Ammonia synthesis enhanced by magnesium chloride absorption

Conversion to ammonia with Haber–Bosch catalysts can be increased above 95% by selective absorption of ammonia by MgCl₂. The maximum conversion depends on reaction and absorption equilibria. At very short times, the measured conversion rate is the same with and without absorption by the MgCl₂ salt; the overall rate constants are comparable to those in the literature. At larger times, conversion to ammonia can be over seven times greater with MgCl₂ than without. However, the overall rate constants can be over 10 times slower because they are controlled by ammonia diffusion in the solid salt. An approximate, pseudosteady state theory consistent with these results provides a strategy for improving the overall rate while keeping the conversion over 90%. For example, the absorption rates might be increased using smaller particles of absorbent on a porous inert absorbent support. The results provide part of the basis for designing small scale ammonia plants. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1364–1371, 2015     

Limits to the evolution of dispersal kernels under rapid fragmentation

Adaptive evolution of dispersal strategies is one mechanism by which species can respond to rapid environmental changes. However, under rapid anthropogenic fragmentation, the evolution of dispersal may be limited, and species may be unable to adequately adapt to fragmented landscapes. Here, we develop a spatially explicit model to investigate the evolution of dispersal kernels under various combinations of fragmentation dynamics and initial conditions. We also study the consequences of modelling an evolutionary process in which dispersal phenotypes continuously and gradually shift in phenotype space in a manner corresponding to a polygenic underlying genetic architecture. With rapid fragmentation rates, we observed the emergence of long-term transient states in which dispersal strategies are not well suited to fragmented landscapes. We also show that the extent and length of these transient states depend on the pre-fragmentation dispersal strategy of the species, as well as on the rate of the fragmentation process leading to the fragmented landscape. In an increasingly fragmented world, understanding the ability of populations to adapt, and the effects that rapid fragmentation has on the evolution of dispersal, is critical for an informed assessment of species viability in the Anthropocene.     

Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets

Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.     

Computing the fault tolerance of multi-agent deployment

A deployment of a multi-agent system on a network refers to the placement of one or more copies of each agent on network hosts, in such a manner that the memory constraints of each node are satisfied. Finding the deployment that is most likely to tolerate faults (i.e. have at least one copy of each agent functioning and in communication with other agents) is a challenge. In this paper, we address the problem of finding the probability of survival of a deployment (i.e. the probability that a deployment will tolerate faults), under the assumption that node failures are independent. We show that the problem of computing the survival probability of a deployment is at least NP-hard. Moreover, it is hard to approximate. We produce two algorithms to accurately compute the probability of survival of a deployment—these algorithms are expectedly exponential. We also produce five heuristic algorithms to estimate survival probabilities—these algorithms work in acceptable time frames. We report on a detailed set of experiments to determine the conditions under which some of these algorithms perform better than the others.     

The implementation of a 2-core, multi-threaded itanium family processor

The design of the high end server processor code named Montecito incorporated several ambitious goals requiring innovation. The most obvious being the incorporation of two legacy cores on-die and at the same time reducing power by 23%. This is an effective 325% increase in MIPS per watt which necessitated a holistic focus on power reduction and management. The next challenge in the implementation was to ensure robust and high frequency circuit operation in the 90-nm process generation which brings with it higher leakage and greater variability. Achieving this goal required new methodologies for design, a greatly improved and tunable clock system and a better understanding of our power grid behavior all of which required new circuits and capabilities. The final aspect of circuit design improvement involved the I/O design for our legacy multi-drop system bus. To properly feed the two high frequency cores with memory bandwidth we needed to ensure frequency headroom in the operation of the bus. This was achieved through several innovations in controllability and tuning of the I/O buffers which are discussed as well.     

Inhibition of expression of the lysine-rich 30 kDa surface antigen of Entamoeba dispar by the transcription of its antisense RNA

The gene coding for the 30 kDa lysine rich surface antigen (Ed-Ag) that is present on membrane surfaces of Entamoeba dispar trophozoites has been characterized. A specific monoclonal antibody MAb 318-28 prepared against this antigen reacts with all E. dispar strains tested, but not with any of the antigens of E. histolytica. In order to understand the function of this antigen, we constructed two plasmids, pEdA-9 and pEdA-Rev, in which the antigen-coding sequence was introduced into the pEhAct-Neo shuttle vector in the direct and opposite orientation, respectively. When E. dispar trophozoites were transfected with pEdA-9, only a slight increase was observed in the expression of the antigen. However, when E. dispar trophozoites were transfected with pEdA-Rev, the expression of the native 30 kDa antigen was significantly inhibited. This inhibition was proportional to the level of resistance of the E. dispar culture to the neomycin derivative G418. Cytopathic assays detected only a slight difference between untransfected, pEdA-9 transfected and pEdA-Rev transfected trophozoites.     

Fair attribution of functional contribution in artificial and biological networks

This letter presents the multi-perturbation Shapley value analysis (MSA), an axiomatic, scalable, and rigorous method for deducing causal function localization from multiple perturbations data. The MSA, based on fundamental concepts from game theory, accurately quantifies the contributions of network elements and their interactions, overcoming several shortcomings of previous function localization approaches. Its successful operation is demonstrated in both the analysis of a neurophysiological model and of reversible deactivation data. The MSA has a wide range of potential applications, including the analysis of reversible deactivation experiments, neuronal laser ablations, and transcranial magnetic stimulation "virtual lesions," as well as in providing insight into the inner workings of computational models of neurophysiological systems.