape registration is a challenging problem,especially for shapes under non-rigid transformations.In this paper,a 3D non-rigid shape registration method is proposed,called balanced functional maps(BFM).The BFM algorithm generalizes the point-based correspondence to functions.By choosing the Laplace-Beltrami eigenfunctions as the function basis,the transformations between shapes can be represented by the functional map(FM)matrix.In addition,many constraints on shape registration,such as the feature descriptor,keypoint,and salient region correspondence,can be formulated linearly using the matrix.By bi-directionally searching for the nearest neighbors of points’indicator functions in the function space,the point-based correspondence can be derived from FMs.We conducted several experiments on the Topology and Orchestration Specification for Cloud Applications(TOSCA)dataset and the Shape Completion and Animation of People(SCAPE)dataset.Experimental results show that the proposed BFM algorithm is effective and has superior performance than the state-of-the-art methods on both datasets.

延长蒸发器清洗周期的工程化改造

某煤化工零排放装置处理高盐废水的过程中,强制循环蒸发器频繁污堵,运行周期不足半个月。为解决该问题,本研究提出首先对进水水质进行优化,通过两级脱碳塔及两级吸附塔进行预处理,将进水碱度降到400 mg/L以下,COD降到300 mg/l以下。运行过程中蒸发器加装304不锈钢折流板式除沫器可有效去除3~5μm的雾滴,底部盐腿加装结晶器,形成大颗粒的结晶体,最后进入LLWZ450N卧式螺旋浓缩过滤离心机,出盐量达到每天45 t以上,有效的避免了蒸发器的污堵,保障了装置的长周期稳定运行。