The Galerkin Finite Element Method for A Multi-term Time-Fractional Diffusion equation

We consider the initial/boundary value problem for a diffusion equation involving multiple time-fractional derivatives on a bounded convex polyhedral domain. We analyze a space semidiscrete scheme based on the standard Galerkin finite element method using continuous piecewise linear functions. Nearly optimal error estimates for both cases of initial data and inhomogeneous term are derived, which cover both smooth and nonsmooth data. Further we develop a fully discrete scheme based on a finite difference discretization of the time-fractional derivatives, and discuss its stability and error estimate. Extensive numerical experiments for one and two-dimension problems confirm the convergence rates of the theoretical results.Comment: 22 pages, 4 figure

A Survey on Users' Perspectives to Functionalities of Web-Based Construction Collaboration Extranets

Construction collaboration extranets (CCEs) provide various functionalities depending on the vendors' origins, history, experiences, and financial status. Previous research has listed and described the functionalities that extranet systems can be capable of providing. However, no publication was found so far to systematically analyze users' perspectives to the provided functionalities. This article is to bridge this gap through a questionnaire survey to the users. It aims at examining user's attitude to functionalities of CCEs. The result may be useful to information system vendors, end-users and researchers involved in CCEs development and implementation

Breakpoint lead-lag analysis of the last deglacial climate change and atmospheric CO2 concentration on global and hemispheric scales

Antarctic ice core records show that climate change and atmospheric CO2 concentration (aCO(2)) are closely related over the past 800 thousand years. However, the interpretation of their sequential, and hence the causal relationship has long been controversial. In this study, we revisit this long-standing scientific issue based on 88 well-dated high-resolution climate proxy records derived from ice cores, marine deposits, and stalagmites. We composite global and hemispheric stacks of the last deglacial climate index (DCI) using a normalization scheme instead of a more conventional area-weighting and mixing scheme to enable a better detection of temporal variations. Rampfit and Breakfit techniques are employed to detect the trend transitions in each composited DCI series and in the recently constructed centennial-scale aCO(2) over the period from 22 to 9 thousand years before present. We detect a clear lead of DCI change over aCO(2) variation on both global and hemispheric scales at the early stage of the deglaciation, suggesting that the variation of aCO(2) is an internal feedback in Earth's climate system rather than an initial trigger of the last deglacial warming. During the periods of the Bolling-Allerod and the Younger Dryas, the climate system appeared to have been constrained by a fast coupling mechanism between climate change and aCO(2) with no obvious asynchrony. The northern and southern hemispheric DCI stacks exhibit a seesawing pattern that can be linked to the influences of Atlantic meridional overturning circulation (AMOC) strength, revealing an important role of AMOC in regulating the global climate in the course of the last deglaciation

Rigid vortices in MgB2

Magnetic relaxation of high-pressure synthesized MgB$_2$ bulks with different thickness is investigated. It is found that the superconducting dia-magnetic moment depends on time in a logarithmic way; the flux-creep activation energy decreases linearly with the current density (as expected by Kim-Anderson model); and the activation energy increases linearly with the thickness of sample when it is thinner than about 1 mm. These features suggest that the vortices in the MgB$_2$ are rather rigid, and the pinning and creep can be well described by Kim-Anderson model.Comment: Typo corrected & reference adde

Building Program Vector Representations for Deep Learning

Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, which are the premise of deep learning for program analysis. Our representation learning approach directly makes deep learning a reality in this new field. We evaluate the learned vector representations both qualitatively and quantitatively. We conclude, based on the experiments, the coding criterion is successful in building program representations. To evaluate whether deep learning is beneficial for program analysis, we feed the representations to deep neural networks, and achieve higher accuracy in the program classification task than "shallow" methods, such as logistic regression and the support vector machine. This result confirms the feasibility of deep learning to analyze programs. It also gives primary evidence of its success in this new field. We believe deep learning will become an outstanding technique for program analysis in the near future.Comment: This paper was submitted to ICSE'1

Breakpoint lead-lag analysis of the last deglacial climate change andatmospheric CO2 concentration on global and hemispheric scales

Antarctic ice core records show that climate change and atmospheric CO2 concentration (aCO2) are closely related over the past 800 thousand years. However, the interpretation of their sequential, and hence the causal relationship has long been controversial. In this study, we revisit this long-standing scientific issue based on 88 well-dated high-resolution climate proxy records derived from ice cores, marine deposits, and stalagmites. We composite global and hemispheric stacks of the last deglacial climate index (DCI) using a normalization scheme instead of a more conventional area-weighting and mixing scheme to enable a better detection of temporal variations. Rampfit and Breakfit techniques are employed to detect the trend transitions in each composited DCI series and in the recently constructed centennial-scale aCO2 over the period from 22 to 9 thousand years before present. We detect a clear lead of DCI change over aCO2 variation on both global and hemispheric scales at the early stage of the deglaciation, suggesting that the variation of aCO2 is an internal feedback in Earth&#39;s climate system rather than an initial trigger of the last deglacial warming. During the periods of the B&oslash;lling-Aller&oslash;d and the Younger Dryas, the climate system appeared to have been constrained by a fast coupling mechanism between climate change and aCO2 with no obvious asynchrony. The northern and southern hemispheric DCI stacks exhibit a seesawing pattern that can be linked to the influences of Atlantic meridional overturning circulation (AMOC) strength, revealing an important role of AMOC in regulating the global climate in the course of the last deglaciation.<br /

Identification of a histone acetyltransferase as a novel regulator of Drosophila intestinal stem cells

AbstractOne of the major challenges in stem cell research is to decipher the controlling mechanisms/genes of stem cell homeostasis. Through an RNAi mediated genetic screen of living animals, we identified an evolutionarily conserved histone acetyltransferase Atac2 as a novel regulator of Drosophila intestinal stem cells (ISCs). Expression of Atac2-RNAi or a dominant negative allele of Atac2 generated more ISCs, while excessive Atac2 or a histone deacetylase inhibitor promoted ISC differentiation without affecting ISC survival or lineage specification. These findings extend our knowledge of epigenetic mechanisms in stem cell regulation