111 research outputs found
Distribution of Onryza maga (Leech, 1890) (Lepidoptera: Hesperiidae) with description of female genitalia and taxonomic notes
For more than twenty years, Hainan, Vietnam, Myanmar, Thailand, Malaysia, Singapore and Indonesia have been erroneously reported in Chinese literature as belonging to the distribution range of Onryza maga (Leech 1890). Based upon a careful survey of specimens and relevant literature, these regions are omitted from the known range of this species. Onryza maga maga is found from northeast Guizhou, south Henan and Qinling-Daba Mountains in Shaanxi of China, its occurrence in Hunan is confirmed. The adults are redescribed and the variability of wing patterns is discussed. Female genitalia are illustrated and described for the first time. Some biological information and an updated distribution map of the species are provided
Microscale Investigation of Arsenic Distribution and Species in Cement Product from Cement Kiln Coprocessing Wastes
To improve the understanding of the immobilization mechanism and the leaching risk of Arsenic (As) in the cement product from coprocessing wastes using cement kiln, distribution and species of As in cement product were determined by microscale investigation methods, including electron probe microanalysis (EPMA) and X-ray absorption spectroscopy. In this study, sodium arsenate crystals (Na3AsO412H2O) were mixed with cement production raw materials and calcined to produce cement clinker. Then, clinker was mixed water to prepare cement paste. EPMA results showed that As was generally distributed throughout the cement paste. As content in calcium silicate hydrates gel (C-S-H) was in low level, but higher than that in other cement mineral phases. This means that most of As is expected to form some compounds that disperse on the surfaces of cement mineral phases. Linear combination fitting (LCF) of the X-ray absorption near edge structure spectra revealed that As in the cement paste was predominantly As(V) and mainly existed as Mg3(AsO4)2, Ca3(AsO4)2, and Na2HAsO4
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression
Nested networks or slimmable networks are neural networks whose architectures
can be adjusted instantly during testing time, e.g., based on computational
constraints. Recent studies have focused on a "nested dropout" layer, which is
able to order the nodes of a layer by importance during training, thus
generating a nested set of sub-networks that are optimal for different
configurations of resources. However, the dropout rate is fixed as a
hyper-parameter over different layers during the whole training process.
Therefore, when nodes are removed, the performance decays in a human-specified
trajectory rather than in a trajectory learned from data. Another drawback is
the generated sub-networks are deterministic networks without well-calibrated
uncertainty. To address these two problems, we develop a Bayesian approach to
nested neural networks. We propose a variational ordering unit that draws
samples for nested dropout at a low cost, from a proposed Downhill
distribution, which provides useful gradients to the parameters of nested
dropout. Based on this approach, we design a Bayesian nested neural network
that learns the order knowledge of the node distributions. In experiments, we
show that the proposed approach outperforms the nested network in terms of
accuracy, calibration, and out-of-domain detection in classification tasks. It
also outperforms the related approach on uncertainty-critical tasks in computer
vision.Comment: 16 pages, 10 figure
Mitigating catalyst deactivation in selective hydrogenation by enhancing dispersion and utilizing reaction heat effect
ACKNOWLEDGMENT This work was financially supported by National Key R&D Program of China (2021YFB3801600), National Natural Science Foundation of China (21908002), and Fundamental Research Funds for the Central Universities (buctrc201921, JD2223).Peer reviewedPostprin
Chiral charge density wave and backscattering-immune orbital texture in monolayer 1T-TiTe2
Non-trivial electronic states are attracting intense attention in
low-dimensional physics. Though chirality has been identified in charge states
with a scalar order parameter, its intertwining with charge density waves
(CDW), film thickness and the impact on the electronic behaviors remain less
well understood. Here, using scanning tunneling microscopy, we report a 2 x 2
chiral CDW as well as a strong suppression of the Te-5p hole-band
backscattering in monolayer 1T-TiTe2. These exotic characters vanish in bilayer
TiTe2 with a non-CDW state. Theoretical calculations approve that chirality
comes from a helical stacking of the triple-q CDW components and therefore can
persist at the two-dimensional limit. Furthermore, the chirality renders the
Te-5p bands an unconventional orbital texture that prohibits electron
backscattering. Our study establishes TiTe2 as a promising playground for
manipulating the chiral ground states at the monolayer limit and provides a
novel path to engineer electronic properties from an orbital degree.Comment: 21 pages, 5 figure
The Prognostic and Clinical Value of CD44 in Colorectal Cancer: A Meta-Analysis
Background: CD44 is widely used as a putative cancer stem cells (CSCs) marker for colorectal cancer (CRC). However, the prognostic role of CD44 in CRC remains controversial.Methods: We performed a systematic review and meta-analysis to evaluate the association of various CD44 isoforms and overall survival (OS) and clinicopathological features of CRC patients.Results: A total of 48 studies were included in the meta-analysis. Total CD44 isoforms overexpression was significantly correlated with worse OS of patients with CRC (HR = 1.32, 95% CI = 1.08–1.61, P = 0.007). In a stratified analysis, a higher level of either CD44v6 or CD44v2 had an unfavorable impact on OS (HRCD44v6 = 1.50, 95% CI = 1.10–2.14, P = 0.010; HRCD44v2 = 2.93, 95% CI = 1.49–5.77, P = 0.002). Additionally, CD44 was shown to be associated with some clinicopathological features, such as lymph node metastasis (ORCD44 = 1.56, 95% CI = 1.01–2.41, P = 0.044; ORCD44v6 = 1.97, 95% CI = 1.19–3.26, P = 0.008; ORTotal CD44 isoforms = 1.57, 95% CI = 1.15–2.14, P = 0.004), distant metastasis (ORCD44 = 2.90, 95% CI = 1.08–7.83, P = 0.035; ORTotal CD44 isoforms = 1.89, 95% CI = 1.02–3.53, P = 0.044). Moreover, a high level of CD44 showed a possible correlation with poor differentiation (ORTotal CD44 isoforms = 1.44, 95% CI = 1.00–2.08, P = 0.051), elevated level of CD44v6 tend to be correlated with tumor size (OR = 1.71, 95% CI = 0.99–2.96, P = 0.056).Conclusions: This meta-analysis demonstrated that CD44 overexpression might be an unfavorable prognostic factor for CRC patients and could be used to predict poor differentiation, lymph node metastasis and distant metastasis
GLM-130B: An Open Bilingual Pre-trained Model
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language
model with 130 billion parameters. It is an attempt to open-source a 100B-scale
model at least as good as GPT-3 (davinci) and unveil how models of such a scale
can be successfully pre-trained. Over the course of this effort, we face
numerous unexpected technical and engineering challenges, particularly on loss
spikes and divergence. In this paper, we introduce the training process of
GLM-130B including its design choices, training strategies for both efficiency
and stability, and engineering efforts. The resultant GLM-130B model offers
significant outperformance over GPT-3 175B (davinci) on a wide range of popular
English benchmarks while the performance advantage is not observed in OPT-175B
and BLOOM-176B. It also consistently and significantly outperforms ERNIE TITAN
3.0 260B -- the largest Chinese language model -- across related benchmarks.
Finally, we leverage a unique scaling property of GLM-130B to reach INT4
quantization without post training, with almost no performance loss, making it
the first among 100B-scale models and more importantly, allowing its effective
inference on 4RTX 3090 (24G) or 8RTX 2080 Ti (11G) GPUs, the
most affordable GPUs required for using 100B-scale models. The GLM-130B model
weights are publicly accessible and its code, training logs, related toolkit,
and lessons learned are open-sourced at
\url{https://github.com/THUDM/GLM-130B/}.Comment: Accepted to ICLR 202
Downregulation of Brassica napus MYB69 (BnMYB69) increases biomass growth and disease susceptibility via remodeling phytohormone, chlorophyll, shikimate and lignin levels
MYB transcription factors are major actors regulating plant development and adaptability. Brassica napus is a staple oil crop and is hampered by lodging and diseases. Here, four B. napus MYB69 (BnMYB69s) genes were cloned and functionally characterized. They were dominantly expressed in stems during lignification. BnMYB69 RNA interference (BnMYB69i) plants showed considerable changes in morphology, anatomy, metabolism and gene expression. Stem diameter, leaves, roots and total biomass were distinctly larger, but plant height was significantly reduced. Contents of lignin, cellulose and protopectin in stems were significantly reduced, accompanied with decrease in bending resistance and Sclerotinia sclerotiorum resistance. Anatomical detection observed perturbation in vascular and fiber differentiation in stems, but promotion in parenchyma growth, accompanied with changes in cell size and cell number. In shoots, contents of IAA, shikimates and proanthocyanidin were reduced, while contents of ABA, BL and leaf chlorophyll were increased. qRT-PCR revealed changes in multiple pathways of primary and secondary metabolisms. IAA treatment could recover many phenotypes and metabolisms of BnMYB69i plants. However, roots showed trends opposite to shoots in most cases, and BnMYB69i phenotypes were light-sensitive. Conclusively, BnMYB69s might be light-regulated positive regulators of shikimates-related metabolisms, and exert profound influences on various internal and external plant traits
1-Deoxynojirimycin promotes cardiac function and rescues mitochondrial cristae in mitochondrial hypertrophic cardiomyopathy
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