An Eclipse Modelling Framework Alternative to Meet the Models@Runtime Requirements

Models@Runtime aims at taming the complexity of software dynamic adaptation by pushing further the idea of reflection and considering the reflection layer as a first-class modeling space. A natural approach to Models@Runtime is to use MDE techniques, in particular those based on the Eclipse Modeling Framework. EMF provides facilities for building DSLs and tools based on a structured data model, with tight integration with the Eclipse IDE. EMF has rapidly become the defacto standard in the MDE community and has also been adopted for building Models@Runtime platforms. For example, Frascati (implementing the Service Component Architecture standard) uses EMF for the design and runtime tooling of its architecture description language. However, EMF has primarily been thought to support design-time activities. This paper highlights specific Models@Runtime requirements, discusses the benefits and limitations of EMF in this context, and presents an alternative implementation to meet these requirements

Wave-like patterns of plant phenology determine ungulate movement tactics

Animals exhibit a diversity of movement tactics [1]. Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called ‘‘green-wave surfing’’ [3–5]. Yet general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested an emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of greenup facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n = 1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine-tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology

The First 30 Years of Cryptographic Hash Functions and the NIST SHA-3 Competition

The first designs of cryptographic hash functions date back to the late 1970s; more proposals emerged in the 1980s. During the 1990s, the number of hash function designs grew very quickly, but for many of these proposals security flaws were identified. MD5 and SHA-1 were deployed in an ever increasing number of applications, resulting in the name "Swiss army knifes" of cryptography. In spite of the importance of hash functions, only limited effort was spent on studying their formal definitions and foundations. In 2004 Wang et al. perfected differential cryptanalysis to a point that finding collisions for MD5 became very easy; for SHA-1 a substantial reduction of the security margin was obtained. This breakthrough has resulted in a flurry of research, resulting in new constructions and a growing body of foundational research. NIST announced in November 2007 that it would organize the SHA-3 competition, with as goal to select a new hash function family by 2012. From the 64 candidates submitted by October 2008, 14 have made it to the second round. This paper presents a brief overview of the state of hash functions 30 years after their introduction; it also discusses the progress of the SHA-3 competition. © 2010 Springer-Verlag.status: publishe

Code based cryptography and steganography

Abstract. For a long time, coding theory was only concerned by message integrity (how to protect against errors a message sent via some noisely channel). Nowadays, coding theory plays an important role in the area of cryptography and steganography. The aim of this paper is to show how algebraic coding theory offers ways to define secure cryptographic primitives and efficient steganographic schemes. Cryptography

The Arabidopsis Nuclear Pore and Nuclear Envelope

The nuclear envelope is a double membrane structure that separates the eukaryotic cytoplasm from the nucleoplasm. The nuclear pores embedded in the nuclear envelope are the sole gateways for macromolecular trafficking in and out of the nucleus. The nuclear pore complexes assembled at the nuclear pores are large protein conglomerates composed of multiple units of about 30 different nucleoporins. Proteins and RNAs traffic through the nuclear pore complexes, enabled by the interacting activities of nuclear transport receptors, nucleoporins, and elements of the Ran GTPase cycle. In addition to directional and possibly selective protein and RNA nuclear import and export, the nuclear pore gains increasing prominence as a spatial organizer of cellular processes, such as sumoylation and desumoylation. Individual nucleoporins and whole nuclear pore subcomplexes traffic to specific mitotic locations and have mitotic functions, for example at the kinetochores, in spindle assembly, and in conjunction with the checkpoints. Mutants of nucleoporin genes and genes of nuclear transport components lead to a wide array of defects from human diseases to compromised plant defense responses. The nuclear envelope acts as a repository of calcium, and its inner membrane is populated by functionally unique proteins connected to both chromatin and—through the nuclear envelope lumen—the cytoplasmic cytoskeleton. Plant nuclear pore and nuclear envelope research—predominantly focusing on Arabidopsis as a model—is discovering both similarities and surprisingly unique aspects compared to the more mature model systems. This chapter gives an overview of our current knowledge in the field and of exciting areas awaiting further exploration