26,093 research outputs found
The Buffered \pi-Calculus: A Model for Concurrent Languages
Message-passing based concurrent languages are widely used in developing
large distributed and coordination systems. This paper presents the buffered
-calculus --- a variant of the -calculus where channel names are
classified into buffered and unbuffered: communication along buffered channels
is asynchronous, and remains synchronous along unbuffered channels. We show
that the buffered -calculus can be fully simulated in the polyadic
-calculus with respect to strong bisimulation. In contrast to the
-calculus which is hard to use in practice, the new language enables easy
and clear modeling of practical concurrent languages. We encode two real-world
concurrent languages in the buffered -calculus: the (core) Go language and
the (Core) Erlang. Both encodings are fully abstract with respect to weak
bisimulations
A Novel Deep Learning Framework for Internal Gross Target Volume Definition from 4D Computed Tomography of Lung Cancer Patients
In this paper, we study the reliability of a novel deep learning framework for internal gross target volume (IGTV) delineation from four-dimensional computed tomography (4DCT), which is applied to patients with lung cancer treated by Stereotactic Body Radiation Therapy (SBRT). 77 patients who underwent SBRT followed by 4DCT scans were incorporated in a retrospective study. The IGTV_DL was delineated using a novel deep machine learning algorithm with a linear exhaustive optimal combination framework, for the purpose of comparison, three other IGTVs base on common methods was also delineated, we compared the relative volume difference (RVI), matching index (MI) and encompassment index (EI) for the above IGTVs. Then, multiple parameter regression analysis assesses the tumor volume and motion range as clinical influencing factors in the MI variation. Experimental results demonstrated that the deep learning algorithm with linear exhaustive optimal combination framework has a higher probability of achieving optimal MI compared with other currently widely used methods. For patients after simple breathing training by keeping the respiratory frequency in 10 BMP, the four phase combinations of 0%, 30%, 50% and 90% can be considered as a potential candidate for an optimal combination to synthesis IGTV in all respiration amplitudes
The Crystal Structure of Monovalent Streptavidin.
The strong interaction between streptavidin (SA) and biotin is widely utilized in biotechnological applications. A SA variant, monovalent SA, was developed with a single and high affinity biotin-binding site within the intact tetramer. However, its structural characterization remains undetermined. Here, we seek to determine the crystal structure of monovalent SA at 1.7-Å resolution. We show that, in contrast to its 'close-state' in the only wild-type subunit, the L3,4 loops of three Dead SA subunits are free from crystal packing and remain in an 'open state', stabilized by a consistent H-bonding network involving S52. This H-bonding network also applies to the previously reported open state of the wild-type apo-SA. These results suggest that specific substitutions (N23A/S27D/S45A) at biotin-binding sites stabilize the open state of SA L3,4 loop, thereby further reducing biotin-binding affinity. The general features of the 'open state' SA among different SA variants may facilitate its rational design. The structural information of monovalent SA will be valuable for its applications across a wide range of biotechnological areas
Effect of weak measurement on entanglement distribution over noisy channels
Being able to implement effective entanglement distribution in noisy
environments is a key step towards practical quantum communication, and
long-term efforts have been made on the development of it. Recently, it has
been found that the null-result weak measurement (NRWM) can be used to enhance
probabilistically the entanglement of a single copy of amplitude-damped
entangled state. This paper investigates remote distributions of bipartite and
multipartite entangled states in the amplitudedamping environment by combining
NRWMs and entanglement distillation protocols (EDPs). We show that the NRWM has
no positive effect on the distribution of bipartite maximally entangled states
and multipartite Greenberger-Horne-Zeilinger states, although it is able to
increase the amount of entanglement of each source state (noisy entangled
state) of EDPs with a certain probability. However, we find that the NRWM would
contribute to remote distributions of multipartite W states. We demonstrate
that the NRWM can not only reduce the fidelity thresholds for distillability of
decohered W states, but also raise the distillation efficiencies of W states.
Our results suggest a new idea for quantifying the ability of a local filtering
operation in protecting entanglement from decoherence.Comment: 15 pages, 9 figures. Minor revision has been mad
Multiparty quantum secret sharing with pure entangled states and decoy photons
We present a scheme for multiparty quantum secret sharing of a private key
with pure entangled states and decoy photons. The boss, say Alice uses the
decoy photons, which are randomly in one of the four nonorthogonal
single-photon states, to prevent a potentially dishonest agent from
eavesdropping freely. This scheme requires the parties of communication to have
neither an ideal single-photon quantum source nor a maximally entangled one,
which makes this scheme more convenient than others in a practical application.
Moreover, it has the advantage of having high intrinsic efficiency for qubits
and exchanging less classical information in principle.Comment: 5 pages, no figure
Optimizing Quantum Programs against Decoherence: Delaying Qubits into Quantum Superposition
Quantum computing technology has reached a second renaissance in the last
decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum
noise and decoherence, which affect the accuracy and execution effect of
quantum programs, cannot be ignored and corrected by the near future NISQ
computers. In order to let users more easily write quantum programs, the
compiler and runtime system should consider underlying quantum hardware
features such as decoherence. To address the challenges posed by decoherence,
in this paper, we propose and prototype QLifeReducer to minimize the qubit
lifetime in the input OpenQASM program by delaying qubits into quantum
superposition. QLifeReducer includes three core modules, i.e.,the parser,
parallelism analyzer and transformer. It introduces the layered bundle format
to express the quantum program, where a set of parallelizable quantum
operations is packaged into a bundle. We evaluate quantum programs before and
after transformed by QLifeReducer on both real IBM Q 5 Tenerife and the
self-developed simulator. The experimental results show that QLifeReducer
reduces the error rate of a quantum program when executed on IBMQ 5 Tenerife by
11%; and can reduce the longest qubit lifetime as well as average qubit
lifetime by more than 20% on most quantum workloads.Comment: To appear in TASE2019 - the 13th International Symposium on
Theoretical Aspects of Software Engineering (submitted on Jan 25, 2019, and
this is camera-ready version
Does Notch play a tumor suppressor role across diverse squamous cell carcinomas?
The role of Notch pathway in tumorigenesis is highly variable. It can be tumor suppressive or pro-oncogenic, typically depending on the cellular context. Squamous cell carcinoma (SCC) is a cancer of the squamous cell, which can occur in diverse human tissues. SCCs are one of the most frequent human malignancies for which the pathologic mechanisms remain elusive. Recent genomic analysis of diverse SCCs identified marked levels of mutations in NOTCH1, implicating Notch signaling pathways in the pathogenesis of SCCs. In this review, evidences highlighting NOTCH's role in different types of SCCs are summarized. Moreover, based on accumulating structural information of the NOTCH receptor, the functional consequences of NOTCH1 gene mutations identified from diverse SCCs are analyzed, emphasizing loss of function of Notch in these cancers. Finally, we discuss the convergent view on an intriguing possibility that Notch may function as tumor suppressor in SCCs across different tissues. These mechanistic insights into Notch signaling pathways will help to guide the research of SCCs and development of therapeutic strategies for these cancers
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