Active and Unidirectional Acceleration of Biaryl Rotation by a Molecular Motor

Light‐driven molecular motors possess immense potential as central driving units for future nanotechnology. Integration into larger molecular setups and transduction of their mechanical motions represents the current frontier of research. Herein we report on an integrated molecular machine setup allowing the transmission of potential energy from a motor unit onto a remote receiving entity. The setup consists of a motor unit connected covalently to a distant and sterically encumbered biaryl receiver. By action of the motor unit, single‐bond rotation of the receiver is strongly accelerated and forced to proceed unidirectionally. The transmitted potential energy is directly measured as the extent to which energy degeneration is lifted in the thermal atropisomerization of this biaryl. Energy degeneracy is reduced by more than 1.5 kcal mol^?1, and rate accelerations of several orders of magnitude in terms of the rate constants are achieved.     

Least-squares support vector machines and near infrared spectroscopy for quantification of common adulterants in powdered milk

This paper proposes the use of the least-squares support vector machine (LS-SVM) as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants (starch, whey or sucrose) found in powdered milk samples, using near-infrared spectroscopy with direct measurements by diffuse reflectance. Due to the spectral differences of the three adulterants a nonlinear behavior is present when all groups of adulterants are in the same data set, making the use of linear methods such as partial least squares regression (PLSR) difficult. Excellent models were built using LS-SVM, with low prediction errors and superior performance in relation to PLSR. These results show it possible to built robust models to quantify some common adulterants in powdered milk using near-infrared spectroscopy and LS-SVM as a nonlinear multivariate calibration procedure.     

具有主导晶面的BiOIO3/BiOCl异质结制备与光催化性能

分别以乙二醇/去离子水为溶剂,通过溶剂热/水热法分别制备了具有不同主导晶面的BiOIO₃/{110}BiOCl和BiOIO₃/{001}BiOCl异质结。采用X射线衍射、扫描电子显微镜、能量色散谱和紫外可见漫反射光谱对制备的BiOIO₃/BiOCl光催化剂进行了表征。在可见光照射下,通过对罗丹明 B和苯酚水溶液的光催化降解,考察了 BiOIO₃/BiOCl异质结的光催化活性。结果显示25% BiOIO₃/{110}BiOCl异质结具有最高的光催化效率。BiOIO₃/{110}BiOCl较好的光催化性能是由于其在可见光区较强的光吸收,以及异质结结构和BiOCl所具有的(110)主导晶面有利于光生载流子的分离。超氧自由基(·O₂^-)和空穴(h⁺)是光催化过程中的主要活性物质。此外,根据实验结果探讨了光催化性能增强的机理。     

两台自私型机器上自私工件排序的PoA紧界

本文研究了两台自私型机器上有自私型工件的关于二元均衡的排序问题。对任意工件序列$L$, 证明了二元均衡排序的PoA的紧界为$\frac{8}{7}$。如果工件尺寸在区间$[1, r](r\ge1)$内, 得到了二元均衡排序的PoA的紧界为关于$r$的分段线性函数。     

Development of superconducting power devices in Europe

Europe celebrated last year (2008) the 100-year anniversary of the first liquefaction of helium by H. Kammerling Onnes in Leiden. It led to the discovery of superconductivity in 1911. Europe is still active in the development of superconducting (SC) devices. The discovery of high critical temperature materials in 1986, again in Europe, has opened a lot of opportunities for SC devices by broking the 4 K cryogenic bottleneck.     

Vibrations of a continuous web on elastic supports

We consider an infinite, homogenous linearly elastic beam resting on a system of linearly elastic supports, as an idealized model for a paper web in the middle of a cylinder-based dryer section. We obtain closed-form analytical expressions for the eigenfrequencies and the eigenmodes. The frequencies increase as the support rigidity is increased. Each frequency is bounded from above by the solution with absolutely rigid supports, and from below by the solution in the limit of vanishing support rigidity. Thus in a real system, the natural frequencies will be lower than predicted by commonly used models with rigid supports.     

A monotone finite element scheme for convection-diffusion equations

A simple technique is given in this paper for the construction and analysis of a class of finite element discretizations for convection-diffusion problems in any spatial dimension by properly averaging the PDE coefficients on element edges. The resulting finite element stiffness matrix is an -matrix under some mild assumption for the underlying (generally unstructured) finite element grids. As a consequence the proposed edge-averaged finite element scheme is particularly interesting for the discretization of convection dominated problems. This scheme admits a simple variational formulation, it is easy to analyze, and it is also suitable for problems with a relatively smooth flux variable. Some simple numerical examples are given to demonstrate its effectiveness for convection dominated problems.

     

An approximation algorithm for the generalized assignment problem

The generalized assignment problem can be viewed as the following problem of scheduling parallel machines with costs. Each job is to be processed by exactly one machine; processing jobj on machinei requires timep _ij and incurs a cost ofc _ij ; each machinei is available forT _i time units, and the objective is to minimize the total cost incurred. Our main result is as follows. There is a polynomial-time algorithm that, given a valueC, either proves that no feasible schedule of costC exists, or else finds a schedule of cost at mostC where each machinei is used for at most 2T _i time units.We also extend this result to a variant of the problem where, instead of a fixed processing timep _ij , there is a range of possible processing times for each machine—job pair, and the cost linearly increases as the processing time decreases. We show that these results imply a polynomial-time 2-approximation algorithm to minimize a weighted sum of the cost and the makespan, i.e., the maximum job completion time. We also consider the objective of minimizing the mean job completion time. We show that there is a polynomial-time algorithm that, given valuesM andT, either proves that no schedule of mean job completion timeM and makespanT exists, or else finds a schedule of mean job completion time at mostM and makespan at most 2T. Research partially supported by an NSF PYI award CCR-89-96272 with matching support from UPS, and Sun Microsystems, and by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550.Research supported in part by a Packard Fellowship, a Sloan Fellowship, an NSF PYI award, and by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550.     

The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification

This study investigated the value of information from both magnetic resonance imaging and magnetic resonance spectroscopic imaging (MRSI) to automated discrimination of brain tumours. The influence of imaging intensities and metabolic data was tested by comparing the use of MR spectra from MRSI, MR imaging intensities, peak integration values obtained from the MR spectra and a combination of the latter two. Three classification techniques were objectively compared: linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis function kernel as a nonlinear technique. Classifiers were evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic (ROC) curve (AUC) was used as a global performance measure on test data. In general, all techniques obtained a high performance when using peak integration values with or without MR imaging intensities. For example for low- versus high-grade tumours, low- versus high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and peak integration values were used. The use of metabolic data from MRSI significantly improved automated classification of brain tumour types compared to the use of MR imaging intensities solely.