Structural Basis for The Recognition of Deaminated Nucleobases by An Archaeal DNA Polymerase

With increasing temperature, nucleobases in DNA become increasingly damaged by hydrolysis of exocyclic amines. The most prominent damage includes the conversion of cytosine to uracil and adenine to hypoxanthine. These damages are mutagenic and put the integrity of the genome at risk if not repaired appropriately. Several archaea live at elevated temperatures and thus, are exposed to a higher risk of deamination. Earlier studies have shown that DNA polymerases of archaea have the property of sensing deaminated nucleobases in the DNA template and thereby stalling the DNA synthesis during DNA replication providing another layer of DNA damage recognition and repair. However, the structural basis of uracil and hypoxanthine sensing by archaeal B-family DNA polymerases is sparse. Here we report on three new crystal structures of the archaeal B-family DNA polymerase from Thermococcus kodakarensis (KOD) DNA polymerase in complex with primer and template strands that have extended single stranded DNA template 5’-overhangs. These overhangs contain either the canonical nucleobases as well as uracil or hypoxanthine, respectively, and provide unprecedented structural insights into their recognition by archaeal B-family DNA polymerases.     

基于粗轧镰刀弯的精轧跑偏预控模型及应用

带钢热轧跑偏问题是影响带钢生产与板形质量的重要因素。轧制生产过程中,由于粗轧中间坯头部弯曲导致的精轧堆钢事故频发,不仅严重危害生产稳定性,还造成资源的严重浪费和企业的经济损失。为了解决上述问题,针对粗轧非对称板形影响因素,结合实测粗轧中间坯以及工艺过程数据,建立中间坯头部预控模型,并利用加权最小二乘法与模型自学习对模型增益系数进行优化,最终建立了基于粗轧镰刀弯的精轧跑偏预控模型。将模型计算值应用于现场生产后,有效降低了精轧带钢头部跑偏,具有较好的参考价值和指导意义。     

填隙Ti2Ni相形成条件的模式识别分析

在多维键参数空间中对填隙Ti_2Ni相化合物的形成条件做模式识别分析,由于前过渡金属原子组成的八面体空穴中填入C,N.O原子使Ti_2Ni结构稳定化,此结构的分布区扩大,邻近的Al_2Cu,MoSi_2结构分布区减小。     

Bayesian decision-based pattern recognition on spectrum signal of metal transfer modes

A software system of pattern recognition on spectrum signal of metal transfer mode has been developed using Visual Basic under Windows environment. On the basis of the coincidence relation between the spectrum signal and metal transfer mode, according to the geometrical pattern feature of the spectrum signal, several key characteristic parameters are extracted. The correspondent recognition function and a minimum distance classifier have been constructed based on Bayesian decision theory. The results show that using this system, the metal transfer mode of MIG, MAG, CO2 welding can be recognized automatically which provides the basis for automatically controlling of the metal gas arc welding metal transfer.     

基于电容层析成像和模糊模式识别的油气两相流流型辨识新方法的研究

基于电容层析成像和模糊模式识别技术别提出了一种油气两相流流型辨识的新方法。建立了12电极电容层析成像流型自动识别系统，该系统利用Tikhonov正则化原理并结合SIRT(Simultaneous Reconstruction Techniques)算法进行图像重建。Tikhonov正则化原理用于克服图像重建过程中的不适定问题，SIRT算法用于提高最终重建图像的质量。根据流型的随机和模糊特性，提出了一种根据管截面重建图像进行流型辨识的模糊流型判别方法。研究结果表明，提出的流型辨识新方法是有效的。对于层状流、核心流、环状流、均相流等流型，流型辨识的准确率高于95％，辨识一个流型所用的时间小于0.3秒。对于塞状流，流型辨识的准确率高于90％。     

The haustorium and the chemistry of host recognition in parasitic angiosperms

Two parasitic angiosperms,Agalinis purpurea (Scrophulariaceae) andStriga asiatica (Scrophulariaceae), are compared as to the chemical recognition events involved in host selection.Agalinis is a hemiparasite which can mature to seed-set without a host, whereasStriga is a holoparasite and survives for only a very limited time without a host. Both parasites, however, attach to a host through a specialized organ known as the haustorium and regulate the development of this organ through the recognition of chemical factors from host plants. We now describe the discovery of 2,6-dimethoxy-p-benzoquinone (2,6-DMBQ) as an haustoria-inducing principle fromSorghum root extracts. Our investigation of this compound has led us to suggest that one level of host recognition in these parasitic plants is mediated through their enzymatic digestion of the host root surface. Degradation of surface components liberates quinonoid compounds, such as 2,6-DMBQ, which in turn trigger haustorial development.     

Exploring album structure for face recognition in online social networks

In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.     

Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models

This paper proposes an efficient speech data selection technique that can identify those data that will be well recognized. Conventional confidence measure techniques can also identify well-recognized speech data. However, those techniques require a lot of computation time for speech recognition processing to estimate confidence scores. Speech data with low confidence should not go through the time-consuming recognition process since they will yield erroneous spoken documents that will eventually be rejected. The proposed technique can select the speech data that will be acceptable for speech recognition applications. It rapidly selects speech data with high prior confidence based on acoustic likelihood values and using only speech and monophone models. Experiments show that the proposed confidence estimation technique is over 50 times faster than the conventional posterior confidence measure while providing equivalent data selection performance for speech recognition and spoken document retrieval.