242 research outputs found
Table Search Using a Deep Contextualized Language Model
Pretrained contextualized language models such as BERT have achieved
impressive results on various natural language processing benchmarks.
Benefiting from multiple pretraining tasks and large scale training corpora,
pretrained models can capture complex syntactic word relations. In this paper,
we use the deep contextualized language model BERT for the task of ad hoc table
retrieval. We investigate how to encode table content considering the table
structure and input length limit of BERT. We also propose an approach that
incorporates features from prior literature on table retrieval and jointly
trains them with BERT. In experiments on public datasets, we show that our best
approach can outperform the previous state-of-the-art method and BERT baselines
with a large margin under different evaluation metrics.Comment: Accepted at SIGIR 2020 (Long
Analysis of the current status of tuberculosis transmission in China based on a heterogeneity model
Tuberculosis (TB) is an infectious disease transmitted through the
respiratory system. China is one of the countries with a high burden of TB.
Since 2004, an average of more than 800,000 cases of active TB have been
reported each year in China. Analyzing the case data from 2004-2018, we find
significant differences in TB incidence by age group. Therefore, the effect of
age heterogeneous structure on TB transmission needs further study. We develop
a model of TB to explore the role of age heterogeneity as a factor in TB
transmission. The model is fitted numerically using the nonlinear least squares
method to obtain the key parameters in the model, and the basic reproduction
number Rv 0.8017 is calculated and the sensitivity anal-ysis of Rv to the
parameters is given. The simulation results show that reducing the number of
new infections in the elderly population and increasing the recovery rate of
elderly patients with the disease could significantly reduce the transmission
of tuberculosis. Furthermore the feasibility of achieving the goals of the WHO
End TB Strategy in China is assessed, and we obtain that with existing TB
control measures it will take another 30 years for China to reach the WHO goal
to reduce 90% of the number of new cases by year 2049. However, in theoretical
it is feasible to reach the WHO strategic goal of ending tuberculosis by 2035
if the group contact rate in the elderly population can be reduced though it is
difficulty to reduce the contact rate.Comment: We think this is a very interesting work that gives a good
understanding of the current TB transmission in China and assesses the
possibility of China achieving the 2035 TB control target and also explores
possible ways for how to prevent and control the TB in Chin
Metal-bonded Atomic Layers of Transition Metal Carbides (MXenes)
Although two-dimensional transition metal carbides and nitrides (MXenes) have
fantastic physical and chemical properties as well as wide applications, it
remains challenging to produce stable MXenes due to their rapid structural
degradation. Here, unique metal-bonded atomic layers of transition metal
carbides with high stabilities are produced via a simple topological reaction
between chlorine-terminated MXenes and selected metals, where the metals enable
to not only remove Cl terminations, but also efficiently bond with adjacent
atomic MXene slabs, driven by the symmetry of MAX phases. The films constructed
from Al-bonded TiCCl atomic layers show high oxidation resistance
up to 400 degrees centigrade and low sheet resistance of 9.3 ohm per square.
Coupled to the multi-layer structure, the Al-bonded TiCCl film
displays a significantly improved EMI shielding capability with a total
shielding effectiveness value of 39 dB at a low thickness of 3.1 micron,
outperforming pure TiCCl film
Transformation and reconstruction towards two-dimensional atomic laminates
Two-dimensional (2D) nanomaterials derived from non-van der Waals solids are
promising due to their fantastic physical and chemical properties, but it
remains challenging to obtain 2D atomic laminates with high stability owing to
the strong intrinsic covalent/metallic bonds and highly exposed active surface.
Here, we report a versatile and scalable protocol to produce 2D atomic
laminates, based on an unexpected topological transformation of MAX phases
under hydrogen chloride gas, and/or subsequent reconstruction under some
programmed gases/vapors. In contrast to the known approaches with liquid or
molten medium, our method involves in a gas-phase reaction with fast
thermodynamics for A layers and positive Gibbs free energies for MX slabs.
Remarkably, through subsequent reconstruction in some active gases/vapors (O2,
H2S, P, CH4, Al and Sn metal vapors), a big family of 2D atomic laminates with
elusive configurations as well as high chemical/thermal stabilities and tunable
electrical properties (from metallic to semiconductor-like behaviors) are
achieved. Moreover, the resultant 2D atomic laminates can be facilely scaled up
to 10 kilograms. We believe that the 2D atomic laminates would have broad
applications in catalysis, energy storage, electromagnetic shielding interface
and microwave absorption
Phylogenetic studies of magnoliids: Advances and perspectives
Magnoliids are the largest flowering plant clades outside of the eudicots and monocots, which are distributed worldwide and have high economic, ornamental and ecological values. Eudicots, monocots and magnoliids are the three major clades of Mesangiospermae, and their phylogenetic relationship is one of the most interesting issues. In recent years, with the continuous accumulation of genomic information, the evolutionary status of magnoliids has become a hot spot in plant phylogenetic research. Although great efforts have been made to study the evolution of magnoliids using molecular data from several representative species such as nuclear genome, plastid genome, mitochondrial genome, and transcriptome, the results of current studies on the phylogenetic status of magnoliids are inconsistent. Here, we systematically describe the current understanding of the molecular research on magnoliid phylogeny and review the differences in the evolutionary state of magnoliids. Understanding the research approaches and limitations of magnoliid phylogeny can guide research strategies to further improve the study of the phylogenetic evolution of magnoliids
Critical role of ASCT2-mediated amino acid metabolism in promoting leukaemia development and progression
Amino acid (AA) metabolism is involved in diverse cellular functions, including cell survival and growth, however it remains unclear how it regulates normal hematopoiesis versus leukemogenesis. Here, we report that knockout of Slc1a5 (ASCT2), a transporter of neutral AAs, especially glutamine, results in mild to moderate defects in bone marrow and mature blood cell development under steady state conditions. In contrast, constitutive or induced deletion of Slc1a5 decreases leukemia initiation and maintenance driven by the oncogene MLL-AF9 or Pten deficiency. Survival of leukemic mice is prolonged following Slc1a5 deletion, and pharmacological inhibition of ASCT2 also decreases leukemia development and progression in xenograft models of human acute myeloid leukemia. Mechanistically, loss of ASCT2 generates a global effect on cellular metabolism, disrupts leucine influx and mTOR signaling, and induces apoptosis in leukemic cells. Given the substantial difference in reliance on ASCT2-mediated AA metabolism between normal and malignant blood cells, this in vivo study suggests ASCT2 as a promising therapeutic target for the treatment of leukemia
Quantifying rainfall-derived inflow and infiltration in sanitary sewer systems based on conductivity monitoring
Quantifying rainfall-derived inflow and infiltration (RDII) in a sanitary sewer is difficult when RDII and overflow occur simultaneously. This study proposes a novel conductivity-based method for estimating RDII. The method separately decomposes rainfall-derived inflow (RDI) and rainfall-induced infiltration (RII) on the basis of conductivity data. Fast Fourier transform was adopted to analyze variations in the flow and water quality during dry weather. Nonlinear curve fitting based on the least squares algorithm was used to optimize parameters in the proposed RDII model. The method was successfully applied to real-life case studies, in which inflow and infiltration were successfully estimated for three typical rainfall events with total rainfall volumes of 6.25 mm (light), 28.15 mm (medium), and 178 mm (heavy). Uncertainties of model parameters were estimated using the generalized likelihood uncertainty estimation (GLUE) method and were found to be acceptable. Compared with traditional flow-based methods, the proposed approach exhibits distinct advantages in estimating RDII and overflow, particularly when the two processes happen simultaneously
A Ferroelectric Compute-in-Memory Annealer for Combinatorial Optimization Problems
Computationally hard combinatorial optimization problems (COPs) are
ubiquitous in many applications, including logistical planning, resource
allocation, chip design, drug explorations, and more. Due to their critical
significance and the inability of conventional hardware in efficiently handling
scaled COPs, there is a growing interest in developing computing hardware
tailored specifically for COPs, including digital annealers, dynamical Ising
machines, and quantum/photonic systems. However, significant hurdles still
remain, such as the memory access issue, the system scalability and restricted
applicability to certain types of COPs, and VLSI-incompatibility, respectively.
Here, a ferroelectric field effect transistor (FeFET) based compute-in-memory
(CiM) annealer is proposed. After converting COPs into quadratic unconstrained
binary optimization (QUBO) formulations, a hardware-algorithm co-design is
conducted, yielding an energy-efficient, versatile, and scalable hardware for
COPs. To accelerate the core vector-matrix-vector (VMV) multiplication of QUBO
formulations, a FeFET based CiM array is exploited, which can accelerate the
intended operation in-situ due to its unique three-terminal structure. In
particular, a lossless compression technique is proposed to prune typically
sparse QUBO matrix to reduce hardware cost. Furthermore, a multi-epoch
simulated annealing (MESA) algorithm is proposed to replace conventional
simulated annealing for its faster convergence and better solution quality. The
effectiveness of the proposed techniques is validated through the utilization
of developed chip prototypes for successfully solving graph coloring problem,
indicating great promise of FeFET CiM annealer in solving general COPs.Comment: 39 pages, 12 figure
O-GlcNAcylation of core components of the translation initiation machinery regulates protein synthesis
Protein synthesis is essential for cell growth, proliferation, and survival. Protein synthesis is a tightly regulated process that involves multiple mechanisms. Deregulation of protein synthesis is considered as a key factor in the development and progression of a number of diseases, such as cancer. Here we show that the dynamic modification of proteins by O-linked β-N-acetyl-glucosamine (O-GlcNAcylation) regulates translation initiation by modifying core initiation factors eIF4A and eIF4G, respectively. Mechanistically, site-specific O-GlcNAcylation of eIF4A on Ser322/323 disrupts the formation of the translation initiation complex by perturbing its interaction with eIF4G. In addition, O-GlcNAcylation inhibits the duplex unwinding activity of eIF4A, leading to impaired protein synthesis, and decreased cell proliferation. In contrast, site-specific O-GlcNAcylation of eIF4G on Ser61 promotes its interaction with poly(A)-binding protein (PABP) and poly(A) mRNA. Depletion of eIF4G O-GlcNAcylation results in inhibition of protein synthesis, cell proliferation, and soft agar colony formation. The differential glycosylation of eIF4A and eIF4G appears to be regulated in the initiation complex to fine-tune protein synthesis. Our study thus expands the current understanding of protein synthesis, and adds another dimension of complexity to translational control of cellular proteins
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