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10 páginas.- 4 figuras.- 4 tablas.- 45 referencias.- The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.2c03149, Recent research has demonstrated that chemotactic bacteria can disperse inside microsized pores while traveling toward favorable conditions. Microbe–microbe cotransport might enable nonmotile bacteria to be carried with motile partners to enhance their dispersion and reduce their deposition in porous systems. The aim of this study was to demonstrate the enhancement in the dispersion of nonmotile bacteria (Mycobacterium gilvum VM552, a polycyclic aromatic hydrocarbon-degrader, and Sphingobium sp. D4, a hexachlorocyclohexane-degrader, through micrometer-sized pores near the exclusion-cell-size limit, in the presence of motile Pseudomonas putida G7 cells. For this purpose, we used bioreactors equipped with two chambers that were separated with membrane filters with 3, 5, and 12 μm pore sizes and capillary polydimethylsiloxane (PDMS) microarrays (20 μm × 35 μm × 2.2 mm). The cotransport of nonmotile bacteria occurred exclusively in the presence of a chemoattractant concentration gradient, and therefore, a directed flow of motile cells. This cotransport was more intense in the presence of larger pores (12 μm) and strong chemoeffectors (γ-aminobutyric acid). The mechanism that governed cotransport at the cell scale involved mechanical pushing and hydrodynamic interactions. Chemotaxis-mediated cotransport of bacterial degraders and its implications in pore accessibility opens new avenues for the enhancement of bacterial dispersion in porous media and the biodegradation of heterogeneously contaminated scenarios., This research was funded by European Union's Horizon 2020 research and innovation program under the Marie Sklodowska- Curie grant agreement no. 895340 (BIOTAC project) and by the Spanish Ministry of Science and Innovation (PID2019- 109700RB-C21) .

Cells are promising as carriers that can enhance the delivery of nanomedicines. Cells that carry nanomedicinal cargo, either immobilized on the cell surface or internalized, can allow for highly specific delivery and can enable the transport of nanomedicines across challenging physiological barriers. The effective use of cells as carriers for the transport and delivery of nanomedines requires a careful selection of the chemical strategies that are used to load the cell-based carriers with their cargo. To this end, an in-depth understanding of the impact of various cell-surface modification chemistries on the viability and functional properties of the cells is essential, and techniques are needed that allow characterization of nanoparticle-modified living cells. This article touches upon both of these aspects. The first part of this review will present an overview of contemporary strategies that are available for the cell surface immobilization of nanoparticle cargo. After that, the various techniques that are most frequently used for the characterization of nanoparticle-modified cells will be discussed.

We discuss the genetic, demographic, and selective forces that are likely to be at play in restricting observed levels of DNA sequence variation in natural populations to a much smaller range of values than would be expected from the distribution of census population sizes alone—Lewontin’s Paradox. While several processes that have previously been strongly emphasized must be involved, including the effects of direct selection and genetic hitchhiking, it seems unlikely that they are sufficient to explain this observation without contributions from other factors. We highlight a potentially important role for the less-appreciated contribution of population size change; specifically, the likelihood that many species and populations may be quite far from reaching the relatively high equilibrium diversity values that would be expected given their current census sizes.

Human behavior has a major impact on the spread of the disease during an epidemic. At the same time, the spread of disease has an impact on human behavior. In this paper, we propose a coupled model of human behavior and disease transmission, take into account both individual-based risk assessment and neighbor-based replicator dynamics. The transmission threshold of epidemic disease and the stability of disease-free equilibrium point are analyzed. Some numerical simulations are carried out for the system. Three kinds of return matrices are considered and analyzed one by one. The simulation results show that the change of human behavior can effectively inhibit the spread of the disease, individual-based risk assessments had a stronger effect on disease suppression, but also more hitchhikers. This work contributes to the study of the relationship between human behavior and disease epidemics.

Predictions about the effect of natural selection on patterns of linked neutral variation are largely based on models involving the rapid fixation of unconditionally beneficial mutations. However, when phenotypes adapt to a new optimum trait value, the strength of selection on individual mutations decreases as the population adapts. Here, I use explicit forward simulations of a single trait with additive-effect mutations adapting to an “optimum shift.” Detectable “hitchhiking” patterns are only apparent if (i) the optimum shifts are large with respect to equilibrium variation for the trait, (ii) mutation rates to large-effect mutations are low, and (iii) large-effect mutations rapidly increase in frequency and eventually reach fixation, which typically occurs after the population reaches the new optimum. For the parameters simulated here, partial sweeps do not appreciably affect patterns of linked variation, even when the mutations are strongly selected. The contribution of new mutations vs. standing variation to fixation depends on the mutation rate affecting trait values. Given the fixation of a strongly selected variant, patterns of hitchhiking are similar on average for the two classes of sweeps because sweeps from standing variation involving large-effect mutations are rare when the optimum shifts. The distribution of effect sizes of new mutations has little effect on the time to reach the new optimum, but reducing the mutational variance increases the magnitude of hitchhiking patterns. In general, populations reach the new optimum prior to the completion of any sweeps, and the times to fixation are longer for this model than for standard models of directional selection. The long fixation times are due to a combination of declining selection pressures during adaptation and the possibility of interference among weakly selected sites for traits with high mutation rates.

Hitchhiking bistatic radar system takes the direct wave signal that is transmitted by the non-cooperative radar emitter as the reference to detect and analyze the target echo signal, so as to realize the positioning and tracking of the target. This radar system has the advantages of low cost and strong survivability. Aiming at the problem of passive radar to covert the detection of maritime targets, this paper develops a hitchhiking bistatic radar system for maritime target detection, which uses the shore-based radar as the non-cooperative radar emitter. By continuously collecting the direct wave and target echo data of the non-cooperative radar, the direct wave reference signal reconstruction, pulse compression, interference suppression and synchronization processing, non-coherent integration, MTI (moving target indication), clutter map processing, and adaptive CFAR (constant false alarm rate) detection are completed to obtain the azimuth, bistatic range, and Doppler frequency of the target, and finally realize the positioning of non-cooperative maritime targets. This paper first introduces and demonstrates the composition principle of the system, introduces the signal processing implementation method of the system in detail, and tests and analyzes the key algorithms. The experimental results show that the system can realize the passive coherent detection of maritime moving targets and locate multiple targets at the same time. The experiment obtains a very clear PPI (plane position indicator) display picture of the hitchhiking bistatic radar system, and the radar detection data of the experimental system is in good agreement with the AIS (automatic identification system) data.

Recent studies have demonstrated that phages can be co-transported with motile non-host bacteria, thereby enabling their invasion of biofilms and control of biofilm composition. Here, we developed a novel approach to isolate non-host bacteria able to co-transport phages from soil. It is based on the capability of phage-carrying non-host bacteria to move along mycelia out of soil and form colonies in plaques of their co-transported phages. The approach was tested using two model phages of differing surface hydrophobicity, i.e., hydrophobic Escherichia virus T4 (T4) and hydrophilic Pseudoalteromonas phage HS2 (HS2). The phages were mixed into soil and allowed to be transported by soil bacteria along the mycelia of Pythium ultimum. Five phage-carrying bacterial species were isolated (Viridibacillus sp., Enterobacter sp., Serratia sp., Bacillus sp., Janthinobacterium sp.). These bacteria exhibited phage adsorption efficiencies of ≈90–95% for hydrophobic T4 and 30–95% for hydrophilic HS2. The phage adsorption efficiency of Viridibacillus sp. was ≈95% for both phages and twofold higher than T4-or HS2-adsorption to their respective hosts, qualifying Viridibacillus sp. as a potential super carrier for phages. Our approach offers an effective and target-specific way to identify and isolate phage-carrying bacteria in natural and man-made environments.

© 2018 I. Hashem et al. Spatial evolutionary game theory explains how cooperative traits can survive the intense competition in biological systems. If the spatial distribution allows cooperators to interact with each other frequently, the benefits of cooperation will outweigh the losses due to exploitation by selfish organisms. However, for a cooperative behavior to get established in a system, it needs to be found initially in a sufficiently large cluster to allow a high frequency of intracooperator interactions. Since mutations are rare events, this poses the question of how cooperation can arise in a biological system in the first place. We present a simple model which captures two concepts from genetics that can explain how evolution overcomes the emergence problem. The first concept is, often in nature, a gene may not express its phenotype except under specific environmental conditions, rendering it to be a “silent” gene. The second key idea is that a neutral gene, one that does not harm or improve an organism's survival chances, can still spread through a population if it is physically near to another gene that is positively selected. Through these two ideas, our model offers a possible solution to the fundamental problem of emergence of cooperation in biological systems. ispartof: Complexity vol:2018 status: published

Simple Summary Rapid adaptation has been observed for several insects, including a number of agricultural pests. In these instances, it is expected that variation in insect-encoded genes encodes the variable phenotypes being acted on by natural selection. However, in addition to the thousands of genes encoded in their genomes, many insects harbor maternally transmitted, symbiotic bacteria encoding hundreds to thousands of genes of their own. Variation in the genes or presence and absence of such bacteria may, thus, also cause phenotypic variation, providing further raw material for natural selection. Here we studied symbiotic bacteria of the pea aphid, demonstrating that several change in prevalence within a single growing season. The frequencies of some bacteria shifted in concert with environmental factors predicted to determine their costs and benefits. Interpreting these correlations as plausible signals of symbiont-mediated insect adaptation, we found little evidence in support of alternative hypotheses, and that defense against fungal pathogens was possibly the most common beneficial symbiont service. Yet we also found that the particular combinations of bacteria living within an aphid may sometimes shape how aphids respond to natural selection. Our results have implications for the management of crop pests and for understanding the nature of rapid insect adaptation. Abstract Insects harbor a variety of maternally inherited bacterial symbionts. As such, variation in symbiont presence/absence, in the combinations of harbored symbionts, and in the genotypes of harbored symbiont species provide heritable genetic variation of potential use in the insects’ adaptive repertoires. Understanding the natural importance of symbionts is challenging but studying their dynamics over time can help to elucidate the potential for such symbiont-driven insect adaptation. Toward this end, we studied the seasonal dynamics of six maternally transferred bacterial symbiont species in the multivoltine pea aphid (Acyrthosiphon pisum). Our sampling focused on six alfalfa fields in southeastern Pennsylvania, and spanned 14 timepoints within the 2012 growing season, in addition to two overwintering periods. To test and generate hypotheses on the natural relevance of these non-essential symbionts, we examined whether symbiont dynamics correlated with any of ten measured environmental variables from the 2012 growing season, including some of known importance in the lab. We found that five symbionts changed prevalence across one or both overwintering periods, and that the same five species underwent such frequency shifts across the 2012 growing season. Intriguingly, the frequencies of these dynamic symbionts showed robust correlations with a subset of our measured environmental variables. Several of these trends supported the natural relevance of lab-discovered symbiont roles, including anti-pathogen defense. For a seventh symbiont—Hamiltonella defensa—studied previously across the same study periods, we tested whether a reported correlation between prevalence and temperature stemmed not from thermally varying host-level fitness effects, but from selection on co-infecting symbionts or on aphid-encoded alleles associated with this bacterium. In general, such “hitchhiking” effects were not evident during times with strongly correlated Hamiltonella and temperature shifts. However, we did identify at least one time period in which Hamiltonella spread was likely driven by selection on a co-infecting symbiont—Rickettsiella viridis. Recognizing the broader potential for such hitchhiking, we explored selection on co-infecting symbionts as a possible driver behind the dynamics of the remaining six species. Out of twelve examined instances of symbiont dynamics unfolding across 2-week periods or overwintering spans, we found eight in which the focal symbiont underwent parallel frequency shifts under single infection and one or more co-infection contexts. This supported the idea that phenotypic variation created by the presence/absence of individual symbionts is a direct target for selection, and that symbiont effects can be robust under co-habitation with other symbionts. Contrastingly, in two cases, we found that selection may target phenotypes emerging from symbiont co-infections, with specific species combinations driving overall trends for the focal dynamic symbionts, without correlated change under single infection. Finally, in three cases—including the one described above for Hamiltonella—our data suggested that incidental co-infection with a (dis)favored symbiont could lead to large frequency shifts for “passenger” symbionts, conferring no apparent cost or benefit. Such hitchhiking has rarely been studied in heritable symbiont systems. We propose that it is more common than appreciated, given the widespread nature of maternally inherited bacteria, and the frequency of multi-species symbiotic communities across insects.

Evolve and re-sequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have a weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that are either not replicated or show only a low statistical significance in a primary E&R experiment. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.

Speciation, that is, the evolution of reproductive barriers eventually leading to complete isolation, is a crucial process generating biodiversity. Recent work has contributed much to our understanding of how reproductive barriers begin to evolve, and how they are maintained in the face of gene flow. However, little is known about the transition from partial to strong reproductive isolation (RI) and the completion of speciation. We argue that the evolution of strong RI is likely to involve different processes, or new interactions among processes, compared with the evolution of the first reproductive barriers. Transition to strong RI may be brought about by changing external conditions, for example, following secondary contact. However, the increasing levels of RI themselves create opportunities for new barriers to evolve and, and interaction or coupling among barriers. These changing processes may depend on genomic architecture and leave detectable signals in the genome. We outline outstanding questions and suggest more theoretical and empirical work, considering both patterns and processes associated with strong RI, is needed to understand how speciation is completed. This article is part of the theme issue ‘Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers'.

Background Upon the detection of imminent peril, pea aphids (Acyrthosiphon pisum) often drop off their host plant. Dropping in response to insect enemies is intermittent in nature, but when a mammalian herbivore feeds on their host plant, a large mixed-age group of aphids usually drops off the plant at once. Aphids that reach the ground are confronted with new, hostile environmental conditions and must therefore quickly walk toward a suitable host plant. The longer it takes an aphid to reach a host plant, the more it is exposed to the risks of starvation, desiccation and predation. Results We found that young nymphs, which have limited mobility and high mortality on the ground, quickly climb on conspecific (not necessarily parental) adults and cling to them before the latter start walking in search of a plant. This “riding” behavior is likely to be adaptive for the nymphs, for it shortens their journey and the time they spend off a host plant. Adults however, seem to be irritated by the riding nymphs, as they often actively try to remove them. Conclusions After dropping from the host plant, young aphid nymphs travel at least part of the way back to a plant on the backs of adults. For the riding behavior to take place, nymphs need to successfully find adults and withstand removal attempts. Electronic supplementary material The online version of this article (10.1186/s12983-018-0292-7) contains supplementary material, which is available to authorized users.

In its initial formulation by Motoo Kimura, the neutral theory was concerned solely with the level of variability maintained by random genetic drift of selectively neutral mutation, and the rate of molecular evolution caused by the fixation of such mutations. The original theory considered events at a single genetic locus in isolation from the rest of the genome. It did not take long, however, for theoreticians to wonder whether selection at one or more loci might influence neutral variability at linked sites. Once DNA sequence variability could be studied, and especially when resequencing of whole genomes became possible, it became clear that patterns of neutral variability in genomes are affected by selection at linked sites, and that these patterns could advance our understanding of natural selection, and can be used to detect the action of selection in genomic regions, including selection much weaker than could be detected by direct measurements of the relative fitnesses of different genotypes. We outline the different types of processes that have been studied, in approximate order of their historical development.

Recognizing when and how rapid evolution drives ecological change is fundamental for our understanding of almost all ecological and evolutionary processes such as community assembly, genetic diversification and the stability of communities and ecosystems. Generally, rapid evolutionary change is driven through selection on genetic variation and is affected by evolutionary constraints, such as tradeoffs and pleiotropic effects, all contributing to the overall rate of evolutionary change. Each of these processes can be influenced by the presence of multiple environmental stressors reducing a population's reproductive output. Potential consequences of multistressor selection for the occurrence and strength of the link from rapid evolution to ecological change are unclear. However, understanding these is necessary for predicting when rapid evolution might drive ecological change. Here we investigate how the presence of two stressors affects this link using experimental evolution with the bacterium Pseudomonas fluorescens and its predator Tetrahymena thermophila. We show that the combination of predation and sublethal antibiotic concentrations delays the evolution of anti-predator defence and antibiotic resistance compared with the presence of only one of the two stressors. Rapid defence evolution drives stabilization of the predator-prey dynamics but this link between evolution and ecology is weaker in the two-stressor environment, where defence evolution is slower, leading to less stable population dynamics. Tracking the molecular evolution of whole populations over time shows further that mutations in different genes are favoured under multistressor selection. Overall, we show that selection by multiple stressors can significantly alter eco-evolutionary dynamics and their predictability.

The long-range movement of organelles, vesicles, and macromolecular complexes by microtubule-based transport is crucial for cell growth and survival. The canonical view of intracellular transport is that each cargo directly recruits molecular motors via cargo-specific adaptor molecules. Recently, a new paradigm called 'hitchhiking' has emerged: some cargos can achieve motility by interacting with other cargos that have already recruited molecular motors. In this way, cargos are co-transported together and their movements are directly coupled. Cargo hitchhiking was discovered in fungi. However, the observation that organelle dynamics are coupled in mammalian cells suggests that this paradigm may be evolutionarily conserved. We review here the data for hitchhiking and discuss the biological significance of this non-canonical mode of microtubule-based transport.

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P

Understanding the forces that shape patterns of genetic variation across the genome is a major aim in evolutionary genetics. An emerging insight from analyses of genome-wide polymorphism and divergence data is that selection on linked sites can have an important impact on neutral genetic variation. However, in contrast to Drosophila, which exhibits a signature of recurrent hitchhiking, many plant genomes studied so far seem to mainly be affected by background selection. Moreover, many plants do not exhibit classic signatures of linked selection, such as a correlation between recombination rate and neutral diversity. In this review, I discuss the impact of genome architecture and mating system on the expected signature of linked selection in plants and review empirical evidence for linked selection, with a focus on plant model systems. Finally, I discuss the implications of linked selection for inference of demographic history in plants.

Inteins are self-splicing proteins that occur in-frame within host-coded proteins. DNA elements coding for inteins insert specifically in highly conserved motifs of target genes. These mobile genetic elements have an uneven distribution and thus far have been found only in certain species of bacteria, archaea and fungi, a few viruses of algae and amoebozoa and in the entomopathogen, Chilo iridescent virus (CIV). Here, we report the discovery of seven new inteins parasitizing iridoviruses infecting metazoans: three within their δ DNA polymerase genes and four in genes coding for their large ribonucleotide reductase subunit. Analyses of coding sequences suggest that these inteins were acquired by ancestors shared by viruses currently classified as members of different families of viruses with large double-stranded (ds) DNA genomes and then were maintained by vertical transmission, or lost. Of significant interest is the finding that inteins present in the δ DNA polymerases of iridoviruses insert at a different location into the YGDTDS motif when compared to those found in other viruses and prokaryotes. In addition, our phylogenetic investigations suggest that inteins present in the δ DNA polymerases of these viruses might have an origin different from those found in prokaryotes. Finally, we use the sequence features of the intein insertion sites in host genes to discuss the high polymorphisms of inteins within and among viral species and the immunity of their genetic counterparts in the eukaryotic hosts of these viruses.

Background Methods for parentage control in cattle have changed since their initial implementation in the late 1950’s from blood group typing to more current single nucleotide polymorphism determination. In the early 1990’s, 12 microsatellites were selected by the International Society for Animal Genetics based on their informativeness and robustness in a variety of different cattle breeds. Since then this panel is used as standard in cattle herd book breeding and its application is accompanied by recurrent international comparison tests ensuring permanent validity for the most common commercial dairy and beef cattle breeds for example Holstein Friesian, Simmental, Angus, and Hereford. Although, nearly every parentage can be resolved using these microsatellites, cases with very close relatives became an emerging resolution problem during recent years. This is mainly due to an increase of monomorphism and a trend to the fixation of alleles, although no direct selection against their variability was applied. Thus other effects must be presumed resulting in a loss of polymorphism information content, heterozygosity, and exclusion probabilities. Results To determine changes of allele frequencies and exclusion probabilities, we analyzed the development of these parameters for the 12 microsatellites from 2004 to 2014. One hundred sixty eight thousand recorded Holstein Friesian cattle genotypes were evaluated. During this period certain alleles of nine microsatellites increased significantly (t-values >5). When calculating the exclusion probabilities for 11 microsatellites, reduction was determined for the three situations, i.e. one parent is wrongly identified (p = 0.01), both parents are wrongly identified (p = 0.005), and the genotype of one parent is missing (p = 0.048). With the addition of BM1818 to the marker set in 2009, this development was corrected leading to significant increases in exclusion probabilities. Although, the exclusion probabilities for the three family situations using the 12 microsatellites are >99 %, the clarification of 142 relationships in 40,000 situations where one parent is missing will still be impossible. Twenty-five sires were identified that are responsible for the most significant microsatellite allele increases in the population. The corresponding alleles are mainly associated with milk protein and fat yield, body weight at birth and weaning, as well as somatic cell score, milk fat percentage, and longissimus muscle area. Conclusions Our data show that most of the microsatellites used for parentage control in cattle show directional changes in allele frequencies consistent with the history of artificial selection in the German Holstein population.

Orientador: Eduardo Candido Xavier Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação Resumo: Nesse trabalho é apresentado um framework que tem como objetivo facilitar o compartilhamento de veículos no dia a dia de uma grande cidade. O framework apresenta uma arquitetura cliente-servidor. O lado cliente é usado por passageiros para requerer uma viagem compartilhada e por motoristas, que podem ser donos de veículos privados ou taxistas, os quais estão dispostos a compartilharem seu veículo para redução de custos ou obtenção de lucro. O lado servidor precisa resolver um problema dinâmico de otimização que provamos ser NP-difícil. O problema em questão, denominado Ride-sharing Problem with Money Incentive (RSPMI), é modelado da seguinte forma: em cada instante de tempo, temos um conjunto de pessoas, as quais necessitam de uma viagem a partir de um ponto de origem até um ponto de destino, e um conjunto de veículos, onde cada um tem uma origem e um destino. É necessário considerar algumas restrições que os passageiros possam ter, que são: o horário mínimo de saída da origem, o horário máximo de chegada até o destino, o número de passageiros que devem viajar juntos e também o valor máximo que estão dispostos a pagar. Os veículos também apresentam restrições, já que estes podem ter um horário mínimo de saída e um horário máximo de chegada. O motorista define a capacidade máxima do veículo e o preço por quilômetro rodado. Dado todas as informações e restrições, o problema consiste em formar uma rota para cada veículo com o objetivo de maximizar o número de passageiros atendidos e de minimizar os custos. O RSPMI é um problema novo na literatura e difere dos demais problemas de compartilhamento de veículos por ser o único a considerar custos compartilhados, calculando o valor total a ser pago por cada passageiro e possibilitando cada um escolher o valor máximo a ser pago. O foco do trabalho se deu no estudo e desenvolvimento de métodos que possam resolver a versão dinâmica do RSPMI, em tempo real, e em larga escala. O método proposto necessita de uma heurística que resolva o problema estático e de um algoritmo que resolva, eficientemente, o Many to Many Shortest Path Problem. Desenvolvemos heurísticas GRASP para o problema estático e usamos um algoritmo baseado em Contraction Hierarchies, o qual é muito eficiente, para lidar com os caminhos mínimos. Experimentos computacionais foram realizados usando instâncias que simulam, a partir de dados reais, uma atividade de compartilhamento de táxis na cidade de São Paulo. Em nossas simulações, os passageiros pagaram, em média, quase 30% menos do que pagariam em uma viagem privada Abstract: In this work, we present a framework for dynamic ride-sharing. The framework has a client-server architecture. The client is used by passengers to request rides and by drivers, including vehicle owners and taxi drivers, who are willing to share their vehicles in order to reduce costs or to earn money. The server needs to solve a dynamic optimization problem which is proved to be NP-Hard. The problem, called Ride-sharing Problem with Money Incentive (RSPMI), is modeled in the following manner: at each instant of time, there are a set of passengers needing to travel from a source to a destination point and a set of vehicles, each one having a source and a destination. Passengers have constraints that need to be considered, which are: an earliest departure time, a latest arrival time, the number of passengers that will travel together and the maximum value they are willing to pay for the ride. Vehicles can have an earliest departure time and a latest arrival time, as well. They also have a maximum capacity and a price per kilometer. The problem is to compute a route for each vehicle, with the goal of maximizing the number of attended requests and minimizing the total paid by passengers. RSPMI is a new problem in the literature, differing from others ride-sharing problems, because it is the only one that considers shared costs, having a constraint which allows people to set the maximum value for the ride. The main focus of the work is to develop methods that can solve the dynamic version of the RSPMI, in real time and large scale. The proposed method needs an heuristic to solve the static problem and an algorithm to solve the Many to Many Shortest Path Problem. We developed GRASP heuristics for the static problem and used Contraction Hierarchies to deal with the shortest path problem. Computational experiments were made to evaluate our method and heuristics. We used instances based on real data that simulates a day of taxis activity in the city of Sao Paulo. In our experiments, passengers paid, on average, almost 30% less than a private ride Mestrado Ciência da Computação Mestre em Ciência da Computação

Many crops contain domestication genes that are generally considered to lower fitness of crop–wild hybrids in the wild environment. Transgenes placed in close linkage with such genes would be less likely to spread into a wild population. Therefore, for environmental risk assessment of GM crops, it is important to know whether genomic regions with such genes exist, and how they affect fitness. We performed quantitative trait loci (QTL) analyses on fitness(-related) traits in two different field environments employing recombinant inbred lines from a cross between cultivated Lactuca sativa and its wild relative Lactuca serriola. We identified a region on linkage group 5 where the crop allele consistently conferred a selective advantage (increasing fitness to 212% and 214%), whereas on linkage group 7, a region conferred a selective disadvantage (reducing fitness to 26% and 5%), mainly through delaying flowering. The probability for a putative transgene spreading would therefore depend strongly on the insertion location. Comparison of these field results with greenhouse data from a previous study using the same lines showed considerable differences in QTL patterns. This indicates that care should be taken when extrapolating experiments from the greenhouse, and that the impact of domestication genes has to be assessed under field conditions.

When a beneficial mutation occurs in a population, the new, favored allele may spread to the entire population. This process is known as a selective sweep. Suppose we sample $n$ individuals at the end of a selective sweep. If we focus on a site on the chromosome that is close to the location of the beneficial mutation, then many of the lineages will likely be descended from the individual that had the beneficial mutation, while others will be descended from a different individual because of recombination between the two sites. We introduce two approximations for the effect of a selective sweep. The first one is simple but not very accurate: flip $n$ independent coins with probability $p$ of heads and say that the lineages whose coins come up heads are those that are descended from the individual with the beneficial mutation. A second approximation, which is related to Kingman's paintbox construction, replaces the coin flips by integer-valued random variables and leads to very accurate results.