28,415 research outputs found
Lattice QCD calculation of scattering length
We study s-wave pion-pion () scattering length in lattice QCD for
pion masses ranging from 330 MeV to 466 MeV. In the "Asqtad" improved staggered
fermion formulation, we calculate the four-point functions for isospin
I=0 and 2 channels, and use chiral perturbation theory at next-to-leading order
to extrapolate our simulation results. Extrapolating to the physical pion mass
gives the scattering lengths as and for isospin I=2 and 0 channels, respectively. Our lattice
simulation for scattering length in the I=0 channel is an exploratory
study, where we include the disconnected contribution, and our preliminary
result is near to its experimental value. These simulations are performed with
MILC 2+1 flavor gauge configurations at lattice spacing fm.Comment: Remove some typo
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Experimental and computational investigation of confined laser-induced breakdown spectroscopy
This paper presents an experimental and computational study on laser-induced breakdown spectroscopy (LIBS) for both unconfined flat surface and confined cavity cases. An integrated LIBS system is employed to acquire the shockwave and plasma plume images. The computational model consists of the mass, momentum, and energy conservation equations, which are necessary to describe shockwave behaviors. The numerical predictions are validated against shadowgraphic images in terms of shockwave expansion and reflection. The three-dimensional (3D) shockwave morphology and velocity fields are displayed and discussed
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Multi-aspect, robust, and memory exclusive guest os fingerprinting
Precise fingerprinting of an operating system (OS) is critical to many security and forensics applications in the cloud, such as virtual machine (VM) introspection, penetration testing, guest OS administration, kernel dump analysis, and memory forensics. The existing OS fingerprinting techniques primarily inspect network packets or CPU states, and they all fall short in precision and usability. As the physical memory of a VM always exists in all these applications, in this article, we present OS-Sommelier+, a multi-aspect, memory exclusive approach for precise and robust guest OS fingerprinting in the cloud. It works as follows: given a physical memory dump of a guest OS, OS-Sommelier+ first uses a code hash based approach from kernel code aspect to determine the guest OS version. If code hash approach fails, OS-Sommelier+ then uses a kernel data signature based approach from kernel data aspect to determine the version. We have implemented a prototype system, and tested it with a number of Linux kernels. Our evaluation results show that the code hash approach is faster but can only fingerprint the known kernels, and data signature approach complements the code signature approach and can fingerprint even unknown kernels
The effect of pre-processing and grain structure on the bio-corrosion and fatigue resistance of magnesium alloy AZ31
Magnesium alloys are broadly used for structural applications in the aerospace and automotive industries as well as in consumer electronics. While a high specific strength is the forte of magnesium alloys, one serious limitation for Mg alloys is their corrosion performance. Unlike aluminium, it does not form a stable passive film to provide long-term protection from further corrosion. The poor corrosion resistance of magnesium and magnesium alloys is regarded as a major drawback, and significant effort has been focused on improving this.[1-3] However, the high reactivity of magnesium alloys in corrosive media can be used to advantage in biomedical applications, particularly in temporary implants where the capacity of a material for bio-degradation is one of the most sought after properties. Indeed, permanent implant materials, such as stainless steel, titanium alloys or Nitinol (55Ni-45Ti), are the only choices currently available for hard tissue implantation. They can cause permanent physical irritation, long-term endothelial dysfunction and chronic inflammatory local reaction. Sometimes a second operation is needed for the implant to be removed. Given the ability of the human body to gradually recover and regenerate damaged tissue, the ideal solution would thus be a degradable implant, which would offer a physiologically less invasive repair and temporary support during tissue recovery. After fulfilling its function, this implant would be obliterated, being absorbed by the body. This philosophy of implant surgery would also be of particular interest for endovascular stent
Beyond relativistic mean-field studies of low-lying states in neutron-deficient krypton isotopes
Neutron-deficient krypton isotopes are of particular interest due to the
coexistence of oblate and prolate shapes in low-lying states and the transition
of ground-state from one dominate shape to another as a function of neutron
number. A detailed interpretation of these phenomena in neutron-deficient Kr
isotopes requires the use of a method going beyond a mean-field approach that
permits to determine spectra and transition probabilities. The aim of this work
is to provide a systematic calculation of low-lying state in the even-even
68-86Kr isotopes and to understand the shape coexistence phenomenon and the
onset of large collectivity around N=40 from beyond relativistic mean-field
studies. The starting point of our method is a set of relativistic
mean-field+BCS wave functions generated with a constraint on triaxial
deformations (beta, gamma). The excitation energies and electric multipole
transition strengths of low-lying states are calculated by solving a
five-dimensional collective Hamiltonian (5DCH) with parameters determined by
the mean-field wave functions. To examine the role of triaxiality, a
configuration mixing of both particle number (PN) and angular momentum (AM)
projected axially deformed states is also carried out within the exact
generator coordinate method (GCM) based on the same energy density functional.
The energy surfaces, the excitation energies of 0^+_2, 2^+_1, 2^+_2 states, as
well as the E0 and E2 transition strengths are compared with the results of
similar 5DCH calculations but with parameters determined by the
non-relativistic mean-field wave functions, as well as with the available
data...Comment: 23 pages, 10 figure
ZIKV infection activates the IRE1-XBP1 and ATF6 pathways of unfolded protein response in neural cells.
BACKGROUND: Many viruses depend on the extensive membranous network of the endoplasmic reticulum (ER) for their translation, replication, and packaging. Certain membrane modifications of the ER can be a trigger for ER stress, as well as the accumulation of viral protein in the ER by viral infection. Then, unfolded protein response (UPR) is activated to alleviate the stress. Zika virus (ZIKV) is a mosquito-borne flavivirus and its infection causes microcephaly in newborns and serious neurological complications in adults. Here, we investigated ER stress and the regulating model of UPR in ZIKV-infected neural cells in vitro and in vivo. METHODS: Mice deficient in type I and II IFN receptors were infected with ZIKV via intraperitoneal injection and the nervous tissues of the mice were assayed at 5 days post-infection. The expression of phospho-IRE1, XBP1, and ATF6 which were the key markers of ER stress were analyzed by immunohistochemistry assay in vivo. Additionally, the nuclear localization of XBP1s and ATF6n were analyzed by immunohistofluorescence. Furthermore, two representative neural cells, neuroblastoma cell line (SK-N-SH) and astrocytoma cell line (CCF-STTG1), were selected to verify the ER stress in vitro. The expression of BIP, phospho-elF2α, phospho-IRE1, and ATF6 were analyzed through western blot and the nuclear localization of XBP1s was performed by confocal immunofluorescence microscopy. RT-qPCR was also used to quantify the mRNA level of the UPR downstream genes in vitro and in vivo. RESULTS: ZIKV infection significantly upregulated the expression of ER stress markers in vitro and in vivo. Phospho-IRE1 and XBP1 expression significantly increased in the cerebellum and mesocephalon, while ATF6 expression significantly increased in the mesocephalon. ATF6n and XBP1s were translocated into the cell nucleus. The levels of BIP, ATF6, phospho-elf2α, and spliced xbp1 also significantly increased in vitro. Furthermore, the downstream genes of UPR were detected to investigate the regulating model of the UPR during ZIKV infection in vitro and in vivo. The transcriptional levels of atf4, gadd34, chop, and edem-1 in vivo and that of gadd34 and chop in vitro significantly increased. CONCLUSION: Findings in this study demonstrated that ZIKV infection activates ER stress in neural cells. The results offer clues to further study the mechanism of neuropathogenesis caused by ZIKV infection
A convolutional neural network for impact detection and characterization of complex composite structures
This paper reports on a novel metamodel for impact detection, localization and characterization of complex composite structures based on Convolutional Neural Networks (CNN) and passive sensing. Methods to generate appropriate input datasets and network architectures for impact localization and characterization were proposed, investigated and optimized. The ultrasonic waves generated by external impact events and recorded by piezoelectric sensors are transferred to 2D images which are used for impact detection and characterization. The accuracy of the detection was tested on a composite fuselage panel which was shown to be over 94%. In addition, the scalability of this metamodelling technique has been investigated by training the CNN metamodels with the data from part of the stiffened panel and testing the performance on other sections with similar geometry. Impacts were detected with an accuracy of over 95%. Impact energy levels were also successfully categorized while trained at coupon level and applied to sub-components with greater complexity. These results validated the applicability of the proposed CNN-based metamodel to real-life application such as composite aircraft parts
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