Effect of pre-treatment and hydraulic retention time on biohydrogen production from organic wastes

This study investigated the effect of pre-treatment and hydraulic retention time (HRT) on biohydrogen production from organic wastes. Various pre-treatments including thermal, base, acid, ultrasonication, and hydrogen peroxide were applied alone or in combination to enhance biohydrogen production from potato and bean wastewater in batch tests. All the pre-treated samples showed higher hydrogen production than the control tests. Hydrogen peroxide pre-treatment achieved the best results of 939.7 and 470 mL for potato and bean wastewater, respectively. Continuous biohydrogen production from sucrose, potato and bean wastewater was significantly influenced by reducing the HRT as 24, 18 and 12 h. Sucrose and potato showed similar behavior, where the hydrogen production rate (HPR) increased with decreasing the HRT. Optimum hydrogen yield results of 320 mL-H₂/g-VS (sucrose) and 150 mL-H₂/g-VS (potato) were achieved at HRT of 18 h. Bean wastewater showed optimum HPR of 0.65 L/L.d with hydrogen yield of 80 mL-H₂/g-VS at 24 h HRT.     

CNT/g‐C3N4 photocatalysts with enhanced hydrogen evolution ability for water splitting based on a noncovalent interaction

Graphite carbon nitride (g‐C₃N₄) as a novel photocatalyst has attracted growing attention, but its photocatalytic efficiency should be further improved. Based on the large work function and fast electron conductivity of carbon nanotubes (CNTs), here CNT/g‐C₃N₄ photocatalysts with improved H₂ evolution ability and stable water splitting ability were synthesized. The improvement was attributed to the synergistic effect between CNTs and g‐C₃N₄. As for the mechanisms, CNTs strongly attracted photoelectrons and, because of excellent conductibility, rapidly transferred photoelectrons from the catalyst interface. Thereby, the photoelectron migration rate and the photogenerated charge separation and the use efficiency of photoelectrons in g‐C₃N₄ were improved, which largely enhanced the hydrogen production ability. Moreover, the addition of CNTs improved the service life and stability of g‐C₃N₄‐based photocatalytic H₂ production. After 10 hours of visible light irradiation, the maximum H₂ yield from the 12‐mg/L CNT/g‐C₃N₄ (CG12) was 138.7 times larger than that of g‐C₃N₄ (6548.4 vs 47.2 μmol/g), and the H₂ evolution rate was 138.7 times that of g‐C₃N₄ (654.8 vs 4.72 μmol/g/h). After 50 hours, the apparent quantum efficiency of CG12 was up to 37.9%, indicating that the addition of CNTs improved the photocatalytic splitting and stability of g‐C₃N₄. The mechanism of photocatalytic hydrogen production and the roles of CNTs in improving water splitting were discussed through characterization and activity experiments. It was found that the addition of CNTs accelerated the migration, separation, and utilization of photoelectrons and thereby significantly enhanced the photocatalytic performance.     

Reliability of design approaches for axially loaded offshore piles and its consequences with respect to the North Sea

In the near future, several offshore wind farms are planned to be built in the North Sea. Therefore, jacket and tripod constructions with mainly axially loaded piles are suitable as support structures. The current design of axial bearing resistance of these piles leads to deviant results regarding the pile resistance when different design methods are adopted. Hence, a strong deviation regarding the required pile length must be addressed. The reliability of a design method can be evaluated based on a model error which describes the quality of the considered design method by comparing measured and predicted pile bearing resistances. However, only few pile load tests are reported with regard to the boundary conditions in the North Sea. This paper presents 6 large-scale axial pile load tests which were incorporated within a new model error approach for the current design methods used for the axial bearing resistance, namely API Main Text method and cone penetration test (CPT)-based design methods, such as simplified ICP-05, offshore UWA-05, Fugro-05 and NGI-05 methods. Based on these new model errors, a reliability-based study towards the safety was conducted by performing a Monte-Carlo simulation. In addition, consequences regarding the deterministic pile design in terms of quality factors were evaluated. It is shown that the current global safety factor (GSF) prescribed and the partial safety factors are only valid for the API Main Text and the offshore UWA-05 design methods; whereas for the simplified ICP-05, Fugro-05 and NGI-05 design methods, an increase in the required embedded pile length and thus in the GSF up to 2.69, 2.95 and 3.27, respectively, should be considered to satisfy the desired safety level according to DIN EN 1990 of β = 3.8. Further, quality factors for each design method on the basis of all reliability-based design results were derived. Hence, evaluation of each design method regarding the reliability of the pile capacity prediction is possible.     

融合约束学习的图像字幕生成方法

目的 图像字幕生成是一个涉及计算机视觉和自然语言处理的热门研究领域，其目的是生成可以准确表达图片内容的句子。在已经提出的方法中，生成的句子存在描述不准确、缺乏连贯性的问题。为此，提出一种基于编码器-解码器框架和生成式对抗网络的融合训练新方法。通过对生成字幕整体和局部分别进行优化，提高生成句子的准确性和连贯性。方法 使用卷积神经网络作为编码器提取图像特征，并将得到的特征和图像对应的真实描述共同作为解码器的输入。使用长短时记忆网络作为解码器进行图像字幕生成。在字幕生成的每个时刻，分别使用真实描述和前一时刻生成的字幕作为下一时刻的输入，同时生成两组字幕。计算使用真实描述生成的字幕和真实描述本身之间的相似性，以及使用前一时刻的输出生成的字幕通过判别器得到的分数。将二者组合成一个新的融合优化函数指导生成器的训练。结果 在CUB-200数据集上，与未使用约束器的方法相比，本文方法在BLEU-4、BLEU-3、BLEI-2、BLEU-1、ROUGE-L和METEOR等6个评价指标上的得分分别提升了0.8%、1.2%、1.6%、0.9%、1.8%和1.0%。在Oxford-102数据集上，与未使用约束器的方法相比，本文方法在CIDEr、BLEU-4、BLEU-3、BLEU-2、BLEU-1、ROUGE-L和METEOR等7个评价指标上的得分分别提升了3.8%、1.5%、1.7%、1.4%、1.5%、0.5%和0.1%。在MSCOCO数据集上，本文方法在BLEU-2和BLEU-3两项评价指标上取得了最优值，分别为50.4%和36.8%。结论 本文方法将图像字幕中单词前后的使用关系纳入考虑范围，并使用约束器对字幕局部信息进行优化，有效解决了之前方法生成的字幕准确度和连贯度不高的问题，可以很好地用于图像理解和图像字幕生成。     

金属氧化物半导体场效应晶体管中总剂量效应导致的阈值电压漂移研究现状

为了研发可用于核与辐射应急响应与准备的机器人,对比了多种具有不同结构和生产工艺的金属氧化物半导体场效应晶体管(MOSFET)由于总剂量效应(TID)导致的阈值电压漂移(ΔV_th)。注意到了栅宽和栅长对器件耐辐射能力的影响在体CMOS器件和纳米线(NW)MOSFET器件之间、高的和低的工艺节点之间的不同,并从辐射诱导的窄通道效应(RINCE)和辐射诱导的短通道效应(RISCE)两方面解释了这种区别的原因。发现近年来前沿的一些研究在考虑辐射效应时,修正了负偏压不稳定性(NBTI)的影响。并讨论了几种新型器件包括锗沟道、氮化镓沟道管和具有特殊几何布局的晶体管。此外,介绍了计算机辅助设计技术(TCAD)在几种新型场效应管的机理研究和建模验证中的应用。     

A novel strategy for quantitative analysis of soil pH via laser-induced breakdown spectroscopy coupled with random forest

pH is one of the significant properties of soil,and is closely related to the decomposition of soil organic matter,anion-cation balance,growth of plants and many other soil processes.In the present work,laser-induced breakdown spectroscopy(LIBS) technique coupled with random forest(RF) was proposed to quantify the pH of soil.First,LIBS spectra of soil was collected,and some common elements in soil were identified based on the National Institute of Science and Technology database.Then,in order to obtain a better predictive result,the influence of different input variables(full spectrum,different spectral ranges,the intensity of characteristic bands and characteristic lines) on the predictive performance of RF calibration model was explored with the evaluation indicators of root mean square error(RMSE) and coefficient of determination(R2),the characteristic bands of four elements(AI,Ca,Mg and Si) were determined as the optimal input variables.Finally,the predictive performance of RF calibration model was compared with partial least squares calibration model with the optimal input variables and model parameters,and RF calibration model showed a better predictive performance,and the four evaluation indicators of R_p~2,RMSEP,mean absolute error and mean relative error were 0.9687,0.1285,0.1114 and 0.0136,respectively.It indicates that LIBS technique coupled with RF algorithm is an effective method for pH determination of soil.     

氨基羟基脲还原反萃高浓度Pu(Ⅳ)

采用氨基羟基脲（HSC）的硝酸水溶液研究了从30%（体积分数，下同）TBP/煤油中还原反萃高浓度四价钚（Pu（Ⅳ））的性能，并与羟胺-肼（HAN-HN）、N,N-二甲基羟胺-单甲基肼（DMHAN-MMH）在钚净化浓缩循环中反萃行为进行了对比。结果表明：在一定HSC浓度下，适当延长相接触时间、减小相比（o/a）、降低酸度和提高温度，均有利于Pu（Ⅳ）的还原反萃。HSC作为还原反萃剂，可以有效实现30%TBP/煤油中高浓钚的反萃，反萃效果较其它几种还原剂更好，有望在先进二循环流程的钚净化浓缩工艺中得到应用。     

基于EEMD能量熵和混合算法的电机轴承故障诊断

针对提升机电机轴承振动信号的非平稳特性和单一粒子群算法(PSO) 优化径向基函数（RBF）神经网络时存在网络收敛速度慢和适应度值易陷入局部最小的缺点，提出基于集合经验模态分解（EEMD）能量熵和模拟退火粒子群混合算法（SAPSO）优化RBF神经网络的提升机电机轴承故障诊断方法。基于EEMD求取振动信号各固有模态函数分量的能量熵，并使用相关性分析方法剔除虚假的分量，把筛选后的有效数据作为故障识别的特征向量；利用模拟退火（SA）算法具有局部概率突跳的特性，将SA算法和PSO算法相结合，在优化RBF诊断模型隐含层参数时以实现不同算法间的优劣互补。仿真结果表明，使用SAPSO算法优化后的RBF神经网络模型在提升机电机轴承故障诊断中能够加快网络收敛速度和提升故障识别精度。     

Enriching Context Information for Entity Linking with Web Data

Journal of Computer Science and Technology - Entity linking (EL) is the task of determining the identity of textual entity mentions given a predefined knowledge base (KB). Plenty of existing...     

Machine learning assisted OSP approach for improved QoS performance on 3D charge-trap based SSDs

Three-dimensional (3D) charge-trap based solid-state-drivers (SSDs) have become an emerging storage solution in recent years. One-shot-programming in 3D charge-trap based SSDs could deliver a maximized system input/output (I/O) throughput at the cost of degraded Quality-of-Service (QoS) performance. This paper proposes reinforcement-learning based one-shot-programming (RLOSP), a reinforcement learning based approach to improve the QoS performance for 3D charge-trap based SSDs. By learning the I/O patterns of the workload environments as well as the device internal status, the proposed approach could properly choose requests in the device queue, and allocate physical addresses for these requests during one-shot-programming. In this manner, the storage device could deliver an improved QoS performance. Experimental results reveal that the proposed approach could reduce the worst-case latency at the 99.9th percentile by 37.5%–59.2%, with an optimal system I/O throughput.