Modeling of the devolatilization kinetics during pyrolysis of grape residues

Thermo-gravimetric analysis (TGA) was performed on grape seeds, skins, stalks, marc, vine-branches, grape seed oil and grape seeds depleted of their oil. The TGA data was modeled through Gaussian, logistic and Miura-Maki distributed activation energy models (DAEMs) and a simpler two-parameter model. All DAEMs allowed an accurate prediction of the TGA data; however, the Miura-Maki model could not account for the complete range of conversion for some substrates, while the Gaussian and logistic DAEMs suffered from the interrelation between the pre-exponential factor k₀ and the mean activation energy E₀ - an obstacle that can be overcome by fixing the value of k₀a priori. The results confirmed the capabilities of DAEMs but also highlighted some drawbacks in their application to certain thermodegradation experimental data.     

Photophysics of ANS. IV. Electron transfer quenching of ANS in alcoholic solvents and mixtures

ANS is observed to decay from the fluorescent state with distributed kinetics in nearly pure ethanol solvent, notwithstanding that in mixed ethanol/water solvents the decay is discrete and biexponential. The origin of this behavior is investigated. In particular, a theory of electron transfer theory in the adiabatic regime is adduced, with specific involvement of solvent cage structure in the form of the solvent-electron polaron wave function. Properties of various polarons for various solvent systems are predicted and, for the case of ethanol and cyclohexanol, employed to generate the observed Arrhenius-type decay parameters in a quantitative fashion.     

APP: an Automated Proteomics Pipeline for the analysis of mass spectrometry data based on multiple open access tools

Background

Mass spectrometry analyses of complex protein samples yield large amounts of data and specific expertise is needed for data analysis, in addition to a dedicated computer infrastructure. Furthermore, the identification of proteins and their specific properties require the use of multiple independent bioinformatics tools and several database search algorithms to process the same datasets. In order to facilitate and increase the speed of data analysis, there is a need for an integrated platform that would allow a comprehensive profiling of thousands of peptides and proteins in a single process through the simultaneous exploitation of multiple complementary algorithms.

Results

We have established a new proteomics pipeline designated as APP that fulfills these objectives using a complete series of tools freely available from open sources. APP automates the processing of proteomics tasks such as peptide identification, validation and quantitation from LC-MS/MS data and allows easy integration of many separate proteomics tools. Distributed processing is at the core of APP, allowing the processing of very large datasets using any combination of Windows/Linux physical or virtual computing resources.

Conclusions

APP provides distributed computing nodes that are simple to set up, greatly relieving the need for separate IT competence when handling large datasets. The modular nature of APP allows complex workflows to be managed and distributed, speeding up throughput and setup. Additionally, APP logs execution information on all executed tasks and generated results, simplifying information management and validation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0441-8) contains supplementary material, which is available to authorized users.     

Analysis of the genetic diversity of garlic (Allium sativum L.) by simple sequence repeat and inter simple sequence repeat analysis and agro-morphological traits

The genetic diversity of 39 garlic accessions was investigated using eight simple sequence repeat (SSR) primer combinations and 17 inter-simple sequence repeat (ISSR) primer combinations. A total of 109 polymorphic loci were detected among these accessions, with an average of 4.63 polymorphic loci per SSR primer combination and 4.29 polymorphic loci per ISSR primer combination. The mean effective number of alleles, the mean Nei's genetic diversity, and the mean Shannon's information index for SSR were 1.4799, 0.2870, and 0.4378, respectively; and those for ISSR were 1.4847, 0.2898 and 0.4415, respectively. Cluster analysis, using the unweighted pair-group method with arithmetic averages (UPGMA) based on the allele frequency data, classified the accessions into three groups. The results of principal component analysis (PCA) were consistent with those of the cluster analysis. PCA showed that each of these three groups exhibited significant variation in agro-morphological traits. These findings suggest that the eight SSR and 17 ISSR primers identified could define valuable markers for genetic diversity for use by plant breeders.     

Discovering likely invariants of distributed transaction systems for autonomic system management

Large amount of monitoring data can be collected from distributed systems as the observables to analyze system behaviors. However, without reasonable models to characterize systems, we can hardly interpret such monitoring data effectively for system management. In this paper, a new concept named flow intensity is introduced to measure the intensity with which internal monitoring data reacts to the volume of user requests in distributed transaction systems. We propose a novel approach to automatically model and search relationships between the flow intensities measured at various points across the system. If the modeled relationships hold all the time, they are regarded as invariants of the underlying system. Experimental results from a real system demonstrate that such invariants widely exist in distributed transaction systems. Further we discuss how such invariants can be used to characterize complex systems and support autonomic system management. Guofei Jiang received the B.S. and Ph.D. degrees in electrical and computer engineering from Beijing Institute of Technology, China, in 1993 and 1998, respectively. During 1998–2000, he was a postdoctoral fellow in computer engineering at Dartmouth College, NH. He is currently a research staff member with the Robust and Secure Systems Group in NEC Laboratories America at Princeton, NJ. During 2000–2004, he was a research scientist in the Institute for Security Technology Studies at Dartmouth College. His current research focus is on distributed system, dependable and secure computing, system and information theory. He has published over 50 technical papers in these areas. He is an associate editor of IEEE Security and Privacy magazine and has served in the program committees of many conferences. Haifeng Chen received the BEng and MEng degrees, both in automation, from Southeast University, China, in 1994 and 1997 respectively, and the PhD degree in computer engineering from Rutgers University, New Jersey, in 2004. He has worked as a researcher in the Chinese national research institute of power automation. He is currently a research staff member at NEC laboratory America, Princeton, NJ. His research interests include data mining, autonomic computing, pattern recognition and robust statistics. Kenji Yoshihira received the B.E. in EE at University of Tokyo in 1996 and designed processor chips for enterprise computer at Hitachi Ltd. for five years. He employed himself in CTO at Investoria Inc. in Japan to develop an Internet service system for financial information distribution through 2002 and received the M.S. in CS at New York University in 2004. He is currently a research staff member with the Robust and Secure Systems Group in NEC Laboratories America, inc. in NJ. His current research focus is on distributed system and autonomic computing.     

Distributed shared arrays: A distributed virtual machine with mobility support for reconfiguration

Distributed Shared Arrays (DSA) is a distributed virtual machine that supports Java-compliant multithreaded programming with mobility support for system reconfiguration in distributed environments. The DSA programming model allows programmers to explicitly control data distribution so as to take advantage of the deep memory hierarchy, while relieving them from error-prone orchestration of communication and synchronization at run-time. The DSA system is developed as an integral component of mobility support middleware for Grid computing so that DSA-based virtual machines can be reconfigured to adapt to the varying resource supplies or demand over the course of a computation. The DSA runtime system also features a directory-based cache coherence protocol in support of replication of user-defined sharing granularity and a communication proxy mechanism for reducing network contention. System reconfiguration is achieved by a DSA service migration mechanism, which moves the DSA service and residing computational agents between physical servers for load balancing and fault resilience. We demonstrate the programmability of the model in a number of parallel applications and evaluate its performance by application benchmark programs, in particular, the impact of the coherence granularity and service migration overhead. Song Fu received the BS degreee in computer science from Nanjing University of Aeronautics and Astronautics, China, in 1999, and the MS degree in computer science from Nanjing University, China, in 2002. He is currently a PhD candidate in computer engineering at Wayne State University. His research interests include the resource management, security, and mobility issues in wide-area distributed systems. Cheng-Zhong Xu received the BS and MS degrees in computer science from Nanjing University in 1986 and 1989, respectively, and the Ph.D. degree in computer science from the University of Hong Kong in 1993. He is an Associate Professor in the Department of Electrical and Computer Engineer of Wayne State University. His research interests lie in distributed are in distributed and parallel systems, particularly in resource management for high performance cluster and grid computing and scalable and secure Internet services. He has published more than100 peer-reviewed articles in journals and conference proceedings in these areas. He is the author of the book Scalable and Secure Internet Services and Architecture (CRC Press, 2005) and a co-author of the book Load Balancing in Parallel Computers: Theory and Practice (Kluwer Academic, 1997). He serves on the editorial boards of J. of Parallel and Distributed Computing, J. of Parallel, Emergent, and Distributed Systems, J. of High Performance Computing and Networking, and J. of Computers and Applications. He was the founding program co-chair of International Workshop on Security in Systems and Networks (SSN), the general co-chair of the IFIP 2006 International Conference on Embedded and Ubiquitous Computing (EUC06), and a member of the program committees of numerous conferences. His research was supported in part by the US National Science Foundation, NASA, and Cray Research. He is a recipient of the Faculty Research Award of Wayne State University in 2000, the Presidents Award for Excellence in Teaching in 2002, and the Career Development Chair Award in 2003. He is a senior member of the IEEE. Brian A. Wims was born in Washington, DC in 1967. He received the Bachelor of Science in Electrical Engineering from GMI-EMI (now called Kettering University) in 1990; and Master of Science in Computer Engineering from Wayne State University in 1999. His research interests are primarily in the fields of parallel and distributed systems with applications in Mobile Agent technologies. From 1990–2001 he worked in various Engineering positions in General Motors, including Electrical Analysis, Software Design, and Test and Development. In 2001, he joined the General Motors IS&S department where he is currently a Project Manager in the Computer Aided Test group. Responsibilities include managing the development of test automation applications in the Electrical, EMC, and Safety Labs. Ramzi Basharahil was born in Aden, Yemen in 1972. He received the Bachelor of Science degree in Electrical Engineering from the United Arab Emirates University. He graduated top of his engineering graduated class of 1997. He obtained Master of Science degree in 2001 from Wayne State University in the Department of Electrical and Computer Engineering. His main research interests are primarily in the fields of parallel and distributed systems with applications to distributed processing across cluster of servers. From 1997 to 1998, he worked as a Teaching Assistant in the Department of Electrical Engineering at the UAE University. In 2000, he joined Internet Security Systems as a security software engineer. He later joined NetIQ Corporation in 2002 and still working since then. He is leading the security events trending and events management software development where he is involved in designing and the implementing event/log managements products.     

Global dynamics of a chemostat competition model with distributed delay

 We study the global dynamics of n-species competition in a chemostat with distributed delay describing the time-lag involved in the conversion of nutrient to viable biomass. The delay phenomenon is modelled by the gamma distribution. The linear chain trick and a fluctuation lemma are applied to obtain the global limiting behavior of the model. When each population can survive if it is cultured alone, we prove that at most one competitor survives. The winner is the population that has the smallest delayed break-even concentration, provided that the orders of the delay kernels are large and the mean delays modified to include the washout rate (which we call the virtual mean delays) are bounded and close to each other, or the delay kernels modified to include the washout factor (which we call the virtual delay kernels) are close in L ¹-norm. Also, when the virtual mean delays are relatively small, it is shown that the predictions of the distributed delay model are identical with the predictions of the corresponding ODEs model without delay. However, since the delayed break-even concentrations are functions of the parameters appearing in the delay kernels, if the delays are sufficiently large, the prediction of which competitor survives, given by the ODEs model, can differ from that given by the delay model. Received: 9 August 1997 / Revised version: 2 July 1998     

Path formation in a robot swarm

We present two swarm intelligence control mechanisms used for distributed robot path formation. In the first, the robots form linear chains. We study three variants of robot chains, which vary in the degree of motion allowed to the chain structure. The second mechanism is called vectorfield. In this case, the robots form a pattern that globally indicates the direction towards a goal or home location. We test each controller on a task that consists in forming a path between two objects which an individual robot cannot perceive simultaneously. Our simulation experiments show promising results. All the controllers are able to form paths in complex obstacle environments and exhibit very good scalability, robustness, and fault tolerance characteristics. Additionally, we observe that chains perform better for small robot group sizes, while vectorfield performs better for large groups.