Simulation of aerated lagoon using artificial neural networks and multivariate regression techniques

The aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.     

How can the Cross-Link Adducts Formed by Novel Trans Platinum Drug be Influenced by Hydrogen Bond

A systematic quantum chemical characterization of intrinsic structure, energies and spectral properties of all the studied cross-link adducts formed by the novel trans platinum with thiazole ligand has been carried out at B3LYP/6-31G^＊ level of theory with the Lanl2dz pseudo potential basis set for the Pt atom. Special attention has been paid to the relative stability of these complexes and the factors that probably alter the order of the relative stability. The important influence of hydrogen bond on the structures, the energies and the spectral property was revealed. Other factors that contribute to relative stability including solvation effect, entropy and electronic delocalization energy were taken into account. The stability energy of the whole complex, and the interaction energy between two purine bases and the [Pt-（NH3）thiazole]^2＋ group were adopted to study the interplay among subsystems and their contribution to relative stability of all the studied cross-link model. Finally, basic spectral properties of these complexes including H（8） chemical shifts of all the studied complexes and the VCD （vibrational circular dichroism） spectra of two pairs of GG chelate enantiomers, were provided in order to define the structure of the most possible duplex bearing novel trans platinum drug lesions.     

融合课程思政的“自动化综合实验”教学探索

为将思政教育融入课程教学中,培养德能兼备的自动化专业优秀人才。在《自动化综合实验》课程中,首先明确提出了教学的专业目标和思政目标,然后将教学环节分为课程介绍、选题汇报、学生实践以及项目展示和答辩环节,挖掘出丰富的思政元素并融入到课程教学的每个环节,并选取典型案例,通过思维导图法剖析了课程思政的融入策略,最后介绍了课程思政考核模式和取得的初步成效。该课程思政教学模式可以为“专业实验课程-思政教育体系”的打造提供参考。     

Entanglement complexity of lattice ribbons

We consider a discrete ribbon model for double-stranded polymers where the ribbon is constrained to lie in a three-dimensional lattice. The ribbon can be open or closed, and closed ribbons can be orientable or nonorientable. We prove some results about the asymptotic behavior of the numbers of ribbons withn plaquettes, and a theorem about the frequency of occurrence of certain patterns in these ribbons. We use this to derive results about the frequency of knots in closed ribbons, the linking of the boundary curves of orientable closed ribbons, and the twist and writhe of ribbons. We show that the centerline and boundary of a closed ribbon are both almost surely knotted in the infinite-n limit. For an orientable ribbon, the expectation of the absolute value of the linking number of the two boundary curves increases at least as fast as n, and similar results hold for the twist and writhe.     

大数据时代下数字生活社区的前景

随着信息化大数据时代的到来,既给信息科技从业者带来新的机遇和挑战的同时,也给大众百姓的生活带来巨大的品质提升,数字生活社区将引导一场前所未有的技术革命,对影响人们衣、食、住、行、医等方方面面,也使得人们对科技生活的依赖性更加增强,更加的理所当然.     

Study on AdaBoost-based link quality prediction mechanism

The link quality was vulnerable to the complexity environment in wireless sensor network.Obtaining link quality information in advance could reduce energy consumption of nodes.After analyzing the existing link quality prediction methods,AdaBoost-based link quality prediction mechanism was put forward.Link quality samples in deferent scenarios were collected.Density-based unsupervised clustering algorithm was employed to classify training samples into deferent link quality levels.The AdaBoost with SVM-based component classifiers was adopted to build link quality prediction mechanism.Experimental results show that the proposed mechanism has better prediction precision.     

Improving energy efficiency using a link adaptation algorithm dedicated for 100 Gbps wireless communication

This paper presents a link adaptation algorithm dedicated for 100 Gbps wireless transmission. Interleaved Reed-Solomon codes are selected as forward error correction (FEC) algorithms. The redundancy of the codes is selected according to the channel bit error rate (BER). The uncomplicated FEC scheme allows implementing a complete data link layer processor in an FPGA (field programmable gate array). In our case, we use the Virtex7 FPGA to validate the functionality of our implementation. The proposed FPGA-processor achieves 169 Gbps throughput. Moreover, the implementation is synthesized into 40 nm CMOS technology and the described link adaptation algorithm allows reducing consumed energy per bit to values below 1 pJ/bit at BER <1e−4. With higher BER, the energy increases up to ∼13 pJ/bit.     

在线教学的实践与反思*——以有机化学课程为例

以有机化学课程在线教学开展情况为背景,通过与传统教学模式对比,分析了在线教学的优势与不足。在此基础上,将笔者所在课程组开展在线教学以来在教学内容重构、教学环节设计、考核方式改革等方面的探索与尝试进行了总结与分享。     

Value drivers of blockchain technology: A case study of blockchain-enabled online community

There is growing recognition that blockchain technology has significant potential to alter how organizations and people work and communicate. However, theoretical guidance concerning how organizations leverage blockchain technology to enhance value creation for users is still limited. Grounded in the socio-technical perspective and leveraging the rich data obtained from case analyses of blockchain-enabled online communities, this paper develops a theoretical model to identify the core value drivers that blockchain enables for online communities. The core value drivers include: a reputation-value system, data ownership mechanisms, and verification & tracking mechanisms. Our findings suggest that these three value drivers enhance value creation of online communities by motivating participation and protecting contributions.     

Families,experiments, and nature: Learning science through project-based learning

This study brings together the research focused on science education through project-based learning (PBL). This learning project was carried out in a rural learning community and an attempt was made to adapt to the natural resources of the area by organizing educational outings, experimental activities, and encouraging the participation of families. The overall objective is to test the effectiveness of applying the PBL teaching methodology for learning science in a rural learning community. The methodology used has been qualitative, specifically, the participating research has been used and the information has been compiled in a field notebook. The results show that the didactic proposal had good results; showing that, in conclusion, science teaching today should be inclined toward more innovative educational methodologies such as PBL.