Crossing the Border: From Keto- to Imine Reduction in Short-Chain Dehydrogenases/Reductases

The family of NAD(P)H-dependent short-chain dehydrogenases/reductases (SDRs) comprises numerous biocatalysts capable of C=O or C=C reduction. The highly homologous noroxomaritidine reductase (NR) from Narcissus sp. aff. pseudonarcissus and Zt_SDR from Zephyranthes treatiae, however, are SDRs with an extended imine substrate scope. Comparison with a similar SDR from Asparagus officinalis (Ao_SDR) exhibiting keto-reducing activity, yet negligible imine-reducing capability, and mining the Short-Chain Dehydrogenase/Reductase Engineering Database indicated that NR and Zt_SDR possess a unique active-site composition among SDRs. Adapting the active site of Ao_SDR accordingly improved its imine-reducing capability. By applying the same strategy, an unrelated SDR from Methylobacterium sp. 77 (M77_SDR) with distinct keto-reducing activity was engineered into a promiscuous enzyme with imine-reducing activity, thereby confirming that the ability to reduce imines can be rationally introduced into members of the “classical” SDR enzyme family. Thus, members of the SDR family could be a promising starting point for protein approaches to generate new imine-reducing enzymes.     

旋流分离-颗粒床耦合气固分离装备旋流场静压分布

针对一种集旋风分离器和内置颗粒床优势于一体的新型耦合气固分离装备在无灰负荷及固定床操作条件入口环形空间、分离空间和灰斗内静压场进行研究。结果表明，静压沿周向为非对称分布，轴向为非均匀分布，径向则呈中心低两侧高分布；且存在着静压分布的降压区(0?~180?，以入口处为0?)和增压区(180?~360?)；装备中心的负压及旋流作用在轴向高度H=6.41D(D为旋风壳体内径)以下对静压的影响不再显著；内置颗粒床外壁附近存在“滞留层”，有利于提高装备的分离性能。根据实验数据给出了静压周向分布和静压轴向分布的经验公式。     

A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling

The penalized calibration technique in survey sampling combines usual calibration and soft calibration by introducing a penalty term. Certain relevant estimates in survey sampling can be considered as penalized calibration estimates obtained as particular cases from an optimization problem with a common basic structure. In this framework, a case deletion diagnostic is proposed for a class of penalized calibration estimators including both design-based and model-based estimators. The diagnostic compares finite population parameter estimates and can be calculated from quantities related to the full data set. The resulting diagnostic is a function of the residual and leverage, as other diagnostics in regression models, and of the calibration weight, a singular feature in survey sampling. Moreover, a particular case, which includes the basic unit level model for small area estimation, is considered. Both a real and an artificial example are included to illustrate the diagnostic proposed. The results obtained clearly show that the proposed diagnostic depends on the calibration and soft-calibration variables, on the penalization term, as well as on the parameter to estimate.     

Two-step pyrolytic engineering to form porous nitrogen-rich carbons with a 3D network structure for Zn-air battery oxygen reduction electrocatalysis

It is of great urgency to design inexpensive and high-performance oxygen reduction reaction (ORR) electrocatalysts derived from biowastes as substitutes for Pt-based materials in electrochemical energy-conversion devices. Here we propose a strategy to synthesize three-dimensional (3D) porous nitrogen-doped network carbons to catalyze the ORR from two-step pyrolysis engineering of biowaste scale combined with the use of a ZnCl₂ activator and a FeCl₂ promotor. Electrochemical tests show that the synthesized network carbons have exhibited comparable ORR catalytic activity with a half-wave potential (~0.85 V vs. RHE) and outstanding cyclical stability in comparison to the Pt/C catalyst. Beyond that, a high electron transfer number (~3.8) and a low peroxide yield (<7.6%) can be obtained, indicating a four-electron reaction pathway. The maximum power density is ~68 mW cm^?2, but continuous discharge curves (at a constant potential of ~1.30 V) for 12 h are not obviously declined in Zn-air battery tests using synthesized network carbons as the cathodic catalyst. The formation of 3D porous structures with high BET surface area can effectively expose the surface catalytic sites and promote mass transportation to boost the ORR activity. This work may open a new idea to prepare porous carbon-based catalysts for some important reactions in new energy devices.     

A practical Equivalent Electrical Circuit model for Proton Exchange Membrane Fuel Cell (PEMFC) systems

An alternative Equivalent Electrical Circuit for Proton Exchange Membrane Fuel Cells is modelled in this study. Both I–V characteristics and H₂ consumptions corresponding to generated power under load and no-load conditions are investigated. For this purpose, H₂ consumptions and I–V characteristics of three different sized PEMFCs are tested. There is a very good harmony between the model results and measured values (relative error %0.7, %6.4 and %2.5 for FC-A, FC-B and FC-C respectively). In the proposed model current passes only on parallel resistance and not on serial resistance at no-load condition. Thus, a FC with higher parallel resistance should be preferred. Another key output of this study is that based on the proposed model, performance comparison of FCs can be performed with the parameters defined in this work. Proposals made in this study can easily be used for performance analysis of FCs under for both steady state and transient analysis.     

Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

煤矿下山巷道水与空气不耦合装药爆破技术对比研究

为了提高三级煤矿许用炸药能量利用率,改善爆破破岩效果，保证开采区的工作效率，对不耦合装药结构进行优化，以理论推导的方式分别得出空气不耦合与水不耦合装药系数对爆生气体准静压力的影响，并进行了对比分析；通过实验室爆破模型试验研究水和空气径向不耦合分别作用下爆炸应力波的传播分布特性，分析峰值应力与测点到炮孔比例距离、不耦合系数之间的关系，并与理论分析对比验证。结果表明：当不耦合系数相同时，炮孔处水不耦合装药爆炸应力波峰值高于空气不耦合装药，随着不耦合系数的增加，炮孔处爆炸应力波的峰值应力减小；模型试验测得同一测点的水不耦合装药峰值应力是空气不耦合装药峰值应力的1.15~1.52倍，峰值应力作用时间长于空气不耦合装药，同一测点水和空气不耦合装药结构测得的应力波及其峰值应力均随不耦合系数的增加呈负幂函数衰减，且空气不耦合装药时衰减得更快，与理论分析一致；贵州某煤矿下山巷道，于梯形掘进断面实施传统空气不耦合装药结构掏槽爆破，效果不甚理想，运用水不耦合装药爆破技术，提高了炮孔利用率，减小了岩石破碎块度，使爆堆集中，显著提高了岩石破碎效果与出渣效率。