932 research outputs found
Determining layer number of two dimensional flakes of transition-metal dichalcogenides by the Raman intensity from substrate
Transition-metal dichalcogenide (TMD) semiconductors have been widely studied
due to their distinctive electronic and optical properties. The property of TMD
flakes is a function of its thickness, or layer number (N). How to determine N
of ultrathin TMDs materials is of primary importance for fundamental study and
practical applications. Raman mode intensity from substrates has been used to
identify N of intrinsic and defective multilayer graphenes up to N=100.
However, such analysis is not applicable for ultrathin TMD flakes due to the
lack of a unified complex refractive index () from monolayer to bulk
TMDs. Here, we discuss the N identification of TMD flakes on the SiO/Si
substrate by the intensity ratio between the Si peak from 100-nm (or 89-nm)
SiO/Si substrates underneath TMD flakes and that from bare SiO/Si
substrates. We assume the real part of of TMD flakes as that of
monolayer TMD and treat the imaginary part of as a fitting
parameter to fit the experimental intensity ratio. An empirical ,
namely, , of ultrathin MoS, WS and WSe
flakes from monolayer to multilayer is obtained for typical laser excitations
(2.54 eV, 2.34 eV, or 2.09 eV). The fitted of MoS has
been used to identify N of MoS flakes deposited on 302-nm SiO/Si
substrate, which agrees well with that determined from their shear and
layer-breathing modes. This technique by measuring Raman intensity from the
substrate can be extended to identify N of ultrathin 2D flakes with N-dependent
. For the application purpose, the intensity ratio excited by
specific laser excitations has been provided for MoS, WS and
WSe flakes and multilayer graphene flakes deposited on Si substrates
covered by 80-110 nm or 280-310 nm SiO layer.Comment: 10 pages, 4 figures. Accepted by Nanotechnolog
Tree-Structured Neural Machine for Linguistics-Aware Sentence Generation
Different from other sequential data, sentences in natural language are
structured by linguistic grammars. Previous generative conversational models
with chain-structured decoder ignore this structure in human language and might
generate plausible responses with less satisfactory relevance and fluency. In
this study, we aim to incorporate the results from linguistic analysis into the
process of sentence generation for high-quality conversation generation.
Specifically, we use a dependency parser to transform each response sentence
into a dependency tree and construct a training corpus of sentence-tree pairs.
A tree-structured decoder is developed to learn the mapping from a sentence to
its tree, where different types of hidden states are used to depict the local
dependencies from an internal tree node to its children. For training
acceleration, we propose a tree canonicalization method, which transforms trees
into equivalent ternary trees. Then, with a proposed tree-structured search
method, the model is able to generate the most probable responses in the form
of dependency trees, which are finally flattened into sequences as the system
output. Experimental results demonstrate that the proposed X2Tree framework
outperforms baseline methods over 11.15% increase of acceptance ratio
Throughput Maximization Leveraging Just-Enough SNR Margin and Channel Spacing Optimization
Flexible optical network is a promising technology to accommodate
high-capacity demands in next-generation networks. To ensure uninterrupted
communication, existing lightpath provisioning schemes are mainly done with the
assumption of worst-case resource under-provisioning and fixed channel spacing,
which preserves an excessive signal-to-noise ratio (SNR) margin. However, under
a resource over-provisioning scenario, the excessive SNR margin restricts the
transmission bit-rate or transmission reach, leading to physical layer resource
waste and stranded transmission capacity. To tackle this challenging problem,
we leverage an iterative feedback tuning algorithm to provide a just-enough SNR
margin, so as to maximize the network throughput. Specifically, the proposed
algorithm is implemented in three steps. First, starting from the high SNR
margin setup, we establish an integer linear programming model as well as a
heuristic algorithm to maximize the network throughput by solving the problem
of routing, modulation format, forward error correction, baud-rate selection,
and spectrum assignment. Second, we optimize the channel spacing of the
lightpaths obtained from the previous step, thereby increasing the available
physical layer resources. Finally, we iteratively reduce the SNR margin of each
lightpath until the network throughput cannot be increased. Through numerical
simulations, we confirm the throughput improvement in different networks and
with different baud-rates. In particular, we find that our algorithm enables
over 20\% relative gain when network resource is over-provisioned, compared to
the traditional method preserving an excessive SNR margin.Comment: submitted to IEEE JLT, Jul. 17th, 2021. 14 pages, 8 figure
Throughput Maximization in Multi-Band Optical Networks with Column Generation
Multi-band transmission is a promising technical direction for spectrum and
capacity expansion of existing optical networks. Due to the increase in the
number of usable wavelengths in multi-band optical networks, the complexity of
resource allocation problems becomes a major concern. Moreover, the
transmission performance, spectrum width, and cost constraint across optical
bands may be heterogeneous. Assuming a worst-case transmission margin in U, L,
and C-bands, this paper investigates the problem of throughput maximization in
multi-band optical networks, including the optimization of route, wavelength,
and band assignment. We propose a low-complexity decomposition approach based
on Column Generation (CG) to address the scalability issue faced by traditional
methodologies. We numerically compare the results obtained by our CG-based
approach to an integer linear programming model, confirming the near-optimal
network throughput. Our results also demonstrate the scalability of the
CG-based approach when the number of wavelengths increases, with the
computation time in the magnitude order of 10 s for cases varying from 75 to
1200 wavelength channels per link in a 14-node network.Comment: 6 pages, 4 figures, submitted to IEEE International Conference on
Communications 2024 (ICC2024). (Note on arXiv: for beginners in the area of
column generation, please refer to the example computation in the file
. I have uploaded it to this arXiv
project along with other source files.
Maximizing Revenue With Adaptive Modulation and Multiple FECs in Flexible Optical Networks
Flexible optical networks (FONs) are being adopted to accommodate the increasingly heterogeneous traffic in today's Internet. However, in presence of high traffic load, not all offered traffic can be satisfied at all time. As carried traffic load brings revenues to operators, traffic blocking due to limited spectrum resource leads to revenue losses. In this study, given a set of traffic requests to be provisioned, we consider the problem of maximizing operator's revenue, subject to limited spectrum resource and physical layer impairments (PLIs), namely amplified spontaneous emission noise (ASE), self-channel interference (SCI), cross-channel interference (XCI), and node crosstalk. In FONs, adaptive modulation, multiple FEC, and the tuning of power spectrum density (PSD) can be effectively employed to mitigate the impact of PLIs. Hence, in our study, we propose a universal bandwidth-related impairment evaluation model based on channel bandwidth, which allows a performance analysis for different PSD, FEC and modulations. Leveraging this PLI model and a piecewise linear fitting function, we succeed to formulate the revenue maximization problem as a mixed integer linear program. Then, to solve the problem on larger network instances, a fast two-phase heuristic algorithm is also proposed, which is shown to be near-optimal for revenue maximization. Through simulations, we demonstrate that using adaptive modulation enables to significantly increase revenues in the scenario of high signal-to-noise ratio (SNR), where the revenue can even be doubled for high traffic load, while using multiple FECs is more profitable for scenarios with low SNR
Telomere Recombination Accelerates Cellular Aging in Saccharomyces cerevisiae
Telomeres are nucleoprotein structures located at the linear ends of eukaryotic chromosomes. Telomere integrity is required for cell proliferation and survival. Although the vast majority of eukaryotic species use telomerase as a primary means for telomere maintenance, a few species can use recombination or retrotransposon-mediated maintenance pathways. Since Saccharomyces cerevisiae can use both telomerase and recombination to replicate telomeres, budding yeast provides a useful system with which to examine the evolutionary advantages of telomerase and recombination in preserving an organism or cell under natural selection. In this study, we examined the life span in telomerase-null, post-senescent type II survivors that have employed homologous recombination to replicate their telomeres. Type II recombination survivors stably maintained chromosomal integrity but exhibited a significantly reduced replicative life span. Normal patterns of cell morphology at the end of a replicative life span and aging-dependent sterility were observed in telomerase-null type II survivors, suggesting the type II survivors aged prematurely in a manner that is phenotypically consistent with that of wild-type senescent cells. The shortened life span of type II survivors was extended by calorie restriction or TOR1 deletion, but not by Fob1p inactivation or Sir2p over-expression. Intriguingly, rDNA recombination was decreased in type II survivors, indicating that the premature aging of type II survivors was not caused by an increase in extra-chromosomal rDNA circle accumulation. Reintroduction of telomerase activity immediately restored the replicative life span of type II survivors despite their heterogeneous telomeres. These results suggest that telomere recombination accelerates cellular aging in telomerase-null type II survivors and that telomerase is likely a superior telomere maintenance pathway in sustaining yeast replicative life span
2,2′-[(1E)-3-Phenylprop-2-ene-1,1-diyl]bis(3-hydroxy-5,5-dimethylcyclohex-2-en-1-one)
In the title molecule, C25H30O4, the two cyclohexene rings adopt envelope conformations. The two hydroxy groups are involved in the formation of intramolecular O—H⋯O hydrogen bonds. In the crystal structure, weak intermolecular C—H⋯O hydrogen bonds link molecules related by translation along the axis a into chains
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