mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Gas phase ethylene polymerization over SiO_2-supported organosilyl chromate UCC S-2 catalyst using a high-speed stirred-autoclave reactor

Although an important industrial catalyst for producing high density polyethylene,the SiO_2-supported organosilyl chromate UCC S-2 catalyst has not been fully investigated compared with the SiO_2-supported oxo chromium Phillips catalyst.In this work,gas phase ethylene polymerization by S-2 catalysts (Cat-1,Cat-2,and Cat-3)was carried out in a high-speed stirredautoclave reactor.The effects of temperature,time,and pressure on kinetics,activity,and product properties were studied.All kinetics were typical built-up types with slow decay.Compared to the simple physical mixtures of Cat-1 and Cat-2,Cat-3 showed higher activity and its product had a broader molecular weight distribution,indicating new active species induced during blending of Cat-1 and Cat-2 in n-hexane.The innovation by a simple catalyst technology created a new application to meet market demands.
Morphological and mechanical characterization of a PMMA/CdS nanocomposite

Thick film of poly(methyl methacrylate)(PMMA)/CdS nanocomposite have been synthesized by the solution casting process.The nanostructure of the CdS particles has been ascertained through the small angle X-ray scattering (SAXS)technique.The surface morphological characterization of the PMMA/CdS nanocomposite has been done through scanning electron microscopy(SEM)analysis.The variation of mechanical loss factor(TanG)with temperature and tensile properties of prepared samples have been studied using Dynamic Mechanical Analyzer (DMA).This study reveals that the glass transition temperature (Tg),Young's modulus,and fracture energy of the PMMA/CdS nanocomposite are greatly influenced by the existence of interfacial energetic interaction between dispersed CdS nanoparticles and the matrix of PMMA.
Preparation of starch esters with crosslinking structures derived from dianhydride

Starch is a kind of natural polymer used in many industrial fields because of its low cost,availability and biodegradation.Potato starch was modified by esterification with pyromellitic dianhydride,and the products were obtained with crosslinking structures.Orthogonal experiments showed that reactive temperature was the primary influencing factor.The product prepared at 40℃ for 3 h with the mass ratio of starch and dianhydride of 16:1 and pH value of 7.5 exhibited a degree of substitution of 11%.FTIR and UV analysis verified the formation of starch esters.
Invading target cells:multifunctional polymer conjugates as therapeutic nucleic acid carriers

Polymer-based conjugates are an interesting option and challenge for the design of nano-sized drugdelivery systems,as they require advanced conjugation chemistry and precise engineering.In the case of nucleic acid therapy,non-viral carriers face several biological barriers during the delivery process,namely 1)protection of the cargo from extracellular degradation,2)avoidance of non-specific interactions with non-targeted tissues,3)efficient entry into the target cells,4)intracellular trafficking to the site of action and 5)cargo release.To take on these obstacles,multifunctional conjugates can act as "smart polymers" with microenvironment-sensing dynamics to facilitate the separate delivery steps.Synthesis of defined polymer architectures with precise functionalization enables structure-activity relationships to be investigated and the integration of key functions for efficient delivery.Thus bioresponsive polymer conjugates,which are equipped with molecular devices responding to the certain microenvironments within the delivery pathway (e.g.pH,redox potential,enzymes)can be assembled.This review focuses on the modular engineering and conjugation of multifunctional polymeric structures for the utilization as "tailor-made" nucleic acid carriers.
Membrane-bound O-acyltransferases (MBOATs)

The MBOAT enzyme family,identified in 2000,comprises 11 genes in the human genome that participate in a variety of biological processes.MBOAT enzymes contain multiple transmembrane domains and share two active site residues,histidine and asparagine.Several MBOAT members are drug targets for major human diseases,including atherosclerosis,obesity,Alzheimer disease,and viral infections.Here we review the historical aspects of MBOAT enzymes,classify them biochemically into 3 subgroups,and describe the essential features of each member.
中心地等级体系的演化模型

作为地理学两大理论基石之一的中心地学说,因其无法提供确定的时空参数条件,及其在演化过程模式上的缺失,致使其他空间结构模型无法与之对接,也导致完整的区域空间结构理论体系构建上的困难,本文深入解析了不同等级中心地产生与演化的过程机理,构建了中心地等级体系的演化模型,推导分析和模拟结果显示中心地等级体系的产生与演化可分为萌芽期、成形期、完善期、成熟期和提升期5个阶段,受空间区位和中心性影响,中心地规模结构和功能结构存在显著不同,不仅同一级中心地规模可以存在很大的差异,甚至低等级中心地规模可以超过高一级中心地,而位于中央位置的中心地最终可形成中心地集聚区,研究表明基于均质平原假设条件,不仅可以形成均衡性的中心地功能结构,同时还可衍生出不均衡的中心地规模结构,从而完成了从纯理论的空间均衡模式的推导向不均衡的现实模式的解释和论证的转变。
Possible distance indicators in gamma-ray pulsars

Distance measurement of gamma-ray pulsars is a current challenge in pulsar studies.The Large Area Telescope(LAT)aboard the Fermi gamma-ray observatory discovered more than 70 gamma-ray pulsars including 24 new gamma-selected pulsars with almost no distance information.We study the relation between gammaray emission efficiency(η=Lγ/E˙)and pulsar parameters for young radio-selected gamma-ray pulsars with known distance information in the first gamma-ray pulsar catalog reported by Fermi/LAT.We have introduced three generation-order parameters to describe the gamma-ray emission properties of pulsars,and find a strong correlation of η-ζ3,a generation-order parameter which reflectsγ-ray photon generation in the pair cascade processes induced by magnetic field absorption in a pulsar’s magnetosphere.A good correlation of η-BLC,the magnetic field at the light cylinder radius,is also found.These correlations are the distance indicators in gamma-ray pulsars used to evaluate distances for gamma-selected pulsars.Distances of 25 gamma-selected pulsars are estimated,which could be tested by other distance measurement methods.The physical origin of the correlations may also be interesting for pulsar studies.
东亚热带与副热带季风区对流降水和层云降水季节变化特征对比分析研究

利用10年TRMM卫星2A25资料,对东亚热带和副热带季风区对流降水和层云降水的季节变化特征进行了对比分析,研究了热带和副热带季风区降水性质的差异,并结合IPCC第4次报告中24个模式的20c3m模拟资料,对现有模式在东亚热带和副热带季风区关于对流降水及层云降水的模拟能力做了一个简单的评估,分析了模式中可能存在的问题,结果表明:夏季风爆发后,东亚热带与副热带季风区对流降水和层云降水都明显增加,但热带季风区对流降水所占比重明显减少,而副热带季风区对流降水所占比重明显增加,热带和副热带季风区存在明显不同；现有模式对东亚季风区对流降水百分比的模拟普遍偏高,而对层云降水的模拟偏少,这在热带季风区尤其明显；模式较好地模拟出了副热带季风区中对流降水百分比的季节变化特征,而对热带季风区对流降水百分比的季节变化没有正确描述；研究结果表明对流降水和层云降水在时间和空间上经常同时出现,具有很强的伴随性,而模式没有正确描述这种相关性,这可能是模式对层云降水百分比模拟不好的一个重要原因.
12CO,13CO and C18O observations along the major axes of nearby bright infrared galaxies

We present simultaneous observations of 12CO,13CO and C18O J=1-0 emission in 11 nearby(cz<1000 km s-1)bright infrared galaxies.Both 12CO and 13CO are detected in the centers of all the galaxies,except for 13CO in NGC 3031.We have also detected C18O,CSJ=2-1 and HCO+J=1-0 emission in the nuclear regions of M82 and M51.These are the first systematical extragalactic detections of 12CO and its isotopes from the PMO 14 m telescope.We have conducted halfbeam-spaced mapping of M82 over an area of 4×2.5 and major axis mapping of NGC 3627,NGC 3628,NGC 4631 and M51.The radial distributions of 12CO and 13CO in NGC 3627,NGC 3628 and M51 can be well fitted by an exponential profile.The 12CO/13CO intensity ratio,R,decreases monotonically with the galactocentric radius in all mapped sources.The average R in the center and disk of the galaxies are 9.9±3.0 and 5.6±1.9,respectively,much lower than the peculiar R(～24)found in the center of M82.The intensity ratios of 13CO/C18O,13CO/HCO+and 13CO/CS(either our or literature data)show little variation with galactocentric radius,in sharp contrast with the greatly varied R.This supports the notion that the observed gradient in R could be the result of the variations of the physical conditions across the disks.The H2 column density derived from C18O shows that the Galactic standard conversion factor(X-factor)overestimates the amount of the molecular gas in M82 by a factor of～2.5.These observations suggest that the X-factor in active star-forming regions(i.e.,nuclear regions)should be lower than that in normal star-forming disks and the gradient in R can be used to trace the variations of the X-factor.
华南早古生代花岗岩的地球化学、年代学及其成因研究——以赣中南为例

在大量野外地质调查和前人资料分析的基础上,选择赣中南四个有代表性的早古生代花岗质岩进行了重点解剖,内容包括岩相学特征、锆石U-Pb定年、原位Hf同位素成分测试、岩石地球化学特征等．野外观察表明,岩体和围岩成分呈渐变关系,两者的片理产状基本一致,岩体边缘可见不规则状砂质板岩残留体,残留体中的片理产状也与岩体和围岩的相近,具有原地花岗岩化的成因特征．显微镜下观测显示,岩体中石英含量高,含有白云母、矽线石等富铝矿物,应属S型花岗岩类；长石和石英矿物被强烈压扁拉长,呈线状定向排列,反映岩体曾经受到过强烈的挤压剪切作用．四个花岗岩体的主量元素成分显示,A/CNK值在1.03～1.37之间(13组平均值为1.16),属于强过铝质花岗岩；硅．碱图解表明,它们都属于偏碱性花岗岩,源岩主要由砂屑质岩石组成．四个岩体均富集Rb,Th和U,亏损Ba,Sr,Nb和Ti,属于低Ba-Sr花岗岩范畴,它们的微量元素蛛网曲线接近重合,反映同源成因特征．其稀土总量较高,轻稀土富集,铕负异常明显,具有陆壳物质部分熔融的特征,锆石U-Pb定年结果表明,赣中南四个花岗岩体的结晶年龄基本一致:(436.1±5.7)Ma(贵溪塘湾,N=22),(440.6±4)Ma(宜黄界口,N=32),(435.9±6.2)Ma(黎川,N=21),(441.9±3.1)Ma(金溪,N=27),相当于志留纪兰多维列世,另有少量捕获锆石,测年值 700 Ma左右,推测是其基底岩石记录到的华南古陆块裂解信息．锆石TH/U比值大,在0.52～1.54之间,平均值为1.08,具有岩浆结晶锆石的特征．锆石原位Hf同位素成分数据表明,赣中南志留纪花岗岩的εHf(t)值呈现明显负值,表明研究区花岗岩浆基本上来自地壳的部分熔融,没有受到幔源岩浆成分的影响．诸多证据表明,赣中南在早古生代曾经发生过陆块聚合作用．强烈的挤压使地壳缩短变厚,因地温增高以及高产热元素在加厚带的浓聚,遂使地壳逐渐软化并部分熔融,形成铝过饱和花岗岩浆；然后,在后造山伸展一减压背景下上升侵位,形成花岗岩体。
Flexible solar cells based on PCBM/P3HT heterojunction

[6,6]-phenyl-C61-butyric acid methyl ester(PCBM)/ poly (3-hexylthiophene)(P3HT)heterojunction has not only the absorption in ultraviolet light for PCBM,but also the absorption in visible light for P3HT,which widens the incident light harvest range,improving the photoelectrical response of hybrid solar cell effectively.Using conducting polymers blend heterojunction consisting of C60 derivatives PCBM and P3HT as charge carrier transferring medium to replace I3 /I- redox electrolyte and dye,a novel flexible solar cell was fabricated in this study.The influence of PCBM/P3HT mass ratio on the photovoltaic performance of the solar cell was also studied.Under a simulated solar irradiation of 100 mW cm2,the flexible solar cell achieved a light-to-electric energy conversion efficiency of 1.04%,an open circuit voltage of 0.86 V,short circuit current density of 2.6 mA cm-2 and fill factor (FF)of 0.46.
The structure of the spherical tensor forces in the USD and GXPF1A shell model Hamiltonians

The realistic shell model Hamiltonians,USD and GXPF1A,have been transformed from the particle-particle (normal)representation to the particle-hole representation (multipole-multipole)by using the known formulation in Ref.[1].The obtained multipole-multipole terms were compared with the known spherical tensor forces,including the coupled ones.It is the first time the contributions of the coupled tensor forces to the shell model Hamiltonian have been investigated.It has been shown that some coupled-tensor forces,such as [r2Y2? π2]1,also give important contributions to the shell model Hamiltonian.
Radiative decays J/ψ → η(')y in perturbative QCD

With the recent investigations of the g*g*-η(')transition form factor and η-η' mixing scheme,we present an updated study of the radiative decays J/ψ → η(')y in perturbative QCD.The decays are taken as a test ground for the g*g*-η(')transition form factors and the η-η' mixing scheme.The form factors are found to be working for glunic η' production and the mixing angle is constrained to be =35.1°±0.8°.
Multi-scale evaluation of river health in Liao River Basin,China

Previous studies on river health evaluation mainly focused on characterizations at a river-corridor scale and ignored the complex interactions between the river ecosystem and other components of the river basin.Based on the consideration of the interactions among rivers,associated river basin and habitats,an assessment framework with multi-scale indicators was developed.An index system divided among these three scales to characterize the health of river ecosystems in China's Liao River Basin was established.Set pair analysis was applied to integrate the multi-scale indicators and determine the health classes.The evaluation results indicated that the rivers in the western and eastern zones of the Liao River were classified as sick,and rivers in the main stream of the Liao and Huntai rivers were classified as unhealthy.An excessive level of disturbances,such as large pollution loads and dense construction of water conservation projects within the river basin,were the main causes of the river health deterioration.
Influence of influent on anaerobic ammonium oxidation in an Expanded Granular Sludge Bed-Biological Aerated Filter integrated system

Shortcut nitrification-denitrification,anaerobic ammonium oxidation (ANAMMOX),and methanogenesis have been successfully coupled in an Expanded Granular Sludge Bed-Biological Aerated Filter (EGSB-BAF)integrated system.As fed different synthetic wastewater with chemical oxygen demand (COD)of 300-1200 mg L- and NH_4~+-N of 30-120mg·L~(-1)at the outer recycle ratio of 200%,the influence of influent on ANAMMOX in the integrated system was investigated in this paper.The experimental results showed that higher COD concentration caused an increase in denitrification and methanogenesis but a decrease in ANAMMOX; however,when an influent with the low concentration of COD was used,the opposite changes could be observed.Higher influent NH4 -N concentration favored ANAMMOX when the COD concentration of influent was fixed.Therefore,low COD/NH_4~+-N ratio would decrease competition for nitrite between ANAMMOX and denitrification,which was favorable for reducing the negative effect of organic COD on ANAMMOX.The good performance of the integrated system indicated that the bacterial community of denitrification,ANAMMOX,and methanogenesis could be dynamically maintained in the sludge of EGSB reactor for a certain range of influent.
A best-effort approach to an infrastructure for Chinese Web related research

The design of the infrastructure for Chinese Web (CWI),a prototype system aimed at forum data analysis,is introduced.CWI takes a best effort approach.1)It tries its best to extract or annotate semantics over the web data.2)It provides flexible schemes for users to transform the web data into eXtensible Markup Language (XML)forms with more semantic annotations that are more friendly for further analytical tasks.3)A distributed graph repository,called DISGR is used as backend for management of web data.The paper introduces the design issues,reports the progress of the implementation,and discusses the research issues that are under study.
3D face recognition based on principal axes registration and fusing features

A 3D face recognition approach which uses principal axes registration (PAR)and three face representation features from the re-sampling depth image:Eigenfaces,Fisherfaces and Zernike moments is presented.The approach addresses the issue of 3D face registration instantly achieved by PAR.Because each facial feature has its own advantages,limitations and scope of use,different features will complement each other.Thus the fusing features can learn more expressive characterizations than a single feature.The support vector machine (SVM)is applied for classification.In this method,based on the complementarity between different features,weighted decision-level fusion makes the recognition system have certain fault tolerance.Experimental results show that the proposed approach achieves superior performance with the rank-1 recognition rate of 98.36% for GavabDB database.
Finger-knuckle-print recognition using Gabor feature and MMDA

Recently,a new biometrics recognition,finger-knuckle-print,has attracted the interest of researchers.The popular techniques used in face recognition are not applied in finger-knuckle-print recognition.Inspired by the success of Gabor in face recognition,we propose a method that uses Gabor feature and a multi-manifold discriminant analysis (MMDA)method to identify finger-knuckle-print.The experimental results show that our proposed method can work well.
Discriminative training of GMM-HMM acoustic model by RPCL learning

This paper presents a new discriminative approach for training Gaussian mixture models (GMMs)of hidden Markov models (HMMs)based acoustic model in a large vocabulary continuous speech recognition(LVCSR)system.This approach is featured by embedding a rival penalized competitive learning (RPCL)mechanism on the level of hidden Markov states.For every input,the correct identity state,called winner and obtained by the Viterbi force alignment,is enhanced to describe this input while its most competitive rival is penalized by de-learning,which makes GMMs-based states become more discriminative.Without the extensive computing burden required by typical discriminative learning methods for one-pass recognition of the training set,the new approach saves computing costs considerably.Experiments show that the proposed method has a good convergence with better performances than the classical maximum likelihood estimation (MLE)based method.Comparing with two conventional discriminative methods,the proposed method demonstrates improved generalization ability,especially when the test set is not well matched with the training set.
Radar HRRP statistical recognition with temporal factor analysis by automatic Bayesian Ying-Yang harmony learning

Radar high-resolution range profiles(HRRPs)are typical high-dimensional and interdimension dependently distributed data,the statistical modeling of which is a challenging task for HRRP-based target recognition.Supposing that HRRP samples are independent and jointly Gaussian distributed,a recent work [Du L,Liu H W,Bao Z.IEEE Transactions on Signal Processing,2008,56(5):1931-1944] applied factor analysis (FA)to model HRRP data with a two-phase approach for model selection,which achieved satisfactory recognition performance.The theoretical analysis and experimental results reveal that there exists high temporal correlation among adjacent HRRPs.This paper is thus motivated to model the spatial and temporal structure of HRRP data simultaneously by employing temporal factor analysis (TFA)model.For a limited size of high-dimensional HRRP data,the two-phase approach for parameter learning and model selection suffers from intensive computation burden and deteriorated evaluation.To tackle these problems,this work adopts the Bayesian Ying-Yang (BYY)harmony learning that has automatic model selection ability during parameter learning.Experimental results show stepwise improved recognition and rejection performances from the twophase learning based FA,to the two-phase learning based TFA and to the BYY harmony learning based TFA with automatic model selection.In addition,adding many extra free parameters to the classic FA model and thus becoming even worse in identifiability,the model of a general linear dynamical system is even inferior to the classic FA model.
Thresholding-based detection of fine and sparse details

Fine and sparse details appear in many quality inspection applications requiring machine vision.Especially on flat surfaces,such as paper or board,the details can be made detectable by oblique illumination.In this study,a general definition of such details is given by defining sufficient statistical properties from histograms.The statistical model allows simulation of data and comparison of methods designed for detail detection.Based on the definition,utilization of the existing thresholding methods is shown to be well motivated.The comparison shows that minimum error thresholding outperforms the other standard methods.Finally,the results are successfully applied to a paper printability inspection application,and the IGT picking assessment,in which small surface defects must be detected.The provided method and measurement system prototype provide automated assessment with results comparable to manual expert evaluations in this laborious task.
An investigation of several typical model selection criteria for detecting the number of signals

Based on the problem of detecting the number of signals,this paper provides a systematic empirical investigation on model selection performances of several classical criteria and recently developed methods (including Akaike's information criterion (AIC),Schwarz's Bayesian information criterion,Bozdogan's consistent AIC,Hannan-Quinn information criterion,Minka's (MK)principal component analysis (PCA)criterion,Kritchman & Nadler's hypothesis tests (KN),Perry & Wolfe's minimax rank estimation thresholding algorithm (MM),and Bayesian Ying-Yang (BYY)harmony learning),by varying signal-to-noise ratio (SNR)and training sample size N.A family of model selection indifference curves is defined by the contour lines of model selection accuracies,such that we can examine the joint effect of N and SNR rather than merely the effect of either of SNR and N with the other fixed as usually done in the literature.The indifference curves visually reveal that all methods demonstrate relative advantages obviously within a region of moderate N and SNR.Moreover,the importance of studying this region is also confirmed by an alternative reference criterion by maximizing the testing likelihood.It has been shown via extensive simulations that AIC and BYY harmony learning,as well as MK,KN,and MM,are relatively more robust than the others against decreasing N and SNR,and BYY is superior for a small sample size.
Data-based intelligent modeling and control for nonlinear systems

With the ever increasing complexity of industrial systems,model-based control has encountered difficulties and is facing problems,while the interest in data-based control has been booming.This paper gives an overview of data-based control,which divides it into two subfields,intelligent modeling and direct controller design.In the two subfields,some important methods concerning data-based control are intensively investigated.Within the framework of data-based modeling,main modeling technologies and control strategies are discussed,and then fundamental concepts and various algorithms are presented for the design of a data-based controller.Finally,some remaining challenges are suggested.
Optimal locality preserving least square support vector machine

In this paper,a novel least square support vector machine (LSSVM),termed as optimal locality preserving LSSVM (OLP-LSSVM)is proposed.By integrating structural risk minimization and locality preserving criterion in a unified framework,the resulting separating hyperplane is not only in accordance with the structural risk minimization principle but also be sensitive to the manifold structure of data points.The proposed model can be solved efficiently by alternating optimization method.Experimental results on several public available benchmark datasets show the feasibility and effectiveness of the proposed method.
Nature of complex number and complex-valued neural net-works

We discuss the nature of complex number and its effect on complex-valued neural networks(CVNNs).After we review some examples of CVNN applications,we look back at the mathematical history to elucidate the features of complex number,in particular to confirm the importance of the phaseand-amplitude viewpoint for designing and constructing CVNNs to enhance the features.This viewpoint is essential in general to deal with waves such as electromagnetic wave and lightwave.Then,we point out that,although we represent a complex number as an ordered pair of real numbers for example,we can reduce ineffective degree of freedom in learning or self-organization in CVNNs to achieve better generalization characteristics.This merit is significantly useful not only for waverelated signal processing but also for general processing with frequency-domain treatment through Fourier trans-form.