Exciton diffusion in semiconducting single-wall carbon nanotubes studied by transient absorption microscopy

Spatiotemporal dynamics of excitons in isolated semiconducting single-walled carbon nanotubes are studied using transient absorption microscopy. Differential reflection and transmission of an 810-nm probe pulse after excitation by a 750-nm pump pulse are measured. We observe a bi-exponentially decaying signal with a fast time constant of 0.66 ps and a slower time constant of 2.8 ps. Both constants are independent of the pump fluence. By spatially and temporally resolving the differential reflection, we are able to observe a diffusion of excitons, and measure a diffusion coefficient of 200 cm2/s at room temperature and 300 cm2/s at lower temperatures of 10 K and 150 K.Comment: 6 pages, 4 figure

Transmission of doughnut light through a bull's eye structure

We experimentally investigate the extraordinary optical transmission of doughnut light through a bull's eye structure. Since the intensity is vanished in the center of the beam, almost all the energy reaches the circular corrugations (not on the hole), excite surface plasmons which propagate through the hole and reradiate photons. The transmitted energy is about 57 times of the input energy on the hole area. It is also interesting that the transmitted light has a similar spatial shape with the input light although the diameter of the hole is much smaller than the wavelength of light.Comment: 3 pages,4 figure

Antidiabetic activity of isoquercetin in diabetic KK -Ay mice

<p>Abstract</p> <p>Background</p> <p>Tartary buckwheat bran is an important natural source of quercetin and isoquercetin. Quercetin and isoquercetin are both powerful α-glucosidase inhibitors. Although the IC₅₀of isoquercetin as α-glucosidase inhibitor was much higher than that of quercetin, the bioavailability of isoquercetin was higher than that of quercetin. Hence, we are interested in the antidiabetic effect of isoquercetin in diabetic KK -A^ymice.</p> <p>Methods</p> <p>The hypoglycemic effect of isoquercetin in a type 2 diabetic animal model (KK-A^ymice) was studied. Isoquercetin was administrated at doses of 50, 100 and 200 mg/kg for 35 days.</p> <p>Results</p> <p>It was found that fasting blood glucose concentration was decreased with the 200 mg/kg group (<it>p </it>< 0.01) the most efficient compared with the diabetic control group. In addition, there was significant decrease in plasma C-peptide, triglyceride, total cholesterol and blood urea nitrogen levels after 35 days. Meanwhile, glucose tolerance was improved, and the immunoreactive of pancreatic islets β-cells was promoted.</p> <p>Conclusions</p> <p>These results suggest that isoquercetin had a regulative role in blood glucose level and lipids, and improved the function of pancreatic islets. Isoquercetin may be useful in the treatment of type 2 diabetes mellitus.</p

Machine Eye for Defects: Machine Learning-Based Solution to Identify and Characterize Topological Defects in Textured Images of Nematic Materials

Topological defects play a key role in the structures and dynamics of liquid crystals (LCs) and other ordered systems. There is a recent interest in studying defects in different biological systems with distinct textures. However, a robust method to directly recognize defects and extract their structural features from various traditional and nontraditional nematic systems remains challenging to date. Here we present a machine learning solution, termed Machine Eye for Defects (MED), for automated defect analysis in images with diverse nematic textures. MED seamlessly integrates state-of-the-art object detection networks, Segment Anything Model, and vision transformer algorithms with tailored computer vision techniques. We show that MED can accurately identify the positions, winding numbers, and orientations of $\pm 1/2$ defects across distinct cellular contours, sparse vector fields of nematic directors, actin filaments, microtubules, and simulation images of Gay--Berne particles. MED performs faster than conventional defect detection method and can achieve over 90\% accuracy on recognizing $\pm1/2$ defects and their orientations from vector fields and experimental tissue images. We further demonstrate that MED can identify defect types that are not included in the training data, such as giant-core defects and defects with higher winding number. Remarkably, MED can provide correct structural information about $\pm 1$ defects. As such, MED stands poised to transform studies of diverse ordered systems by providing automated, rapid, accurate, and insightful defect analysis

Towards a complete classification of non-chiral topological phases in 2D fermion systems

In recent years, fermionic topological phases of quantum matter has attracted a lot of attention. In a pioneer work by Gu, Wang and Wen, the concept of equivalence classes of fermionic local unitary(FLU) transformations was proposed to systematically understand non-chiral topological phases in 2D fermion systems and an incomplete classification was obtained. On the other hand, the physical picture of fermion condensation and its corresponding super pivotal categories give rise to a generic mathematical framework to describe fermionic topological phases of quantum matter. In particular, it has been pointed out that in certain fermionic topological phases, there exists the so-called q-type anyon excitations, which have no analogues in bosonic theories. In this paper, we generalize the Gu, Wang and Wen construction to include those fermionic topological phases with q-type anyon excitations. We argue that all non-chiral fermionic topological phases in 2+1D are characterized by a set of tensors $(N^{ij}_{k},F^{ij}_{k},F^{ijm,\alpha\beta}_{kln,\chi\delta},n_{i},d_{i})$, which satisfy a set of nonlinear algebraic equations parameterized by phase factors $\Xi^{ijm,\alpha\beta}_{kl}$, $\Xi^{ij}_{kln,\chi\delta}$, $\Omega^{kim,\alpha\beta}_{jl}$ and $\Omega^{ki}_{jln,\chi\delta}$. Moreover, consistency conditions among algebraic equations give rise to additional constraints on these phase factors which allow us to construct a topological invariant partition for an arbitrary triangulation of 3D spin manifold. Finally, several examples with q-type anyon excitations are discussed, including the Fermionic topological phase from Tambara-Yamagami category for $\mathbb{Z}_{2N}$, which can be regarded as the $\mathbb{Z}_{2N}$ parafermion generalization of Ising fermionic topological phase.Comment: 51 pages, 3 figure

CASTER: A Computer-Vision-Assisted Wireless Channel Simulator for Gesture Recognition

In this paper, a computer-vision-assisted simulation method is proposed to address the issue of training dataset acquisition for wireless hand gesture recognition. In the existing literature, in order to classify gestures via the wireless channel estimation, massive training samples should be measured in a consistent environment, consuming significant efforts. In the proposed CASTER simulator, however, the training dataset can be simulated via existing videos. Particularly, a gesture is represented by a sequence of snapshots, and the channel impulse response of each snapshot is calculated via tracing the rays scattered off a primitive-based hand model. Moreover, CASTER simulator relies on the existing videos to extract the motion data of gestures. Thus, the massive measurements of wireless channel can be eliminated. The experiments demonstrate a 90.8% average classification accuracy of simulation-to-reality inference.Comment: 7 pages, 9 figure