44 research outputs found
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High-temperature IR spectra of nioboborate glass melts
The structure of nioboborate glass melts in the system Nb2O5—B2O3—K2O has been studied for the first time by high-temperature IR spectra. The structure models of the glass melts and the glasses have been established
Tradition and mortality : evidence from twin infanticide in Africa
Mortality of twins relative to singletons is no greater today among African ethnicities that once practiced twin infanticide. We introduce data on historic twin infanticide and merge it with birth records from 23 African countries. We use the full sample, a border sample of adjacent societies with and without past twin infanticide, and a sample of twins. All three samples provide no evidence that past twin infanticide predicts greater differential twin mortality today. Twin infanticide and negative attitudes towards twins were suppressed by Africans, missionaries, and colonial governments. Where these channels were weak, we find evidence of greater twin mortality today
SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution
Transformer-based methods have achieved impressive image restoration
performance due to their capacities to model long-range dependency compared to
CNN-based methods. However, advances like SwinIR adopts the window-based and
local attention strategy to balance the performance and computational overhead,
which restricts employing large receptive fields to capture global information
and establish long dependencies in the early layers. To further improve the
efficiency of capturing global information, in this work, we propose SwinFIR to
extend SwinIR by replacing Fast Fourier Convolution (FFC) components, which
have the image-wide receptive field. We also revisit other advanced techniques,
i.e, data augmentation, pre-training, and feature ensemble to improve the
effect of image reconstruction. And our feature ensemble method enables the
performance of the model to be considerably enhanced without increasing the
training and testing time. We applied our algorithm on multiple popular
large-scale benchmarks and achieved state-of-the-art performance comparing to
the existing methods. For example, our SwinFIR achieves the PSNR of 32.83 dB on
Manga109 dataset, which is 0.8 dB higher than the state-of-the-art SwinIR
method
V2I-Based Platooning Design with Delay Awareness
This paper studies the vehicle platooning system based on
vehicle-to-infrastructure (V2I) communication, where all the vehicles in the
platoon upload their driving state information to the roadside unit (RSU), and
RSU makes the platoon control decisions with the assistance of edge computing.
By addressing the delay concern, a platoon control approach is proposed to
achieve plant stability and string stability. The effects of the time headway,
communication and edge computing delays on the stability are quantified. The
velocity and size of the stable platoon are calculated, which show the impacts
of the radio parameters such as massive MIMO antennas and frequency band on the
platoon configuration. The handover performance between RSUs in the V2I-based
platooning system is quantified by considering the effects of the RSU's
coverage and platoon size, which demonstrates that the velocity of a stable
platoon should be appropriately chosen, in order to meet the V2I's
Quality-of-Service and handover constraints
GraphPrompt: Biomedical Entity Normalization Using Graph-based Prompt Templates
Biomedical entity normalization unifies the language across biomedical
experiments and studies, and further enables us to obtain a holistic view of
life sciences. Current approaches mainly study the normalization of more
standardized entities such as diseases and drugs, while disregarding the more
ambiguous but crucial entities such as pathways, functions and cell types,
hindering their real-world applications. To achieve biomedical entity
normalization on these under-explored entities, we first introduce an
expert-curated dataset OBO-syn encompassing 70 different types of entities and
2 million curated entity-synonym pairs. To utilize the unique graph structure
in this dataset, we propose GraphPrompt, a prompt-based learning approach that
creates prompt templates according to the graphs. GraphPrompt obtained 41.0%
and 29.9% improvement on zero-shot and few-shot settings respectively,
indicating the effectiveness of these graph-based prompt templates. We envision
that our method GraphPrompt and OBO-syn dataset can be broadly applied to
graph-based NLP tasks, and serve as the basis for analyzing diverse and
accumulating biomedical data.Comment: 12 page
Towards the assignments for and meson nonets
In this work, we investigate the mass spectrum of and
meson nonets in the framework of the meson mass matrix and Regge
phenomenology. The results are compared with the values from different
phenomenological models and may be useful for the assignment of the
and meson nonets in the future.Comment: 13 pages, 6 figure