Dynamic service deployment in a distributed heterogeneous cluster based router (DHCR)

This paper presents the design, implementation and evaluation of an extensible, scalable and distributed heterogeneous cluster based programmable router, called DHCR (Distributed Heterogeneous Cluster based Router), capable of supporting and deploying network services at run time. DHCR is a software IP router relying on heterogeneous cluster composed of separated computers with different hardware and software architecture capabilities, running different operating systems and interconnected through a high speed network connection. The DHCR ensures dynamic deployment of services and distributed control of router components (forwarding and routing elements) over heterogeneous system environments. The DHCR combines the IETF ForCES (Forwarding and Control Element Separation) architecture with software component technologies to meet the requirements of the next generation software routers. To ensure reliable and transparent communication between separated, decentralized and heterogeneous router components, the CORBA based middleware technology is used to support the DHCR internal communication. The paper also explores the use of the CORBA Component Model (CCM) to design and implement a modular, distributed and heterogeneous forwarding path for the DHCR router architecture. The CCM based forwarding plane ensures dynamic reconfiguration of the data path topology needed for low-level service deployment. Results on achievable performance using the proposed DHCR router are reported.

Owner controlled data exchange in nutrigenomic collaborations: the NuGO information network

New ‘omics’ technologies are changing nutritional sciences research. They enable to tackle increasingly complex questions but also increase the need for collaboration between research groups. An important challenge for successful collaboration is the management and structured exchange of information that accompanies data-intense technologies. NuGO, the European Nutrigenomics Organization, the major collaborating network in molecular nutritional sciences, is supporting the application of modern information technologies in this area. We have developed and implemented a concept for data management and computing infrastructure that supports collaboration between nutrigenomics researchers. The system fills the gap between “private” storing with occasional file sharing by email and the use of centralized databases. It provides flexible tools to share data, also during experiments, while preserving ownership. The NuGO Information Network is a decentral, distributed system for data exchange based on standard web technology. Secure access to data, maintained by the individual researcher, is enabled by web services based on the the BioMoby framework. A central directory provides information about available web services. The flexibility of the infrastructure allows a wide variety of services for data processing and integration by combining several web services, including public services. Therefore, this integrated information system is suited for other research collaborations.     

Applications Of Dl_poly And Dl_multi To Organic Molecular Crystals

Molecular dynamics (MD) simulations are capable of giving considerable insight into the polymorphism of organic molecules, a problem of major concern to the pharmaceutical and other speciality chemicals industries. We illustrate some of the challenges involved in small organic systems, which have complex solid-state phase behaviour, including characterizing rotationally disordered phases, modelling polymorphs with very different hydrogen bonding motifs and explaining the solvent dependence of a polymorphic system. Simulating the dynamics within the organic solid state can be very demanding of the model for the weak forces between the molecules. This has led to the development of DL_MULTI so that a distributed multipole electrostatic model can be used to describe the orientation dependence of hydrogen bonding and π–π stacking more realistically. Once a simulation is correctly reproducing the known crystal structures, there are also considerable system-specific challenges in extracting novel insights from the MD simulations.     

Polymorphism of BMP4 gene in Indian goat breeds differing in prolificacy

Bone morphogenetic proteins (BMPs) are members of the TGF-β (transforming growth factor-beta) superfamily, of which BMP4 is the most important due to its crucial role in follicular growth and differentiation, cumulus expansion and ovulation. Reproduction is a crucial trait in goat breeding and based on the important role of BMP4 gene in reproduction it was considered as a possible candidate gene for the prolificacy of goats. The objective of the present study was to detect polymorphism in intronic, exonic and 3′ un-translated regions of BMP4 gene in Indian goats. Nine different goat breeds (Barbari, Beetal, Black Bengal, Malabari, Jakhrana (Twinning > 40%), Osmanabadi, Sangamneri (Twinning 20–30%), Sirohi and Ganjam (Twinning < 10%)) differing in prolificacy and geographic distribution were employed for polymorphism scanning. Cattle sequence (AC_000167.1) was used to design primers for the amplification of a targeted region followed by direct DNA sequencing to identify the genetic variations. Single nucleotide polymorphisms (SNPs) were not detected in exon 3, the intronic region and the 3′ flanking region. A SNP (G1534A) was identified in exon 2. It was a non-synonymous mutation resulting in an arginine to lysine change in a corresponding protein sequence. G to A transition at the 1534 locus revealed two genotypes GG and GA in the nine investigated goat breeds. The GG genotype was predominant with a genotype frequency of 0.98. The GA genotype was present in the Black Bengal as well as Jakhrana breed with a genotype frequency of 0.02. A microsatellite was identified in the 3′ flanking region, only 20 nucleotides downstream from the termination site of the coding region, as a short sequence with more than nineteen continuous and repeated CA dinucleotides. Since the gene is highly evolutionarily conserved, identification of a non-synonymous SNP (G1534A) in the coding region gains further importance. To our knowledge, this is the first report of a mutation in the coding region of the caprine BMP4 gene. But whether the reproduction trait of goat is associated with the BMP4 polymorphism, needs to be further defined by association studies in more populations so as to delineate an effect on it.     

CRISPys: Optimal sgRNA Design for Editing Multiple Members of a Gene Family Using the CRISPR System

The development of the CRISPR–Cas9 system in recent years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simple and effective task. The system is directed to a genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with it, subsequently leading to site-specific modifications. However, many gene families in eukaryotic genomes exhibit partially overlapping functions, and thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR–Cas9 system, which may lead to the modification of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. We introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the efficiency to edit the induced targets is maximized. We suggest several approaches for designing the optimal individual sgRNA and an approach to compute the optimal set of sgRNAs for cases when the experimental platform allows for more than one. The latter may optionally account for the homologous relationships among gene-family members. We further show that CRISPys outperforms simpler alignment-based techniques by in silico examination over all gene families in the Solanum lycopersicum genome.     

Epidemiological Models with Non-Exponentially Distributed Disease Stages and Applications to Disease Control

SEIR epidemiological models with the inclusion of quarantine and isolation are used to study the control and intervention of infectious diseases. A simple ordinary differential equation (ODE) model that assumes exponential distribution for the latent and infectious stages is shown to be inadequate for assessing disease control strategies. By assuming arbitrarily distributed disease stages, a general integral equation model is developed, of which the simple ODE model is a special case. Analysis of the general model shows that the qualitative disease dynamics are determined by the reproductive number , which is a function of control measures. The integral equation model is shown to reduce to an ODE model when the disease stages are assumed to have a gamma distribution, which is more realistic than the exponential distribution. Outcomes of these models are compared regarding the effectiveness of various intervention policies. Numerical simulations suggest that models that assume exponential and non-exponential stage distribution assumptions can produce inconsistent predictions.     

Global stability results for a generalized Lotka-Volterra system with distributed delays

The paper contains an extension of the general ODE system proposed in previous papers by the same authors, to include distributed time delays in the interaction terms. The new system describes a large class of Lotka-Volterra like population models and epidemic models with continuous time delays. Sufficient conditions for the boundedness of solutions and for the global asymptotic stability of nontrivial equilibrium solutions are given. A detailed analysis of the epidemic system is given with respect to the conditions for global stability. For a relevant subclass of these systems an existence criterion for steady states is also given.Work supported by the Special Program Control of Infectious Diseases, C.N.R. and by the M.P.I., Italy     

On the role of long incubation periods in the dynamics of acquired immunodeficiency syndrome (AIDS)

In this study, we investigate systematically the role played by the reproductive number (the number of secondary infections generated by an infectious individual in a population of susceptibles) on single group populations models of the spread of HIV/AIDS. Our results for a single group model show that if R 1, the disease will die out, and strongly suggest that if R > 1 the disease will persist regardless of initial conditions. Our extensive (but incomplete) mathematical analysis and the numerical simulations of various research groups support the conclusion that the reproductive number R is a global bifurcation parameter. The bifurcation that takes place as R is varied is a transcritical bifurcation; in other words, when R crosses 1 there is a global transfer of stability from the infection-free state to the endemic equilibrium, and vice versa. These results do not depend on the distribution of times spent in the infectious categories (the survivorship functions). Furthermore, by keeping all the key statistics fixed, we can compare two extremes: exponential survivorship versus piecewise constant survivorship (individuals remain infectious for a fixed length of time). By choosing some realistic parameters we can see (at least in these cases) that the reproductive numbers corresponding to these two extreme cases do not differ significantly whenever the two distributions have the same mean. At any rate a formula is provided that allows us to estimate the role played by the survivorship function (and hence the incubation period) in the global dynamics of HIV. These results support the conclusion that single population models of this type are robust and hence are good building blocks for the construction of multiple group models. Our understanding of the dynamics of HIV in the context of mathematical models for multiple groups is critical to our understanding of the dynamics of HIV in a highly heterogeneous population.     

Distributed algorithms for partially clairvoyant dispatchers

Real-time systems are increasingly appearing in complex and dynamic environments such as cruise controllers, life support systems and nuclear reactors. These systems contain components that sense, control and stabilize the environment towards achieving the mission or target. These consociate components synchronize, compute and control themselves locally or have a centralized component to achieve their mission. Distributed computing techniques improve the overall performance and reliability of large real-time systems with spread components. Partially Clairvoyant scheduling was introduced in Saksena, M., PhD thesis (1994) to determine the schedulability of hard real-time jobs with variable execution times. The problem of deciding the Partially Clairvoyant schedulability of a constrained set of jobs was well studied in Gerber, R., et al., IEEE Trans. Comput. 44(3), 471–479 (1995), Choi, S. and Agrawala, A.K., Real-Time Syst. 19(1), 5–40 (2000), Subramani, K., J. Math. Model. Algorithms 2(2), 97–119 (2003). These algorithms determine the schedulability of a job-set offline and produce a set of dispatch functions for each job in the job-set. The dispatch functions of a job depend on the start and execution times of the jobs sequenced before the job. The dispatching problem is concerned with the online computation of the start time interval of a job such that none of the constraints are violated. In certain situations, the dispatcher fails to dispatch a job as it takes longer to compute the interval within which the job has to be dispatched, this phenomenon is called Loss of Dispatchability. For a job-set of size n, sequential approaches using function lists suffer from two major drawbacks, viz., Ω(n) dispatching time and the Loss of Dispatchability phenomenon. Existing approaches to this problem have been along sequential lines, through the use of stored function lists. In this paper, we propose and evaluate three distributed dispatching algorithms for Partially Clairvoyant schedules. For a job-set of size n, the algorithms have dispatch times of O(1) per job. In the first algorithm, one processor executes all the jobs and other processors compute the dispatch functions. This scenario simplifies design and is better in situations where one processor controls all other devices. In the other algorithms, all the processors execute jobs pre-assigned to them and compute the dispatch functions; which is a plausible scenario in distributed controlling.

Robust stability of genetic regulatory networks with distributed delay

This paper investigates robust stability of genetic regulatory networks with distributed delay. Different from other papers, distributed delay is induced. It says that the concentration of macromolecule depends on an integral of the regulatory function of over a specified range of previous time, which is more realistic. Based on Lyapunov stability theory and linear matrix inequality (LMI), sufficient conditions for genetic regulatory networks to be global asymptotic stability and robust stability are derived in terms of LMI. Two numerical examples are given to illustrate the effectiveness of our theoretical results.