Novel process for large scale synthesis of N-(4-hydroxyphenyl) retinamide

A method to synthesize anticancer drug N-（ 4- hydroxyphenyl） retinamide （4-HPR）on a large scale is described. It consists of the preferred steps of reacting all-trans retinoic acid with thionyl chloride to form retinoyl chloride and then reacting with triethylamine to generate retinoyl ammonium salt which in turn is reacted with p-aminophenol to eventually produce 4-HPR. This process can overcome many scale-up challenges that exist in the methods reported in the literature and provide an easy, mild and high yield route for large scale synthesis of 4-HPR. Moreover, the effects of the molar ratios of the reagents on the yield are examined. The best molar ratios are a 2.0 molar equivalence of thionyl chloride and a 3.0 molar equivalence of paminophenol to retinoic acid, and the total yield is 80. 7%.

Compact Scanning Tunneling Microscope with Large Scale Searching Capability for Mmultidisciplinary Applications

We present the design and performance of a home-built scanning tunneling microscope （STM）, which is compact （66 mm tall and 25 mm in diameter）, yet equipped with a 3D atomic precision piezoelectric motor in which the Z coarse approach relies on a high simplic-ity friction-type walker （of our own invention） driven by an axially cut piezoelectric tube. The walker is vertically inserted in a piezoelectric scanner tube （PST） with its brim laying at on the PST end as the inertial slider （driven by the PST） for the XZ （sample plane） motion. The STM is designed to be capable of searching rare microscopic targets （defects, dopants, boundaries, nano-devices, etc.） in a macroscopic sample area （square millimeters） under extreme conditions （low temperatures, strong magnetic elds, etc.） in which it ts. It gives good atomic resolution images after scanning a highly oriented pyrolytic graphite sample in air at room temperature.

Local and global approaches of affinity propagation clustering for large scale data

Recently a new clustering algorithm called 'affinity propagation' (AP) has been proposed, which efficiently clustered sparsely related data by passing messages between data points. However, we want to cluster large scale data where the similarities are not sparse in many cases. This paper presents two variants of AP for grouping large scale data with a dense similarity matrix. The local approach is partition affinity propagation (PAP) and the global method is landmark affinity propagation (LAP). PAP passes messages in the subsets of data first and then merges them as the number of initial step of iterations; it can effectively reduce the number of iterations of clustering. LAP passes messages between the landmark data points first and then clusters non-landmark data points; it is a large global approximation method to speed up clustering. Experiments are conducted on many datasets, such as random data points, manifold subspaces, images of faces and Chinese calligraphy, and the results demonstrate that the two ap-proaches are feasible and practicable.

Large Scale Aspects of India-China Summer Monsoon Rainfall

This study investigates the dominant modes of variability in monthly and seasonal rainfall over the India-China region mainly through Empirical Orthogonal Function (EOF) analysis. The EOFs have shown that whereas the rainfall over India varies as one coherent zone, that over China varies in east-west oriented bands. The influence of this banded structure extends well into India.Relationship of rainfall with large scale parameters such as the subtropical ridge over the Indian and the western Pacific regions, Southern Oscillation, the Northern Hemispheric surface air temperature and stratospheric winds have also been investigated. These results show that the rainfall over the area around 40°N, 110°E over China is highly related with rainfall over India. The subtropical ridge over the Indian region is an important predictor over India as well an over the northern China region. '

Large Scale VLSI Module Placement Using LFF Heuristics by Stages

We present a deterministic algorithm for large-scale VLSI module placement. Following the less flexibility first （LFF） principle,we simulate a manual packing process in which the concept of placement by stages is introduced to reduce the overall evaluation complexity. The complexity of the proposed algorithm is （N1 ＋ N2 ） × O（ n^2 ） ＋ N3× O（n^4lgn） ,where N1, N2 ,and N3 denote the number of modules in each stage, N1 ＋ N2 ＋ N3 = n, and N3〈〈 n. This complexity is much less than the original time complexity of O（n^5lgn）. Experimental results indicate that this approach is quite promising.

Comparing the reinforcement capacity of welded steel mesh and a thin spray-on liner using large scale laboratory tests

Steel mesh is used as a passive skin confinement medium to supplement the active support provided by rock bolts for roof and rib control in underground coal mines. Thin spray-on liners(TSL) are believed to have the potential to take the place of steel mesh as the skin confinement medium in underground mines.To confirm this belief, large scale laboratory experiments were conducted to compare the behaviour of welded steel mesh and a TSL, when used in conjunction with rock bolts, in reinforcing strata with weak bedding planes and strata prone to guttering, two common rock conditions which exist in coal mines. It was found that while the peak load taken by the simulated rock mass with weak bedding planes acting as the control sample(no skin confinement) was 2494 kN, the corresponding value of the sample with 5 mm thick TSL reinforcement reached 2856 kN. The peak load of the steel mesh reinforced sample was only2321 kN, but this was attributed to the fact that one of the rock bolts broke during the test. The TSL reinforced sample had a similar post-yield behaviour as the steel mesh reinforced one. The results of the large scale guttering test indicated that a TSL is better than steel mesh in restricting rock movement and thus inhibiting the formation of gutters in the roof.

Large scale classification with local diversity AdaBoost SVM algorithm

Local diversity AdaBoost support vector machine（LDAB-SVM） is proposed for large scale dataset classification problems.The training dataset is split into several blocks firstly, and some models based on these dataset blocks are built.In order to obtain a better performance, AdaBoost is used in each model building.In the boosting iteration step, the component learners which have higher diversity and accuracy are collected via the kernel parameters adjusting.Then the local models via voting method are integrated.The experimental study shows that LDAB-SVM can deal with large scale dataset efficiently without reducing the performance of the classifier.

Large Scale Perturbations in Extratropical Atmosphere-Part Ⅰ: On Rossby Waves

This study reexamines the propagation mechanism and geostrophic property of the classical two-dimensional Rossby waves in a non-divergent barotropic atmosphere. It will be found that propagation of large scale atmospheric waves depends crucially on horizontal divergence. A small Rossby number in Rossby waves is not sufficient for the waves to have a small ageostrophic component, because the two-dimensional classical Rossby waves do not manifest the geostrophic balance as good as observed in the atmosphere.

Large Scale Perturbations in Extratropical Atmosphere-Part Ⅱ: On Geostrophic Waves

We have examined, in Part Ⅰ, the propagation mechanism and geostrophic property of classical Rossby waves in a non-divergent barotropic atmosphere. As we found that the non-divergent Rossby waves do not propagate in a hydrostatically equilibrium atmosphere, and do not manifest a good geostrophic property, an alternative large scale circulation pattern of geostrophic waves has been proposed (McHall, 1991a). The propagation mechanism and geostrophic property of these waves are examined in the present study.

Digitally Controlled Boost PFC Converters Operating with Large Scale Load Fluctuations

When boost power factor correction(PFC) circuit works with large scale load fluctuations, it is easy to cause a higher total harmonic distortion and a lower power factor because of traditional controllers and inductor current mode. To solve this problem, this paper proposes a PFC control system, which can operate with load fluctuations up to 1 000 W by using duty cycle feed-forward control theory to achieve smooth switching mode. The duty cycles in the next period of the control system are pre-estimated in the current cycle, which enhances the speeds of AD samplers and switching frequency, and reduces the cost and volume of the equipment to some extent. Introductions of system decoupling and feed-forward of input-voltage greatly improve the system performance. Both theoretical simulation and experimental results prove the advantage of the proposed scheme.

AN EXPERIMENTAL STUDY OF THE LARGE SCALE COHERENT STRUCTURES IN A FORCED FREE SHEAR LAYER

The dynamic characteristics of the large scale coherent structures in a forced free shear layer are experi- mentally studied by means of flow visualization. The quantitative measurements are acquired by the use of a LDV. It is shown that the development of the coherent structures can be greatly influenced by upstream artificial perturbations and as a result the mixing in the layer can be controlled. Like vortex merging, vortex splitting is also a common evolu- tion pattern in the development of the coherent structures.

A Reconfigurable Manufacturing System for In-site Machining Component with Large Scale

To cope with various unpredictable changes in large scale parts,the concept of reconfigurable manufacturing system (RMS) for machining these components is presented.Considering with large-size space measurement and the fixed-free manufacture mode,an automatically localizing machining method for large scale part is studied in this paper,and the architecture of the RMS for machining large scale parts is proposed.According to the method and structure,the automatically localizing model is established.The theoretical analysis and simulation examples demonstrate the feasibility and validity of the proposed method,and the results indicate that the method is suitable and effective for machining large scale components in significant scientific projects.

A Hierarchical Clustering and Fixed-Layer Local Learning Based Support Vector Machine Algorithm for Large Scale Classification Problems

It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning. In this paper, a hierarchical clustering and fixed- layer local learning （HCFLL） based support vector machine（SVM） algorithm is proposed to deal with this problem. Firstly, HCFLL hierarchically dusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering. Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree. The experimental results show that compared with the existing popular algorithms such as core vector machine and decision.tree support vector machine, HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.

Preliminary Feasibility Study on Application of Very Large Scale-Photovoltaic Power Generation in China

Some energy experts believe that solar energy photovoltaic power generation is hopeful to be applied in a large amount and possesses a certain proportion in the structure of energy in the future. In this paper, based on the forecasting of electric load demand and energy structure of power generation in the middle of 21 century, the pictures of VLS-PV power genera- tion is composed, the operation characteristic of VLS-PV power generation and the adaptability of electric power grid for it is analyzed, the ways for transmitting large amount of PV power and the economic and technical bottlenecks for applying VLS-PV power generation are discussed. Finally, the steps and suggestions for developing VLS-PV power generation and its electric power system in China are proposed.

ON THE EVOLUTION OF LARGE SCALE STRUCTURES IN THREE-DIMENSIONAL MIXING LAYERS

In this paper, several mathematical models for the large scale structures in some special kinds of mixing layers, which might be practically useful for enhancing the mixing, are proposed. First, the linear growth rate of the large scale structures in the mixing layers was calculated. Then, using the much improved weakly non-linear theory, combined with the energy method, the non-linear evolution of large scale structures in two special mixing layer configurations is calculated. One of the mixing lavers has equal magnitudes of the upstream velocity vectors, while the angles between the velocity vectors and the trailing edge were pi /2 - phi and pi /2 + phi, respectively. The other mixing layer was generated by a splitter-plate with a 45-degree-sweep trailing edge.

Large scale silver nanowires network fabricated by MeV hydrogen (H＋) ion beam irradiation

A random two-dimensional large scale nano-network of silver nanowires （Ag-NWs） is fabricated by MeV hydrogen （H＋） ion beam irradiation. Ag-NWs are irradiated under H＋ ion beam at different ion fluences at room temperature. The Ag-NW network is fabricated by H＋ ion beam-induced welding of Ag-NWs at intersecting positions. H＋ ion beam induced welding is confirmed by transmission electron microscopy （TEM） and scanning electron microscopy （SEM）. Moreover, the structure of Ag NWs remains stable under H＋ ion beam, and networks are optically transparent. Morphology also remains stable under H＋ ion beam irradiation. No slicings or cuttings of Ag-NWs are observed under MeV H＋ ion beam irradiation. The results exhibit that the formation of Ag-NW network proceeds through three steps： ion beam induced thermal spikes lead to the local heating of Ag-NWs, the formation of simple junctions on small scale, and the formation of a large scale network. This observation is useful for using Ag-NWs based devices in upper space where protons are abandoned in an energy range from MeV to GeV. This high-quality Ag-NW network can also be used as a transparent electrode for optoelectronics devices.

ON DECENTRALIZED STABILIZATION OF LINEAR LARGE SCALE SYSTEMS WITH SYMMETRIC CIRCULANT STRUCTURE

The decentralized stabilization of continuous and discrete linear large scale systems with symmetric circulant structure was studied.A few sufficient conditions on decentralized stabilization of such systems were proposed.For the continuous systems,by introducing a concept called the magnitude of interconnected structure,a very important property that the decentralized stabilization of such systems is fully determined by the structure of each isolated subsystem that is obtained when the magnitude of interconnected structure of the overall system is given.So the decentralized stabilization of such systems can be got by only appropriately designing or modifying the structure of each isolated subsystem,no matter how complicated the interconnected structure of the overall system is.A algorithm for obtaining decentralized state feedback to stabilize the overall system is given.The discrete systems were also discussed.The results show that there is a great dfference on decentralized stabilization between continuous case and discrete case.

MATHEMATICAL BASIS FOR LARGE SCALE GIS AND TERRESTRIAL DIGITAL PRODUCTS

The problem of spatial mathematical basis has been encountered by both large scale GIS and spatial digital products theoretically and practically.It is also a basic problem in the development of the whole geo_information science.After analyzing the status quo and the limitations of the space mathematical base of GIS,this paper points out definitely that the geodetic coordinate system is uniform,which can show the location of any point of the global exactly and uniquely in form of ( B,L,H ) and is the most proper reference system of large_scale GIS and Digital Earth.Moreover,this paper also puts forward a set of practical model of the standard "map projection".Finally,this paper introduces a DRG system based on this model.

AN IDENTITY-BASED KEY AGREEMENT SCHEME FOR LARGE SCALE SENSOR NETWORKS

To solve the problems of high memory occupation, low connectivity and poor resiliency against node capture, which existing in the random key pre-distribution techniques while applying to the large scale Wireless Sensor Networks （WSNs）, an Identity-Based Key Agreement Scheme （IBKAS） is proposed based on identity-based encryption and Elliptic Curve Diffie-Hellman （ECDH）. IBKAS can resist man-in-the-middle attacks and node-capture attacks through encrypting the key agreement parameters using identity-based encryption. Theoretical analysis indicates that comparing to the random key pre-distribution techniques, IBKAS achieves significant improvement in key connectivity, communication overhead, memory occupation, and security strength, and also enables efficient secure rekcying and network expansion. Furthermore, we implement IBKAS for TinyOS-2.1.2 based on the MICA2 motes, and the experiment results demonstrate that IBKAS is feasible for infrequent key distribution and rekeying for large scale sensor networks.

THE EFFECTS OF VELOCITY RATIO ON THE LARGE SCALE COHERENT STRUCTURES IN FREE SHEAR LAYERS

The velocity ratio of a free shear layer has an important influence on the spatial development of the large scale coherent structures in the layer. In this study, numerical simulations are performed to get an insight into this problem. The obtained numerical results agree quite well with those of a linear inviscid stability theory and the available experimental data.