Nondispersive and dispersive collective electronic modes in carbon nanotubes

We propose a new theoretical interpretation of the electron energy-loss spectroscopy results of Pichler {\it et al.} on bulk carbon nanotube samples. The experimentally found nondispersive modes have been attributed by Pichler {\it et al.} to interband excitations between localized states polarized perpendicular to the nanotube axis. This interpretation has been challenged by a theorist who attributed the modes to optical plasmons carrying nonzero angular momenta. We point out that both interpretations suffer from difficulties. From our theoretical results of the loss functions for individual carbon nanotubes based on a tight-binding model, we find that the nondispersive modes could be due to collective electronic modes in chiral carbon nanotubes, while the observed dispersive mode should be due to collective electronic modes in armchair and zigzag carbon nanotubes. Momentum-dependent electron energy-loss experiments on individual carbon nanotubes should be able to confirm or disprove this interpretation decisively.Comment: 4 pages, 3 figure

Hybridization Of Tetraploid And Diploid Crassostrea Gigas (Thunberg) With Diploid C-Ariakensis (Fujita)

Three replicates of hybrid crosses of tetraploid and diploid C gigas (Thunberg) with diploid C ariakensis (Fujita) were produced with controls. Larval survival and growth were documented. Cytological events were also monitored in oocytes from hybrid crosses following insemination. Among the four types of hybrid crosses, diploid C. gigas (female) x diploid C. ariakensis (male) (GA) was the most successful. Survival of GA was about the same as that of controls in two of three replications, although its growth rate was 25-30% lower. Crosses of tetraploid C. gigas (female) and diploid C. ariakensis (male) (GGA) had poor yield at day 2 post-fertilization (0.05%), but grew nearly as well as controls subsequently. The other two types of hybrids (i.e., diploid C. ariakensis [female] and tetraploid C. gigas [male] [AGG], diploid C ariakensis [female] and diploid C. gigos [male] [AG]) suffered very low yield at day 2 (0.01% and 0.003%) and grew very slowly. Spat were obtained from all replicates of GA crosses and one of three replicates of GGA, and proved to be hybrids by polymerase chain reaction/restriction fragment length polymorphism (PCR/RFLP) diagnosis. GGA hybrids were confirmed to be triploid by flow cytometry. No larvae survived to eyed stage in AGG or AG crosses. Cytological examination revealed that the vast majority (\u3e99%) of oocytes from hybrid crosses had a prolonged meiotic prophase I or metaphase I at least through 180 min post-insemination

High-performance acceleration of 2-D and 3D CNNs on FPGAs using static block floating point

Over the past few years, 2-D convolutional neural networks (CNNs) have demonstrated their great success in a wide range of 2-D computer vision applications, such as image classification and object detection. At the same time, 3-D CNNs, as a variant of 2-D CNNs, have shown their excellent ability to analyze 3-D data, such as video and geometric data. However, the heavy algorithmic complexity of 2-D and 3-D CNNs imposes a substantial overhead over the speed of these networks, which limits their deployment in real-life applications. Although various domain-specific accelerators have been proposed to address this challenge, most of them only focus on accelerating 2-D CNNs, without considering their computational efficiency on 3-D CNNs. In this article, we propose a unified hardware architecture to accelerate both 2-D and 3-D CNNs with high hardware efficiency. Our experiments demonstrate that the proposed accelerator can achieve up to 92.4% and 85.2% multiply-accumulate efficiency on 2-D and 3-D CNNs, respectively. To improve the hardware performance, we propose a hardware-friendly quantization approach called static block floating point (BFP), which eliminates the frequent representation conversions required in traditional dynamic BFP arithmetic. Comparing with the integer linear quantization using zero-point, the static BFP quantization can decrease the logic resource consumption of the convolutional kernel design by nearly 50% on a field-programmable gate array (FPGA). Without time-consuming retraining, the proposed static BFP quantization is able to quantize the precision to 8-bit mantissa with negligible accuracy loss. As different CNNs on our reconfigurable system require different hardware and software parameters to achieve optimal hardware performance and accuracy, we also propose an automatic tool for parameter optimization. Based on our hardware design and optimization, we demonstrate that the proposed accelerator can achieve 3.8-5.6 times higher energy efficiency than graphics processing unit (GPU) implementation. Comparing with the state-of-the-art FPGA-based accelerators, our design achieves higher generality and up to 1.4-2.2 times higher resource efficiency on both 2-D and 3-D CNNs

Lamellar to Rod Eutectic Transition in the Hypereutectic Nickel- Aluminum Alloy

Directional solidification experiments were carried out on the hypereutectic Ni-25 at.% Al alloy to examine the effect of growth velocity on the eutectic microstructure. The growth velocity was varied from 1 to 20 μm/s at a constant temperature gradient of 10.0 K/mm. The microstructural observations of unidirectionally solidified samples show that the lamellar eutectic growth was observed in the sample solidified at a constant velocity of 1 μm/s and the rod eutectic growth at velocities higher than 10 μm/s. A microstructural transition from lamellar to rod eutectics was achieved at the intermediate velocity. The lamellar to rod eutectic transition was shown to result from the compositional change due to the presence of strong convection in the melt. The undercooling-spacing curves showed that the average eutectic spacings for the lamellar and the rod structures were 1.6 times larger than that in the minimum undercooling for a given velocity

Far-infrared absorption in parallel quantum wires with weak tunneling

We study collective and single-particle intersubband excitations in a system of quantum wires coupled via weak tunneling. For an isolated wire with parabolic confinement, the Kohn's theorem guarantees that the absorption spectrum represents a single sharp peak centered at the frequency given by the bare confining potential. We show that the effect of weak tunneling between two parabolic quantum wires is twofold: (i) additional peaks corresponding to single-particle excitations appear in the absorption spectrum, and (ii) the main absorption peak acquires a depolarization shift. We also show that the interplay between tunneling and weak perpendicular magnetic field drastically enhances the dispersion of single-particle excitations. The latter leads to a strong damping of the intersubband plasmon for magnetic fields exceeding a critical value.Comment: 18 pages + 6 postcript figure

F-E3D: FPGA-based acceleration of an efficient 3D convolutional neural network for human action recognition

Three-dimensional convolutional neural networks (3D CNNs) have demonstrated their outstanding classification accuracy for human action recognition (HAR). However, the large number of computations and parameters in 3D CNNs limits their deployability in real-life applications. To address this challenge, this paper adopts an algorithm-hardware co-design method by proposing an efficient 3D CNN building unit called 3D-1 bottleneck residual block (3D-1 BRB) at the algorithm level, and a corresponding FPGA-based hardware architecture called F-E3D at hardware level. Based on 3D-1 BRB, a novel 3D CNN model called E3DNet is developed, which achieves nearly 37 times reduction in model size and 5% improvement in accuracy compared to standard 3D CNNs on the UCF101 dataset. Together with several hardware optimizations, including 3D fused BRB, online blocking and kernel reuse, the proposed F-E3D is nearly 13 times faster than a previous FPGA design for 3D CNNs, with performance and accuracy comparable to other state-of-the-art 3D CNN models on GPU platforms while requiring only 7% of their energy consumption

Theory of Luminescent Emission in Nanocrystal ZnS:Mn with an Extra Electron

We consider the effect of an extra electron injected into a doped quantum dot $ZnS:Mn^{2+}$. The Coulomb interaction and the exchange interaction between the extra electron and the states of the Mn ion will mix the wavefunctions, split the impurity energy levels, break the previous selection rules and change the transition probabilities. Using this model of an extra electron in the doped quantum dot, we calculated the energy and the wavefunctions, the luminescence probability and the transition lifetime and compare with the experiments. Our calculation shows that two orders of magnitudes of lifetime shortening can occur in the transition $^4T_1-^6A_1$ when an extra electron is present.Comment: 15 pages, 2 Figs No change in Fig

Upconversion nanoparticle platform for efficient dendritic cell antigen delivery and simultaneous tracking

Upconversion nanoparticles (UCNPs) represent a group of NPs that can convert near-infrared (NIR) light into ultraviolet and visible light, thus possess deep tissue penetration power with less background fluorescence noise interference, and do not induce damage to biological tissues. Due to their unique optical properties and possibility for surface modification, UCNPs can be exploited for concomitant antigen delivery into dendritic cells (DCs) and monitoring by molecular imaging. In this study, we focus on the development of a nano-delivery platform targeting DCs for immunotherapy and simultaneous imaging. OVA 254–267 (OVA24) peptide antigen, harboring a CD8 T cell epitope, and Pam3CysSerLys4 (Pam3CSK4) adjuvant were chemically linked to the surface of UCNPs by amide condensation to stimulate DC maturation and antigen presentation. The OVA24-Pam3CSK4-UCNPs were thoroughly characterized and showed a homogeneous morphology and surface electronegativity, which promoted a good dispersion of the NPs. In vitro experiments demonstrated that OVA24-Pam3CSK4-UCNPs induced a strong immune response, including DC maturation, T cell activation, and proliferation, as well as interferon gamma (IFN-γ) production. In vivo, highly sensitive upconversion luminescence (UCL) imaging of OVA24-Pam3CSK4-UCNPs allowed tracking of UCNPs from the periphery to lymph nodes. In summary, OVA24-Pam3CSK4-UCNPs represent an effective tool for DC-based immunotherapy. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00604-022-05441-z