One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. We believe the forthcoming solutions and theories of big data privacy root ...from the in place research output of the privacy discipline. Motivated by these factors, we extensively survey the existing research outputs and achievements of the privacy field in both application and theoretical angles, aiming to pave a solid starting ground for interested readers to address the challenges in the big data case. We first present an overview of the battle ground by defining the roles and operations of privacy systems. Second, we review the milestones of the current two major research categories of privacy: data clustering and privacy frameworks. Third, we discuss the effort of privacy study from the perspectives of different disciplines, respectively. Fourth, the mathematical description, measurement, and modeling on privacy are presented. We summarize the challenges and opportunities of this promising topic at the end of this paper, hoping to shed light on the exciting and almost uncharted land.
We present an extended collision model to simulate the dynamics of an open quantum system. In our model, the unit to represent the environment is, instead of a single particle, a block which consists ...of a number of environment particles. The introduced blocks enable us to study the effects of different strategies of system-environment interactions and states of the blocks on the non-Markovianities. We demonstrate our idea in the Gaussian channels of an all-optical system and derive a necessary and sufficient condition of non-Markovianity for such channels. Moreover, we show the equivalence of our criterion to the non-Markovian quantum jump in the simulation of the pure damping process of a single-mode field. We also show that the non-Markovianity of the channel working in the strategy that the system collides with environmental particles in each block in a certain order will be affected by the size of the block and the embedded entanglement and the effects of heating and squeezing the vacuum environmental state will quantitatively enhance the non-Markovianity.
Primary lung cancer is one of the most common malignant tumors in China. Approximately 60% of lung cancer patients have distant metastasis at the initial diagnosis, so it is necessary to find new ...tumor markers for early diagnosis and individualized treatment. Tumor markers contribute to the early diagnosis of lung cancer and play important roles in early detection and treatment, as well as in precision medicine, efficacy monitoring, and prognosis prediction. The pathological diagnosis of lung cancer in small biopsy specimens determines whether there are tumor cells in the biopsy and tumor type. Because biopsy is traumatic and the compliance of patients with multiple biopsies is poor, liquid biopsy has become a hot research direction. Liquid biopsies are advantageous because they are nontraumatic, easy to obtain, reflect the overall state of the tumor, and allow for real-time monitoring. At present, liquid biopsies mainly include circulating tumor cells, circulating tumor DNA, exosomes, microRNA, circulating RNA, tumor platelets, and tumor endothelial cells. This review introduces the research progress and clinical application prospect of liquid biopsy technology for lung cancer.
Traditional standalone embedded system is limited in their functionality, flexibility, and scalability. Fog computing platform, characterized by pushing the cloud services to the network edge, is a ...promising solution to support and strengthen traditional embedded system. Resource management is always a critical issue to the system performance. In this paper, we consider a fog computing supported software-defined embedded system, where task images lay in the storage server while computations can be conducted on either embedded device or a computation server. It is significant to design an efficient task scheduling and resource management strategy with minimized task completion time for promoting the user experience. To this end, three issues are investigated in this paper: 1) how to balance the workload on a client device and computation servers, i.e., task scheduling, 2) how to place task images on storage servers, i.e., resource management, and 3) how to balance the I/O interrupt requests among the storage servers. They are jointly considered and formulated as a mixed-integer nonlinear programming problem. To deal with its high computation complexity, a computation-efficient solution is proposed based on our formulation and validated by extensive simulation based studies.
MicroRNA‐24‐3p (miR‐24‐3p) has been implicated as a key promoter of chemotherapy resistance in numerous cancers. Meanwhile, cancer‐associated fibroblasts (CAFs) can secret exosomes to transfer ...miRNAs, which mediate tumour development. However, little is known regarding the molecular mechanism of CAF‐derived exosomal miR‐24‐3p in colon cancer (CC). Hence, this study intended to characterize the functional relevance of CAF‐derived exosomal miR‐24‐3p in CC cell resistance to methotrexate (MTX). We identified differentially expressed HEPH, CDX2 and miR‐24‐3p in CC through bioinformatics analyses, and validated their expression in CC tissues and cells. The relationship among HEPH, CDX2 and miR‐24‐3p was verified using ChIP and dual‐luciferase reporter gene assays. Exosomes were isolated from miR‐24‐3p inhibitor–treated CAFs (CAFs‐exo/miR‐24‐3p inhibitor), which were used in combination with gain‐of‐function and loss‐of‐function experiments and MTX treatment. CCK‐8, flow cytometry and colony formation assays were conducted to determine cell viability, apoptosis and colony formation, respectively. Based on the findings, CC tissues and cells presented with high expression of miR‐24‐3p and low expression of HEPH and CDX2. CDX2 was a target gene of miR‐24‐3p and could up‐regulate HEPH. Under MTX treatment, overexpressed CDX2 or HEPH and down‐regulated miR‐24‐3p reduced cell viability and colony formation and elevated cell apoptosis. Furthermore, miR‐24‐3p was transferred into CC cells via CAF‐derived exosomes. CAF‐derived exosomal miR‐24‐3p inhibitor diminished cell viability and colony formation and increased cell apoptosis in vitro and inhibited tumour growth in vivo under MTX treatment. Altogether, CAF‐derived exosomal miR‐24‐3p accelerated resistance of CC cells to MTX by down‐regulating CDX2/HEPH axis.
Abstract
Recent advances in quantum resource theories have been driven by the fact that many quantum information protocols make use of different facets of the same physical features, e.g. ...entanglement, coherence, etc. Resource theories formalise the role of these important physical features in a given protocol. One question that remains open until now is:
how quickly can a resource be generated or degraded?
Using the toolkit of quantum speed limits we construct bounds on the minimum time required for a given resource to change by a fixed increment, which might be thought of as the power of said resource, i.e., the rate of resource variation. We show that the derived bounds are tight by considering several examples. Finally, we discuss some applications of our results, which include generalisations of thermodynamic work, heat, and power to any given resource, as well as fundamental bounds on the computation rate in leading quantum processing architectures.
With the emergence of Internet-of-Things (IoT), there is now growing interest to simplify wireless network controls. This is a very challenging task, comprising information acquisition, information ...analysis, decision-making, and action implementation on large scale IoT networks. Resulting in research to explore the integration of software-defined networking (SDN) and IoT for a simpler, easier, and strain less network control. SDN is a promising novel paradigm shift which has the capability to enable a simplified and robust programmable wireless network serving an array of physical objects and applications. This paper starts with the emergence of SDN and then highlights recent significant developments in the wireless and optical domains with the aim of integrating SDN and IoT. Challenges in SDN and IoT integration are also discussed from both security and scalability perspectives.
Coherence is the most fundamental quantum feature of the nonclassical systems. The understanding of coherence within the resource theory has been attracting increasing interest among which the ...quantification of coherence is an essential ingredient. A satisfactory measure should meet certain standard criteria. It seems that the most crucial criterion should be the strong monotonicity, that is, average coherence doesn't increase under the (sub-selective) incoherent operations. Recently, the Tsallis relative α entropy has been tried to quantify the coherence. But it was shown to violate the strong monotonicity, even though it can unambiguously distinguish the coherent and the incoherent states with the monotonicity. Here we establish a family of coherence quantifiers which are closely related to the Tsallis relative α entropy. It proves that this family of quantifiers satisfy all the standard criteria and particularly cover several typical coherence measures.
Networking for Big Data: A Survey Yu, Shui; Liu, Meng; Dou, Wanchun ...
IEEE Communications surveys and tutorials,
2017-Firstquarter, 2017-00-00, 20170101, Letnik:
19, Številka:
1
Journal Article
Recenzirano
Complementary to the fancy big data applications, networking for big data is an indispensable supporting platform for these applications in practice. This emerging research branch has gained ...extensive attention from both academia and industry in recent years. In this new territory, researchers are facing many unprecedented theoretical and practical challenges. We are therefore motivated to solicit the latest works in this area, aiming to pave a comprehensive and solid starting ground for interested readers. We first clarify the definition of networking for big data based on the cross disciplinary nature and integrated needs of the domain. Second, we present the current understanding of big data from different levels, including its formation, networking features, mathematical representations, and the networking technologies. Third, we discuss the challenges and opportunities from various perspectives in this hopeful field. We further summarize the lessons we learned based on the survey. We humbly hope this paper will shed light for forthcoming researchers to further explore the uncharted part of this promising land.
PDF
