A Scalable Middleware Solution for Advanced Wide Area Web Services

To alleviate scalability problems in the Web, many researchers concentrate on how to incorporate advanced caching and replication techniques. Many solutions incorporate object-based techniques. In particular, Web resources are considered as distributed objects offering a well-defined interface. We argue that most proposals ignore two important aspects. First, there is little discussion on what kind of coherence should be provided. Proposing specific caching or replication solutions makes sense only if we know what coherence model they should implement. Second, most proposals treat all Web resources alike. Such a one-size-fits-all approach will never work in a wide-area system. We propose a solution in which Web resources are encapsulated in physically distributed shared objects. Each object should encapsulate not only state and operations, but also the policy by which its state is distributed, cached, replicated, migrated, etc

Hysteresis and Avalanches in the Random Anisotropy Ising Model

The behaviour of the Random Anisotropy Ising model at T=0 under local relaxation dynamics is studied. The model includes a dominant ferromagnetic interaction and assumes an infinite anisotropy at each site along local anisotropy axes which are randomly aligned. Two different random distributions of anisotropy axes have been studied. Both are characterized by a parameter that allows control of the degree of disorder in the system. By using numerical simulations we analyze the hysteresis loop properties and characterize the statistical distribution of avalanches occuring during the metastable evolution of the system driven by an external field. A disorder-induced critical point is found in which the hysteresis loop changes from displaying a typical ferromagnetic magnetization jump to a rather smooth loop exhibiting only tiny avalanches. The critical point is characterized by a set of critical exponents, which are consistent with the universal values proposed from the study of other simpler models.Comment: 40 pages, 21 figures, Accepted for publication in Phys. Rev.

Low-energy excitations in the three-dimensional random-field Ising model

The random-field Ising model (RFIM), one of the basic models for quenched disorder, can be studied numerically with the help of efficient ground-state algorithms. In this study, we extend these algorithm by various methods in order to analyze low-energy excitations for the three-dimensional RFIM with Gaussian distributed disorder that appear in the form of clusters of connected spins. We analyze several properties of these clusters. Our results support the validity of the droplet-model description for the RFIM.Comment: 10 pages, 9 figure

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

Scaling properties of driven interfaces in disordered media

We perform a systematic study of several models that have been proposed for the purpose of understanding the motion of driven interfaces in disordered media. We identify two distinct universality classes: (i) One of these, referred to as directed percolation depinning (DPD), can be described by a Langevin equation similar to the Kardar-Parisi-Zhang equation, but with quenched disorder. (ii) The other, referred to as quenched Edwards-Wilkinson (QEW), can be described by a Langevin equation similar to the Edwards-Wilkinson equation but with quenched disorder. We find that for the DPD universality class the coefficient $\lambda$ of the nonlinear term diverges at the depinning transition, while for the QEW universality class either $\lambda = 0$ or $\lambda \to 0$ as the depinning transition is approached. The identification of the two universality classes allows us to better understand many of the results previously obtained experimentally and numerically. However, we find that some results cannot be understood in terms of the exponents obtained for the two universality classes {\it at\/} the depinning transition. In order to understand these remaining disagreements, we investigate the scaling properties of models in each of the two universality classes {\it above\/} the depinning transition. For the DPD universality class, we find for the roughness exponent $\alpha_P = 0.63 \pm 0.03$ for the pinned phase, and $\alpha_M = 0.75 \pm 0.05$ for the moving phase. For the growth exponent, we find $\beta_P = 0.67 \pm 0.05$ for the pinned phase, and $\beta_M = 0.74 \pm 0.06$ for the moving phase. Furthermore, we find an anomalous scaling of the prefactor of the width on the driving force. A new exponent $\varphi_M = -0.12 \pm 0.06$, characterizing the scaling of this prefactor, is shown to relate the values of the roughnessComment: Latex manuscript, Revtex 3.0, 15 pages, and 15 figures also available via anonymous ftp from ftp://jhilad.bu.edu/pub/abms/ (128.197.42.52

A mouse-human phase 1 co-clinical trial of a protease-activated fluorescent probe for imaging cancer

Local recurrence is a common cause of treatment failure for patients with solid tumors. Intraoperative detection of microscopic residual cancer in the tumor bed could be used to decrease the risk of a positive surgical margin, reduce rates of reexcision, and tailor adjuvant therapy. We used a protease-activated fluorescent imaging probe, LUM015, to detect cancer in vivo in a mouse model of soft tissue sarcoma (STS) and ex vivo in a first-in-human phase 1 clinical trial. In mice, intravenous injection of LUM015 labeled tumor cells, and residual fluorescence within the tumor bed predicted local recurrence. In 15 patients with STS or breast cancer, intravenous injection of LUM015 before surgery was well tolerated. Imaging of resected human tissues showed that fluorescence from tumor was significantly higher than fluorescence from normal tissues. LUM015 biodistribution, pharmacokinetic profiles, and metabolism were similar in mouse and human subjects. Tissue concentrations of LUM015 and its metabolites, including fluorescently labeled lysine, demonstrated that LUM015 is selectively distributed to tumors where it is activated by proteases. Experiments in mice with a constitutively active PEGylated fluorescent imaging probe support a model where tumor-selective probe distribution is a determinant of increased fluorescence in cancer. These co-clinical studies suggest that the tumor specificity of protease-activated imaging probes, such as LUM015, is dependent on both biodistribution and enzyme activity. Our first-in-human data support future clinical trials of LUM015 and other protease-sensitive probes

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives