Mechanisms of antagonism of Pseudomonas fluorescens EPS62e against Erwinia amylovora, the causal agent of fire blight

Pseudomonas fluorescens EPS62e was selected during a screening procedure for its high efficacy in controlling infections by Erwinia amylovora, the causal agent of fire blight disease, on different plant materials. In field trials carried out in pear trees during bloom, EPS62e colonized flowers until the carrying capacity, providing a moderate efficacy of fire-blight control. The putative mechanisms of EPS62e antagonism against E. amylovora were studied. EPS62e did not produce antimicrobial compounds described in P. fluorescens species and only developed antagonism in King’s B medium, where it produced siderophores. Interaction experiments in culture plate wells including a membrane filter, which physically separated the cultures, confirmed that inhibition of E. amylovora requires cell-to-cell contact. The spectrum of nutrient assimilation indicated that EPS62e used significantly more or different carbon sources than the pathogen. The maximum growth rate and affinity for nutrients in immature fruit extract were higher in EPS62e than in E. amylovora, but the cell yield was similar. The fitness of EPS62e and E. amylovora was studied upon inoculation in immature pear fruit wounds and hypanthia of intact flowers under controlled-environment conditions. When inoculated separately, EPS62e grew faster in flowers, whereas E. amylovora grew faster in fruit wounds because of its rapid spread to adjacent tissues. However, in preventive inoculations of EPS62e, subsequent growth of EPS101 was significantly inhibited. It is concluded that cell-to-cell interference as well as differences in growth potential and the spectrum and efficiency of nutrient use are mechanisms of antagonism of EPS62e against E. amylovora

Charge transfer in DNA: hole charge is confined to a single base pair due to solvation effects

We include solvation effects in tight-binding Hamiltonians for hole states in DNA. The corresponding linear-response parameters are derived from accurate estimates of solvation energy calculated for several hole charge distributions in DNA stacks. Two models are considered: (A) the correction to a diagonal Hamiltonian matrix element depends only on the charge localized on the corresponding site and (B) in addition to this term, the reaction field due to adjacent base pairs is accounted for. We show that both schemes give very similar results. The effects of the polar medium on the hole distribution in DNA are studied. We conclude that the effects of polar surroundings essentially suppress charge delocalization in DNA, and hole states in (GC)n sequences are localized on individual guanines

Generation of mouse-induced pluripotent stem cells by transient expression of a single nonviral polycistronic vector

Induced pluripotent stem (iPS) cells have generated keen interestdue to their potential use in regenerative medicine. They havebeen obtained from various cell types of both mice and humans byexogenous delivery of different combinations of Oct4, Sox2, Klf4,c-Myc, Nanog, and Lin28. The delivery of these transcription factorshas mostly entailed the use of integrating viral vectors (retrovirusesor lentiviruses), carrying the risk of both insertional mutagenesisand oncogenesis due to misexpression of these exogenousfactors. Therefore, obtaining iPS cells that do not carry integratedtransgene sequences is an important prerequisite for their eventualtherapeutic use. Here we report the generation of iPS cell linesfrom mouse embryonic fibroblasts with no evidence of integrationof the reprogramming vector in their genome, achieved by nucleofectionof a polycistronic construct coexpressing Oct4, Sox2, Klf4,and c-Myc

Design and evaluation of a panel os single-nucleotide polymorphisms in microRNA genomic regions for association studies in human disease

MicroRNAs (miRNA) are recognized posttranscriptional gene repressors involved in the control of almost every biological process. Allelic variants in these regions may be an important source of phenotypic diversity and contribute to disease susceptibility. We analyzed the genomic organization of 325 human miRNAs (release 7.1, miRBase) to construct a panel of 768 single-nucleotide polymorphisms (SNPs) covering approximately 1 Mb of genomic DNA, including 131 isolated miRNAs (40%) and 194 miRNAs arranged in 48 miRNA clusters, as well as their 5-kb flanking regions. Of these miRNAs, 37% were inside known protein-coding genes, which were significantly associated with biological functions regarding neurological, psychological or nutritional disorders. SNP coverage analysis revealed a lower SNP density in miRNAs compared with the average of the genome, with only 24 SNPs located in the 325 miRNAs studied. Further genotyping of 340 unrelated Spanish individuals showed that more than half of the SNPs in miRNAs were either rare or monomorphic, in agreement with the reported selective constraint on human miRNAs. A comparison of the minor allele frequencies between Spanish and HapMap population samples confirmed the applicability of this SNP panel to the study of complex disorders among the Spanish population, and revealed two miRNA regions, hsa-mir-26a-2 in the CTDSP2 gene and hsa-mir-128-1 in the R3HDM1 gene, showing geographical allelic frequency variation among the four HapMap populations, probably because of differences in natural selection. The designed miRNA SNP panel could help to identify still hidden links between miRNAs and human disease.

Capacity-achieving input covariance for single-user multi-antenna channels

We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

Goal recognition over POMDPs: inferring the intention of a POMDP agent

Plan recognition is the problem of inferring the goals and plans of an agent from partial observations of her behavior. Recently, it has been shown that the problem can be formulated and solved usingplanners, reducing plan recognition to plan generation.In this work, we extend this model-basedapproach to plan recognition to the POMDP setting, where actions are stochastic and states are partially observable. The task is to infer a probability distribution over the possible goals of an agent whose behavior results from a POMDP model. The POMDP model is shared between agent and observer except for the true goal of the agent that is hidden to the observer. The observations are action sequences O that may contain gaps as some or even most of the actions done by the agent may not be observed. We show that the posterior goal distribution P(GjO) can be computed from the value function VG(b) over beliefs b generated by the POMDPplanner for each possible goal G. Some extensionsof the basic framework are discussed, and a numberof experiments are reported.

Efficient interval scoring rules

Scoring rules that elicit an entire belief distribution through the elicitation of point beliefsare time-consuming and demand considerable cognitive e¤ort. Moreover, the results are validonly when agents are risk-neutral or when one uses probabilistic rules. We investigate a classof rules in which the agent has to choose an interval and is rewarded (deterministically) onthe basis of the chosen interval and the realization of the random variable. We formulatean e¢ ciency criterion for such rules and present a speci.c interval scoring rule. For single-peaked beliefs, our rule gives information about both the location and the dispersion of thebelief distribution. These results hold for all concave utility functions.

Beyond Smith's rule: An optimal dynamic index, rule for single machine stochastic scheduling with convex holding costs

Most research on single machine scheduling has assumedthe linearity of job holding costs, which is arguablynot appropriate in some applications. This motivates ourstudy of a model for scheduling $n$ classes of stochasticjobs on a single machine, with the objective of minimizingthe total expected holding cost (discounted or undiscounted). We allow general holding cost rates that are separable,nondecreasing and convex on the number of jobs in eachclass. We formulate the problem as a linear program overa certain greedoid polytope, and establish that it issolved optimally by a dynamic (priority) index rule,whichextends the classical Smith's rule (1956) for the linearcase. Unlike Smith's indices, defined for each class, ournew indices are defined for each extended class, consistingof a class and a number of jobs in that class, and yieldan optimal dynamic index rule: work at each time on a jobwhose current extended class has larger index. We furthershow that the indices possess a decomposition property,as they are computed separately for each class, andinterpret them in economic terms as marginal expected cost rate reductions per unit of expected processing time.We establish the results by deploying a methodology recentlyintroduced by us [J. Niño-Mora (1999). "Restless bandits,partial conservation laws, and indexability. "Forthcomingin Advances in Applied Probability Vol. 33 No. 1, 2001],based on the satisfaction by performance measures of partialconservation laws (PCL) (which extend the generalizedconservation laws of Bertsimas and Niño-Mora (1996)):PCL provide a polyhedral framework for establishing theoptimality of index policies with special structure inscheduling problems under admissible objectives, which weapply to the model of concern.

Social security, retirement, and the single-mindedness of the electorate

We propose a positive theory that is consistent with two important featuresof social security programs around the world: (1) they redistributeincome from young to old and (2) they induce retirement. We construct avoting model that includes a political campaign or debate prior to theelection. The model incorporates single-mindedness of the groups that donot work: while the workers divide their political capital between their age concerns and occupational concerns , the retired concentrate alltheir political capital to support their age group. In our model, theelderly end up getting transfers from the government (paid by the young)and distortionary labor income taxes induce the retirement of the elderly.In addition, our model predicts that occupational groups that work morewill tend to have more political power. The opposite is true fornon-occupational groups (such as the elderly). We provide some evidencethat supports these additional predictions.

Relying on the agent in charge of production for project evaluation

I study the optimal project choice when the principal relies on the agent in charge of production for project evaluation. The principal has to choose between a safe project generating a fixed revenue and a risky project generating an uncertain revenue. The agent has private information about the production cost under each project but also about the signal regarding the profitability of the risky project. If the signal favoring the adoption of the risky project is goods news to the agent, integrating production and project evaluation tasks does not generate any loss compared to the benchmark in which the principal herself receives the signal. By contrast, if it is bad news, task integration creates an endogenous reservation utility which is type-dependent and thereby generates countervailing incentives, which can make a bias toward either project optimal. Our results can offer an explanation for why good firms can go bad and a rationale for the separation of day-to-day operating decisions from long-term strategic decisions stressed by Williamson.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Monetary unions and the transaction cost savings of a single currency

This paper studies the transaction cost savings of moving froma multi-currency exchange system to a single currency one. Theanalysis concentrates exclusively on the transaction andprecautionary demand for money and abstracts from any othermotives to hold currency. A continuous-time, stochastic Baumol-like model similar to that in Frenkel and Jovanovic (1980) isgeneralized to include several currencies and calibrated to fitEuropean data. The analysis implies an upper bound for thesavings associated with reductions of transaction costs derivedfrom the European Monetary Union of approximately 0.6\% of theCommunity GDP. Additionally, the magnitudes of the brokeragefee and the volatility of transactions, whose estimation hastraditionally been difficult to address empirically, areapproximated for Europe.

The gain-loss asymmetry and single-self preferences

Kahneman and Tversky asserted a fundamental asymmetry between gains and losses, namely a reflection effect which occurs when an individual prefers a sure gain of $ pz to anuncertain gain of $ z with probability p, while preferring an uncertain loss of $z with probability p to a certain loss of $ pz.We focus on this class of choices (actuarially fair), and explore the extent to which thereflection effect, understood as occurring at a range of wealth levels, is compatible with single-self preferences.We decompose the reflection effect into two components, a probability switch effect,which is compatible with single-self preferences, and a translation effect, which is not. To argue the first point, we analyze two classes of single-self, nonexpected utility preferences, which we label homothetic and weakly homothetic. In both cases, we characterize the switch effect as well as the dependence of risk attitudes on wealth.We also discuss two types of utility functions of a form reminiscent of expected utility but with distorted probabilities. Type I always distorts the probability of the worst outcome downwards, yielding attraction to small risks for all probabilities. Type II distorts low probabilities upwards, and high probabilities downwards, implying risk aversion when the probability of the worst outcome is low. By combining homothetic or weak homothetic preferences with Type I or Type II distortion functions, we present four explicit examples: All four display a switch effect and, hence, a form of reflection effect consistent a single self preferences.

Are agent-based simulations robust? The wholesale electricity trading case

Agent-based computational economics is becoming widely used in practice. This paperexplores the consistency of some of its standard techniques. We focus in particular on prevailingwholesale electricity trading simulation methods. We include different supply and demandrepresentations and propose the Experience-Weighted Attractions method to include severalbehavioural algorithms. We compare the results across assumptions and to economic theorypredictions. The match is good under best-response and reinforcement learning but not underfictitious play. The simulations perform well under flat and upward-slopping supply bidding,and also for plausible demand elasticity assumptions. Learning is influenced by the number ofbids per plant and the initial conditions. The overall conclusion is that agent-based simulationassumptions are far from innocuous. We link their performance to underlying features, andidentify those that are better suited to model wholesale electricity markets.

Solving heterogeneous-agent models by projection and perturbation

The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.