Hasil untuk "q-fin.PM"

Jiangang Zhu, S. Ozdemir, Yun-Feng Xiao et al.

The ability to detect and size individual nanoparticles with high resolution is crucial to understanding the behaviour of single particles and effectively using their strong size-dependent properties to develop innovative products. We report realtime, in situ detection and sizing of single nanoparticles, down to 30 nm in radius, using mode splitting in a monolithic ultrahigh-quality-factor (Q) whispering-gallery-mode microresonator. Particle binding splits a whispering-gallery mode into two spectrally shifted resonance modes, forming a self-referenced detection scheme. This technique provides superior noise suppression and enables the extraction of accurate particle size information with a single-shot measurement in a microscale device. Our method requires neither labelling of the particles nor a priori information on their presence in the medium, providing an effective platform to study nanoparticles at single-particle resolution. With the rapid progress in nanotechnology, nanoparticles of different materials and sizes have been synthesized and engineered as key components in various applications ranging from solar cell

M. Turunen, J. Olsson, G. Dallner

Coenzyme Q (CoQ) is present in all cells and membranes and in addition to be a member of the mitochondrial respiratory chain it has also several other functions of great importance for the cellular metabolism. This review summarizes the findings available to day concerning CoQ distribution, biosynthesis, regulatory modifications and its participation in cellular metabolism. There are a number of indications that this lipid is not always functioning by its direct presence at the site of action but also using e.g. receptor expression modifications, signal transduction mechanisms and action through its metabolites. The biosynthesis of CoQ is studied in great detail in bacteria and yeast but only to a limited extent in animal tissues and therefore the informations available is restricted. However, it is known that the CoQ is compartmentalized in the cell with multiple sites of biosynthesis, breakdown and regulation which is the basis of functional specialization. Some regulatory mechanisms concerning amount and biosynthesis are established and nuclear transcription factors are partly identified in this process. Using appropriate ligands of nuclear receptors the biosynthetic rate can be increased in experimental system which raises the possibility of drug-induced upregulation of the lipid in deficiency. During aging and pathophysiological conditions the tissue concentration of CoQ is modified which influences cellular functions. In this case the extent of disturbances is dependent on the localization and the modified distribution of the lipid at cellular and membrane levels.

E. Lindenberg, S. Ross

M. Jimbo

U. Bhawandeep, V. Khachatryan, A. Sirunyan et al.

The CMS trigger system must reduce an input data rate from the LHC bunch-crossing frequency of 40 MHz to a rate which will be written to permanent storage. A detailed study has recently been made of the performance of this system. This paper presents key elements of the results obtained and gives details of a draft “trigger table” for the Level-1 Trigger and the High-Level Trigger selection at a “start-up” luminosity of 2× 1033 cm – 2s – 1. High efficiencies for most physics objects are attainable with a selection that remains inclusive and avoids detailed topological or other requirements on the event.

A. Yaghjian, S. Best

Qing Zhang, S. Ha, Xinfeng Liu et al.

C. Breuil, B. Conrad, Fred Diamond et al.

We complete the proof that every elliptic curve over the rational numbers is modular.

Cindy J. Smith, Osborn, M. Osborn et al.

K. Ono

Annette Michalski, Eugen Damoc, J. Hauschild et al.

Mass spectrometry-based proteomics has greatly benefitted from enormous advances in high resolution instrumentation in recent years. In particular, the combination of a linear ion trap with the Orbitrap analyzer has proven to be a popular instrument configuration. Complementing this hybrid trap-trap instrument, as well as the standalone Orbitrap analyzer termed Exactive, we here present coupling of a quadrupole mass filter to an Orbitrap analyzer. This “Q Exactive” instrument features high ion currents because of an S-lens, and fast high-energy collision-induced dissociation peptide fragmentation because of parallel filling and detection modes. The image current from the detector is processed by an “enhanced Fourier Transformation” algorithm, doubling mass spectrometric resolution. Together with almost instantaneous isolation and fragmentation, the instrument achieves overall cycle times of 1 s for a top10 higher energy collisional dissociation method. More than 2500 proteins can be identified in standard 90-min gradients of tryptic digests of mammalian cell lysate— a significant improvement over previous Orbitrap mass spectrometers. Furthermore, the quadrupole Orbitrap analyzer combination enables multiplexed operation at the MS and tandem MS levels. This is demonstrated in a multiplexed single ion monitoring mode, in which the quadrupole rapidly switches among different narrow mass ranges that are analyzed in a single composite MS spectrum. Similarly, the quadrupole allows fragmentation of different precursor masses in rapid succession, followed by joint analysis of the higher energy collisional dissociation fragment ions in the Orbitrap analyzer. High performance in a robust benchtop format together with the ability to perform complex multiplexed scan modes make the Q Exactive an exciting new instrument for the proteomics and general analytical communities.

L. Kriston, I. Scholl, L. Hölzel et al.

P. Bolton, Hui Chen, Neng Wang

Zhao Tong, Hongjian Chen, Xiaomei Deng et al.

Abstract Task scheduling, which plays a vital role in cloud computing, is a critical factor that determines the performance of cloud computing. From the booming economy of information processing to the increasing need of quality of service (QoS) in the business of networking, the dynamic task-scheduling problem has attracted worldwide attention. Due to its complexity, task scheduling has been defined and classified as an NP-hard problem. Additionally, most dynamic online task scheduling often manages tasks in a complex environment, which makes it even more challenging to balance and satisfy the benefits of each aspect of cloud computing. In this paper, we propose a novel artificial intelligence algorithm, called deep Q-learning task scheduling (DQTS), that combines the advantages of the Q-learning algorithm and a deep neural network. This new approach is aimed at solving the problem of handling directed acyclic graph (DAG) tasks in a cloud computing environment. The essential idea of our approach uses the popular deep Q-learning (DQL) method in task scheduling, where fundamental model learning is primarily inspired by DQL. Based on developments in WorkflowSim, experiments are conducted that comparatively consider the variance of makespan and load balance in task scheduling. Both simulation and real-life experiments are conducted to verify the efficiency of optimization and learning abilities in DQTS. The result shows that when compared with several standard algorithms precoded in WorkflowSim, DQTS has advantages regarding learning ability, containment, and scalability. In this paper, we have successfully developed a new method for task scheduling in cloud computing.

S. Bermudo, Pawel Korus, JUAN EDUARDO Nápoles Valdés

Wess A. Cohen, Lily R. Mundy, Tiffany N. S. Ballard et al.

Biao Luo, Derong Liu, Tingwen Huang et al.

Xindong Peng, Lin Liu

The q‐rung orthopair fuzzy set (q‐ROFS), originally developed by Yager, is more capable than that of Pythagorean fuzzy set to deal uncertainty in real life. The main goal of this paper is to investigate the relationship between the distance measure, the similarity measure, the entropy, and the inclusion measure for q‐ROFSs. The primary purpose of the study is to develop the systematic transformation of information measures (distance measure, similarity measure, entropy, and inclusion measure) for q‐ROFSs. For obtaining this goal, some new formulae for information measures of q‐ROFSs are presented. To show the validity of the explored similarity measure, we apply it to pattern recognition, clustering analysis, and medical diagnosis. Some illustrative examples are given to support the findings, and also demonstrate their practicality and availability of similarity measure between q‐ROFSs.

Sunil Mithas, R. Rust

D. Hoaglin