2,024 research outputs found
Study the Heavy Molecular States in Quark Model with Meson Exchange Interaction
Some charmonium-like resonances such as X(3872) can be interpreted as
possible molecular states. Within the quark model, we study
the structure of such molecular states and the similar
molecular states by taking into account of the light meson exchange (,
, , and ) between two light quarks from different
mesons
Dynamical study of the possible molecular state X(3872) with the s-channel one gluon exchange interaction
The recently observed X(3872) resonance, which is difficult to be assigned a
conventional charmonium state in the quark model, may be interpreted
as a molecular state. Such a molecular state is a hidden flavor four quark
state because of its charmonium-like quantum numbers. The s-channel one gluon
exchange is an interaction which only acts in the hidden flavor multi-quark
system. In this paper, we will study the X(3872) and other similiar hidden
flavor molecular states in a quark model by taking into account of the
s-channel one gluon exchange interaction
Demystifying RCE Vulnerabilities in LLM-Integrated Apps
In recent years, Large Language Models (LLMs) have demonstrated remarkable
potential across various downstream tasks. LLM-integrated frameworks, which
serve as the essential infrastructure, have given rise to many LLM-integrated
web apps. However, some of these frameworks suffer from Remote Code Execution
(RCE) vulnerabilities, allowing attackers to execute arbitrary code on apps'
servers remotely via prompt injections. Despite the severity of these
vulnerabilities, no existing work has been conducted for a systematic
investigation of them. This leaves a great challenge on how to detect
vulnerabilities in frameworks as well as LLM-integrated apps in real-world
scenarios.
To fill this gap, we present two novel strategies, including 1) a static
analysis-based tool called LLMSmith to scan the source code of the framework to
detect potential RCE vulnerabilities and 2) a prompt-based automated testing
approach to verify the vulnerability in LLM-integrated web apps. We discovered
13 vulnerabilities in 6 frameworks, including 12 RCE vulnerabilities and 1
arbitrary file read/write vulnerability. 11 of them are confirmed by the
framework developers, resulting in the assignment of 7 CVE IDs. After testing
51 apps, we found vulnerabilities in 17 apps, 16 of which are vulnerable to RCE
and 1 to SQL injection. We responsibly reported all 17 issues to the
corresponding developers and received acknowledgments. Furthermore, we amplify
the attack impact beyond achieving RCE by allowing attackers to exploit other
app users (e.g. app responses hijacking, user API key leakage) without direct
interaction between the attacker and the victim. Lastly, we propose some
mitigating strategies for improving the security awareness of both framework
and app developers, helping them to mitigate these risks effectively
Molecular Beam Epitaxy Growth of Superconducting LiFeAs Film on SrTiO3(001) Substrate
The stoichiometric "111" iron-based superconductor, LiFeAs, has attacted
great research interest in recent years. For the first time, we have
successfully grown LiFeAs thin film by molecular beam epitaxy (MBE) on
SrTiO3(001) substrate, and studied the interfacial growth behavior by
reflection high energy electron diffraction (RHEED) and low-temperature
scanning tunneling microscope (LT-STM). The effects of substrate temperature
and Li/Fe flux ratio were investigated. Uniform LiFeAs film as thin as 3
quintuple-layer (QL) is formed. Superconducting gap appears in LiFeAs films
thicker than 4 QL at 4.7 K. When the film is thicker than 13 QL, the
superconducting gap determined by the distance between coherence peaks is about
7 meV, close to the value of bulk material. The ex situ transport measurement
of thick LiFeAs film shows a sharp superconducting transition around 16 K. The
upper critical field, Hc2(0)=13.0 T, is estimated from the temperature
dependent magnetoresistance. The precise thickness and quality control of
LiFeAs film paves the road of growing similar ultrathin iron arsenide films.Comment: 7 pages, 6 figure
Spatio-Temporal Change of LakeWater Extent in Wuhan Urban Agglomeration Based on Landsat Images from 1987 to 2015
Urban lakes play an important role in urban development and environmental protection for the Wuhan urban agglomeration. Under the impacts of urbanization and climate change, understanding urban lake-water extent dynamics is significant. However, few studies on the lake-water extent changes for the Wuhan urban agglomeration exist. This research employed 1375 seasonally continuous Landsat TM/ETM+/OLI data scenes to evaluate the lake-water extent changes from 1987 to 2015. The random forest model was used to extract water bodies based on eleven feature variables, including six remote-sensing spectral bands and five spectral indices. An accuracy assessment yielded a mean classification accuracy of 93.11%, with a standard deviation of 2.26%. The calculated results revealed the following: (1) The average maximum lake-water area of the Wuhan urban agglomeration was 2262.17 km2 from 1987 to 2002, and it decreased to 2020.78 km2 from 2005 to 2015, with a loss of 241.39 km2 (10.67%). (2) The lake-water areas of loss of Wuhan, Huanggang, Xianning, and Xiaogan cities, were 114.83 km2, 44.40 km2, 45.39 km2, and 31.18 km2, respectively, with percentages of loss of 14.30%, 11.83%, 13.16%, and 23.05%, respectively. (3) The lake-water areas in the Wuhan urban agglomeration were 226.29 km2, 322.71 km2, 460.35 km2, 400.79 km2, 535.51 km2, and 635.42 km2 under water inundation frequencies of 5%–10%, 10%–20%, 20%–40%, 40%–60%, 60%–80%, and 80%–100%, respectively. The Wuhan urban agglomeration was approved as the pilot area for national comprehensive reform, for promoting resource-saving and environmentally friendly developments. This study could be used as guidance for lake protection and water resource management
6DOF Pose Estimation of a 3D Rigid Object based on Edge-enhanced Point Pair Features
The point pair feature (PPF) is widely used for 6D pose estimation. In this
paper, we propose an efficient 6D pose estimation method based on the PPF
framework. We introduce a well-targeted down-sampling strategy that focuses
more on edge area for efficient feature extraction of complex geometry. A pose
hypothesis validation approach is proposed to resolve the symmetric ambiguity
by calculating edge matching degree. We perform evaluations on two challenging
datasets and one real-world collected dataset, demonstrating the superiority of
our method on pose estimation of geometrically complex, occluded, symmetrical
objects. We further validate our method by applying it to simulated punctures.Comment: 16 pages,20 figure
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