Dhh1 is a member of the SESA network

The correct separation of chromosomes during mitosis is necessary to prevent genetic instability and aneuploidy, which are responsible for cancer and other diseases, and it depends on proper centrosome duplication. In a recent study, we found that Smy2 can suppress the essential role of Mps2 in the insertion of yeast centrosome into the nuclear membrane by interacting with Eap1, Scp160, and Asc1 and designated this network as SESA (S my2, E ap1, S cp160, A sc1). Detailed analysis showed that the SESA network is part of a mechanism which regulates translation of POM34 mRNA. Thus, SESA is a system that suppresses spindle pole body duplication defects by repressing the translation of POM34 mRNA. In this study, we performed a genome-wide screening in order to identify new members of the SESA network and confirmed Dhh1 as a putative member. Dhh1 is a cytoplasmic DEAD-box helicase known to regulate translation. Therefore, we hypothesized that Dhh1 is responsible for the highly selective inhibition of POM34 mRNA by SESA.     

Evaluation of expanded gamut software solutions for spot color reproduction

Expanded gamut printing is an approach in color reproduction that expands the color gamut of conventional CMYK printing processes via the use of additional colorants, such as Orange, Green, and Violet inks. This study evaluates the ability of commercial color management software to create an accurate solution for an expanded gamut printing system. In this study, two printing processes were used, an Epson SureColor P9000 inkjet printer/proofer and an HP Indigo 7900 digital production press, both with 7-color expanded gamut ink sets. Software solutions from Alwan, CGS ORIS, ColorLogic, GMG Color, Heidelberg, and Kodak were evaluated. The systems were tested to see how well they could reproduce the colors in the entire PANTONE+ Solid Coated spot color library. It is shown that the solutions are able to reproduce 89% to 94% of the spot colors on the Epson P9000 inkjet printer and 77% to 87% of the library on the Indigo 7900, both to less than two CIEDE2000 (a typical tolerance in label and packaging work). The number of color patches in expanded gamut characterization test charts was noted, as this is still an area of proprietary, nonstandardized working practice. There are many different colorant combinations that can make the same color in expanded gamut printing. The ink build created by the different software solutions was studied, as it relates to press stability through appropriate choice of colorants. Pantone and Adobe provide everyday commercial tools for expanded color workflows. The study identified some issues with products from these companies that could confuse a less-skilled user in a busy production environment. The conclusion of the study is that expanded gamut solutions for spot color printing produce totally acceptable results for digital printing processes; expanded gamut printing is ready, here and now. The findings show that expanded gamut printing can replace cumbersome conventional spot color workflows creating considerable savings and advantages, especially for label and packaging printers.     

A grounded theory examination of project managers' accountability

26 interviews were conducted with a snowball sample of project managers to explore how project managers were influenced by accountability arrangements and how they responded to accountability demands. Using a grounded theory approach to code the interview data, this study revealed that project managers develop new skills to respond to accountability demands. These effects are facilitated by the interaction of resource-based mechanisms and reflexivity that interact with the contextual factors of the project. The study broadens the understanding of accountability in project management and suggests a model for further empirical examination.     

视频侦查中人像智能分析应用及算法优化

人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

隐蔽老火区立体式综合治理研究

对2320隐蔽老火区首先通过灌注泥浆对火区进行治理,同时对部分裂隙通道进行堵漏,然后对泥浆不能到达的区域注入高倍数三相泡沫灭火材料泡沫,瞬间将火源处覆盖,火源因隔绝氧气而窒息灭火。三相泡沫具有良好的堆积性和流动性,对煤体具有保水保湿,惰化遗煤氧化空间,并能够对松散煤体进行化学阻化,从本质上降低遗煤自然氧化速率,消灭了隐蔽老火区的火灾隐患,具有较高的推广价值。     

Detection of correlation characteristics between financial time series based on multi-resolution analysis

Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China’s market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis.     

Mining fleet management systems: a review of models and algorithms

The objective of this paper is to review and document the mine fleet management systems’ models and algorithms. The purpose is to understand the algorithms behind the fleet management systems and the proposed academic solutions in this area to identify any gaps in the current literature and to open up opportunities to establish research questions that need to be addressed in an integrated simulation and optimisation operational planning research framework. In this paper, we review industrial fleet management systems and the main academic algorithms behind such systems. The fleet management systems are divided into three subsequently related problems to review: shortest path, production optimisation and real-time dispatching. Finally, the limitations of current algorithms for fleet management systems are documented in terms of mining practice feasibility and optimality of the solution on large-scale problems. The results of this literature review enable us to evaluate the logical links between major components of an integrated simulation and optimisation operational planning framework with current theory of fleet management systems.     

Sustainable supply chain management in Indian organisations: an empirical investigation

The present work is an attempt to investigate the adoption of sustainable supply chain management (SSCM) practices amongst manufacturing and process based organisations in India and its impact on organisational performance encompassing all three dimensions of sustainability. SSCM practices conceived in the present study include environmental management practices (EMP), socially inclusive practices for employees (SPE), socially inclusive practices for community (SPC), operations practices (OP) and supply chain integration (SCI) which were treated as exogenous variables. Organisational performance considered in this study includes five dimensions, namely environmental performance (EPR), employee-centred social performance (ESP), community-centred social performance (CSP), operations performance (OPR) and competitiveness, which were regarded as endogenous variables. The analysis was carried out with the help of structural equation modelling considering natural logarithm of manpower as a control variable. Few major findings are mentioned. EMP does not have any significant association with OPR, nor does it result in competitiveness. However, when jointly mediated through both EPR and OPR, EMP leads to competitiveness. SPC has significant negative association with competitiveness, when only direct relationship is considered. However, indirect relationship between SPC and competitiveness shows significant positive association when mediated through CSP. The resultant total effect between SPC and competitiveness turns out to be insignificant. Further, OPR fully mediates the relationship between OP and competitiveness. Managerial implications of the findings are discussed.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。