Hasil untuk "q-bio.NC"

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

C. Cruz, C. D. Cruz, Q. Huang et al.

Following the discovery of long-range antiferromagnetic order in the parent compounds of high-transition-temperature (high-Tc) copper oxides, there have been efforts to understand the role of magnetism in the superconductivity that occurs when mobile ‘electrons’ or ‘holes’ are doped into the antiferromagnetic parent compounds. Superconductivity in the newly discovered rare-earth iron-based oxide systems ROFeAs (R, rare-earth metal) also arises from either electron or hole doping of their non-superconducting parent compounds. The parent material LaOFeAs is metallic but shows anomalies near 150 K in both resistivity and d.c. magnetic susceptibility. Although optical conductivity and theoretical calculations suggest that LaOFeAs exhibits a spin-density-wave (SDW) instability that is suppressed by doping with electrons to induce superconductivity, there has been no direct evidence of SDW order. Here we report neutron-scattering experiments that demonstrate that LaOFeAs undergoes an abrupt structural distortion below 155 K, changing the symmetry from tetragonal (space group P4/nmm) to monoclinic (space group P112/n) at low temperatures, and then, at ∼137 K, develops long-range SDW-type antiferromagnetic order with a small moment but simple magnetic structure. Doping the system with fluorine suppresses both the magnetic order and the structural distortion in favour of superconductivity. Therefore, like high-Tc copper oxides, the superconducting regime in these iron-based materials occurs in close proximity to a long-range-ordered antiferromagnetic ground state.

Boling Guo, Liming Ling, Q. P. Liu

In this paper, we construct a generalized Darboux transformation for the nonlinear Schrödinger equation. The associated N-fold Darboux transformation is given in terms of both a summation formula and determinants. As applications, we obtain compact representations for the Nth-order rogue wave solutions of the focusing nonlinear Schrödinger equation and Hirota equation. In particular, the dynamics of the general third-order rogue wave is discussed and shown to exhibit interesting structures.

M. Kashiwara

Steven R. Brown

This primer serves two functions: (1) It is a simplified introduction to Q methodology, covering the topics of concourse, Q samples, Q sorting, correlation, factor analysis, theoretical rotation, factor scores, and factor interpretation. (2) It also illustrates different conceptions of Q methodology by taking the concept of "Q methodology" as the subject matter of the study. The factor results show how current understandings about Q are traceable to debates among Stephenson, Burt, and others in the 1930s, '40s, and '50s.

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.

M. Jimbo

E. Lindenberg, S. Ross

A. Yaghjian, S. Best

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

K. Ono

Ranjan Singh, W. Cao, I. Al-Naib et al.

High quality factor resonances are extremely promising for designing ultra-sensitive refractive index label-free sensors, since it allows intense interaction between electromagnetic waves and the analyte material. Metamaterial and plasmonic sensing have recently attracted a lot of attention due to subwavelength confinement of electromagnetic fields in the resonant structures. However, the excitation of high quality factor resonances in these systems has been a challenge. We excite an order of magnitude higher quality factor resonances in planar terahertz metamaterials that we exploit for ultrasensitive sensing. The low-loss quadrupole and Fano resonances with extremely narrow linewidths enable us to measure the minute spectral shift caused due to the smallest change in the refractive index of the surrounding media. We achieve sensitivity levels of 7.75 × 103 nm/refractive index unit (RIU) with quadrupole and 5.7 × 104 nm/RIU with the Fano resonances which could be further enhanced by using thinner substrates. These findings would facilitate the design of ultrasensitive real time chemical and biomolecular sensors in the fingerprint region of the terahertz regime.

Iordanis Kerenidis, Jonas Landman, Alessandro Luongo et al.

Quantum machine learning is one of the most promising applications of a full-scale quantum computer. Over the past few years, many quantum machine learning algorithms have been proposed that can potentially offer considerable speedups over the corresponding classical algorithms. In this paper, we introduce q-means, a new quantum algorithm for clustering which is a canonical problem in unsupervised machine learning. The $q$-means algorithm has convergence and precision guarantees similar to $k$-means, and it outputs with high probability a good approximation of the $k$ cluster centroids like the classical algorithm. Given a dataset of $N$ $d$-dimensional vectors $v_i$ (seen as a matrix $V \in \mathbb{R}^{N \times d})$ stored in QRAM, the running time of q-means is $\widetilde{O}\left( k d \frac{\eta}{\delta^2}\kappa(V)(\mu(V) + k \frac{\eta}{\delta}) + k^2 \frac{\eta^{1.5}}{\delta^2} \kappa(V)\mu(V) \right)$ per iteration, where $\kappa(V)$ is the condition number, $\mu(V)$ is a parameter that appears in quantum linear algebra procedures and $\eta = \max_{i} ||v_{i}||^{2}$. For a natural notion of well-clusterable datasets, the running time becomes $\widetilde{O}\left( k^2 d \frac{\eta^{2.5}}{\delta^3} + k^{2.5} \frac{\eta^2}{\delta^3} \right)$ per iteration, which is linear in the number of features $d$, and polynomial in the rank $k$, the maximum square norm $\eta$ and the error parameter $\delta$. Both running times are only polylogarithmic in the number of datapoints $N$. Our algorithm provides substantial savings compared to the classical $k$-means algorithm that runs in time $O(kdN)$ per iteration, particularly for the case of large datasets.

Jonathan A Stefely, D. Pagliarini

Takuya Hiraoka, Takahisa Imagawa, Taisei Hashimoto et al.

Randomized ensembled double Q-learning (REDQ) (Chen et al., 2021b) has recently achieved state-of-the-art sample efficiency on continuous-action reinforcement learning benchmarks. This superior sample efficiency is made possible by using a large Q-function ensemble. However, REDQ is much less computationally efficient than non-ensemble counterparts such as Soft Actor-Critic (SAC) (Haarnoja et al., 2018a). To make REDQ more computationally efficient, we propose a method of improving computational efficiency called DroQ, which is a variant of REDQ that uses a small ensemble of dropout Q-functions. Our dropout Q-functions are simple Q-functions equipped with dropout connection and layer normalization. Despite its simplicity of implementation, our experimental results indicate that DroQ is doubly (sample and computationally) efficient. It achieved comparable sample efficiency with REDQ, much better computational efficiency than REDQ, and comparable computational efficiency with that of SAC.

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.

R. Ortega-Ruiz, Rosario del Rey, J. Casas

Resumen El bullying es un fenomeno de agresion injustificada que actualmente sucede en dos formatos: cara a cara y como una conducta que se realiza a traves de dispositivos digitales ( cyberbullying ). Ampliamente estudiado tanto el primero como el segundo, hay sin embargo escaso conocimiento sobre la homogeneidad de ambos problemas y no disponemos de instrumentos de medida que permitan valorar las dos dimensiones del fenomeno: la agresion y la ciberagresion, la victimizacion y la cibervictimizacion. Este trabajo presenta la validacion del European Bullying Intervention Project Questionnaire y del European Cyberbullying Intervention Project Questionnaire, que evaluan la implicacion en bullying y en cyberbullying , respectivamente. Ambos se han administrado a 792 estudiantes de secundaria y se han obtenido unos buenos resultados de ajuste y propiedades psicometricas. La realizacion de un modelo de ecuaciones estructurales ha evaluado la concurrencia y relaciones entre ambos fenomenos, encontrando la influencia del bullying sobre el cyberbullying , pero no al contrario. Estos resultados muestran la idoneidad de ambos instrumentos para evaluar de forma conjunta bullying y cyberbullying , dada su importante relacion y similitud, lo que los convierten en buenas herramientas para la intervencion psicoeducativa destinada a prevenir y reducir ambos fenomenos.