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

Luttinger Parameter g for Metallic Carbon Nanotubes and Related Systems

The random phase approximation (RPA) theory is used to derive the Luttinger parameter g for metallic carbon nanotubes. The results are consistent with the Tomonaga-Luttinger models. All metallic carbon nanotubes, regardless if they are armchair tubes, zigzag tubes, or chiral tubes, should have the same Luttinger parameter g. However, a (10,10) carbon peapod should have a smaller g value than a (10,10) carbon nanotube. Changing the Fermi level by applying a gate voltage has only a second order effect on the g value. RPA theory is a valid approach to calculate plasmon energy in carbon nanotube systems, regardless if the ground state is a Luttinger liquid or Fermi liquid. (This paper was published in PRB 66, 193405 (2002). However, Eqs. (6), (9), and (19) were misprinted there.)Comment: 2 figure

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

Efek Durasi Penggunaan Masker Kain Terhadap End-tidal Karbon Dioksida Pada Mahasiswa Fakultas Kedokteran Universitas Pattimura

Abstrak Masker kain berfungsi untuk melindungi pengguna dari partikel yang terbawa melalui droplet, atau airborne. Penggunaan masker kain dengan jangka waktu yang lebih lama dapat menimbulkan hiperkapnia dengan gejala berupa dyspnea, takikardia, pusing, dan nyeri kepala, yang ditandai dengan kadar CO2 >45. Metode penelitian ini yaitu metode eksperimental, dengan teknik pengambilan simple random sampling, dengan jumlah responden 36 yang dibagi dalam dua kelompok yaitu kontrol dan perlakuan. Data hasil pengamatan dianalisis menggunakan uji Independent Sample T-Test apabila data berdistribusi normal dan mann-whitney jika berdistribusi tidak normal. Hasil uji Mann-Whitney menunjukkan bahwa pada menit ke-0 nilai p = 0, 864, hasil uji Independent Sample T-Test pada menit ke-30 kelompok kontrol nilai p = 0, 850, kelompok perlakuan nilai p = 0, 851 menit ke-60 kelompok kontrol nilai p = 0,935, perlakuan nilai p = 0,935, menit ke-90 kelompok kontrol nilai p = 0,568, kelompok perlakuan nilai p = 0,569 menit ke-120 kelompok kontrol nilai p = 0,056, kelompok perlakuan nilai p = 0,056. Dari hasil kelima pengukuran tersebut rata-rata nilai p = >0,05 yang artinya tidak ada perbedaan yang signifikan. Kesimpulan dari penelitian ini menunjukan bahwa tidak ada efek dari durasi penggunaan masker kain terhadap end-tidal karbon dioksida dalam waktu 2 jam pada mahasiswa Fakultas Kedokteran Universitas Pattimura,dan tidak menunjukan tanda dan gejala yang muncul sebagai efek durasi penggunaan masker kain dalam waktu 2 jam, dengan lima kali pengukuran, yaitu pada menit ke-0, 30, 60, 90 dan 120. Abstract Cloth masks serve to protect users from particles carried through droplets, or airborne. The use of cloth masks for a longer period of time can cause hypercapnia with symptoms such as dyspnea, tachycardia, dizziness, and headaches, which are characterized by CO2 levels >45. This research method is an experimental method, with a simple random sampling technique, with 36 respondents divided into two groups, namely control and treatment. Observational data were analyzed using the Independent Sample T-Test if the data was normally distributed and Mann-Whitney if the distribution was not normal. The results of the Mann-Whitney test showed that at minute 0 the p value = 0.864, the results of the Independent Sample T-Test test at minute 30 the control group p value = 0.850, the treatment group p value = 0.851 minutes to -60 control group p value = 0,935, treatment p value = 0,935, 90th minute control group p value = 0,568, treatment group p value = 0,569 minute 120 control group p value = 0,056, treatment group p value = 0,056. From the results of the five measurements, the average p value = > 0.05, which means there is no significant difference. The test results mean that there is no effect between the duration of using a cloth mask on the end-tidal carbon dioxide

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

Permeation of a Metalworking Fluid Through a Latex Glove Under Field Use Conditions

Whole glove testing for a metalworking fluid (MWF) in the field was performed for the first time. Green latex gloves used in a machine shop were exposed for 20 min to MWF. The permeated amount (1.0 ± 0.5 μg/cm2) was higher than the threshold (0.25 μg/cm2) for the ASTM F739-99a closed-loop normalized breakthrough time

Effect of different drying methods on the protein and product quality of hairtail fish meat gel

Three different methods, namely hot air drying (HA), microwave vacuum drying (MV), and vacuum freeze drying (FD), were employed to investigate the effect of drying method on the quality of hairtail fish meat gel. Compared with HA and MV, FD samples showed a better quality in terms of moisture content, water absorption index, and water solubility index, and had the highest overall acceptance in sensory evaluation. FD preserved the protein from degradation and formed an ordered porous microstructure. The nitrogen fraction assay revealed that protein was degraded into 40–100 kDa fragments during drying in HA, which was almost not affected by MV and FD. Overall, FD was the most suitable method for drying of meat gel made from hairtail, followed by MV and HA

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

Low-temperature structural model of hcp solid C70_{70}

We report intermolecular potential-energy calculations for solid C_${70}$ and determine the optimum static orientations of the molecules at low temperature; we find them to be consistent with the monoclinic structural model proposed by us in an earlier report [Solid State Commun. {\bf 105), 247 (1998)]. This model indicates that the C_5 axis of the molecule is tilted by an angle $\approx$18^o from the monoclinic b axis in contrast with the molecular orientation proposed by Verheijen {\it et al.} [J. Chem. Phys. {\bf 166}, 287 (1992)] where the C_5 axis is parallel to the monoclinic b axis. In this calculation we have incorporated the effective bond charge Coulomb potential together with the Lennard-Jones potential between the molecule at the origin of the monoclinic unit cell and its six nearest neighbours, three above and three below. The minimum energy configuration for the molecular orientations turns out to be at $\theta$=18^o, $\phi$=8^o, and $\psi$=5^o, where $\theta$, $\phi$, and $\psi$ define the molecular orientations.Comment: ReVTeX (4 pages) + 2 PostScript figure