208 research outputs found
Universal scaling of strange particle spectra in pp collisions
As a complementary study to that performed on the transverse momentum
() spectra of charged pions, kaons and protons in proton-proton (pp)
collisions at LHC energies 0.9, 2.76 and 7 TeV, we present a scaling behaviour
in the spectra of strange particles (, ,
and ) at these three energies. This scaling behaviour is
exhibited when the spectra are expressed in a suitable scaling variable
, where the scaling parameter is determined by the quality
factor method and increases with the center of mass energy (). The
rates at which increases with for these strange
particles are found to be identical within errors. In the framework of the
colour string percolation model, we argue that these strange particles are
produced through the decay of clusters that are formed by the colour strings
overlapping. We observe that the strange mesons and baryons are produced from
clusters with different size distributions, while the strange mesons (baryons)
and ( and ) originate from clusters
with the same size distributions. The cluster's size distributions for strange
mesons are more dispersed than those for strange baryons. The scaling behaviour
of the spectra for these strange particles can be explained by the
colour string percolation model in a quantitative way.Comment: 8 pages, 10 figures, accepted by EPJ
Kosmos-2: Grounding Multimodal Large Language Models to the World
We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new
capabilities of perceiving object descriptions (e.g., bounding boxes) and
grounding text to the visual world. Specifically, we represent refer
expressions as links in Markdown, i.e., ``[text span](bounding boxes)'', where
object descriptions are sequences of location tokens. Together with multimodal
corpora, we construct large-scale data of grounded image-text pairs (called
GrIT) to train the model. In addition to the existing capabilities of MLLMs
(e.g., perceiving general modalities, following instructions, and performing
in-context learning), Kosmos-2 integrates the grounding capability into
downstream applications. We evaluate Kosmos-2 on a wide range of tasks,
including (i) multimodal grounding, such as referring expression comprehension,
and phrase grounding, (ii) multimodal referring, such as referring expression
generation, (iii) perception-language tasks, and (iv) language understanding
and generation. This work lays out the foundation for the development of
Embodiment AI and sheds light on the big convergence of language, multimodal
perception, action, and world modeling, which is a key step toward artificial
general intelligence. Data, demo, and pretrained models are available at
https://aka.ms/kosmos-2.Comment: 20 page
Adsorption of gas molecules on graphene nanoribbons and its implication for nano-scale molecule sensor
We have studied the adsorption of gas molecules (CO, NO, NO2, O2, N2, CO2,
and NH3) on graphene nanoribbons (GNRs) using first principles methods. The
adsorption geometries, adsorption energies, charge transfer, and electronic
band structures are obtained. We find that the electronic and transport
properties of the GNR with armchair-shaped edges are sensitive to the
adsorption of NH3 and the system exhibits n type semiconducting behavior after
NH3 adsorption. Other gas molecules have little effect on modifying the
conductance of GNRs. Quantum transport calculations further indicate that NH3
molecules can be detected out of these gas molecules by GNR based sensor.Comment: 13 pages and 5 figure
Wnt/β-catenin signaling in liver cancers
Liver cancer is among the leading global healthcare issues associated with high morbidity and mortality. Liver cancer consists of hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), hepatoblastoma (HB), and several other rare tumors. Progression has been witnessed in understanding the interactions between etiological as well as environmental factors and the host in the development of liver cancers. However, the pathogenesis remains poorly understood, hampering the design of rational strategies aiding in preventing liver cancers. Accumulating evidence demonstrates that aberrant activation of the Wnt/β-catenin signaling pathway plays an important role in the initiation and progression of HCC, CCA, and HB. Targeting Wnt/β-catenin signaling potentiates a novel avenue for liver cancer treatment, which may benefit from the development of numerous small-molecule inhibitors and biologic agents in this field. In this review, we discuss the interaction between various etiological factors and components of Wnt/β-catenin signaling early in the precancerous lesion and the acquired mechanisms to further enhance Wnt/β-catenin signaling to promote robust cancer formation at later stages. Additionally, we shed light on current relevant inhibitors tested in liver cancers and provide future perspectives for preclinical and clinical liver cancer studies
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