280 research outputs found

    Genetic Algorithms in Time-Dependent Environments

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    The influence of time-dependent fitnesses on the infinite population dynamics of simple genetic algorithms (without crossover) is analyzed. Based on general arguments, a schematic phase diagram is constructed that allows one to characterize the asymptotic states in dependence on the mutation rate and the time scale of changes. Furthermore, the notion of regular changes is raised for which the population can be shown to converge towards a generalized quasispecies. Based on this, error thresholds and an optimal mutation rate are approximately calculated for a generational genetic algorithm with a moving needle-in-the-haystack landscape. The so found phase diagram is fully consistent with our general considerations.Comment: 24 pages, 14 figures, submitted to the 2nd EvoNet Summerschoo

    Masters of the Universe: Bid Rigging by Private Equity Firms in Multibillion Dollar LBOs

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    In the first successful case of its kind, a class action alleging widespread collusion in the market for leveraged buyouts, some of the world’s largest private equity firms settled Dahl v. Bain Capital Partners, LLC for 590.5million.Thecasewasuniquenotonlyforitssizeandthefactthatitinvolvedcomplexfinancialtransactionsinsteadofatypicalcommodity,butalsobecausetheclaimantsusedauctiontheorytodemonstrateboththeβ€œplus”factorsrequiredtoproveantitrustinjuryandtheresultingdamages.Economicanalysesshowthatthecosttoshareholdersofcollusionintheeightlitigatedmultiβˆ’billiondollarleveragedbuyouttransactionsapproached590.5 million. The case was unique not only for its size and the fact that it involved complex financial transactions instead of a typical commodity, but also because the claimants used auction theory to demonstrate both the β€œplus” factors required to prove antitrust injury and the resulting damages. Economic analyses show that the cost to shareholders of collusion in the eight litigated multi-billion dollar leveraged buyout transactions approached 12 billion. The use of empirical economic analysis in antitrust litigation is now de rigueur. Courts expect it, and litigants have an array of econometricians available who understand both how to work with data and antitrust doctrine. In β€œordinary” commodities price fixing cases, plaintiffs and defendants are expected to engage experts who gather transaction data and apply regression theory and other economic analyses to contest whether it is possible to demonstrate injury, impact, and damages. Dahl was not an ordinary case in that it involved neither a commodity nor a sellers’ cartel. Instead, it involved a buyers’ cartel which, Plaintiffs alleged, conspired to drive down the price of a number of unique, large LBOs during the mid-2000s. Additionally, the case was notable because of the Plaintiffs’ decision to use the auction theory to demonstrate the existence of antitrust violations and the extent of damage

    New trends in the treatment of bone metastasis

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    Bone metastasis is often the penultimate harbinger of death for many cancer patients. Bone metastases are often associated with fractures and severe pain resulting in decreased quality of life. Accordingly, effective therapies to inhibit the development or progression of bone metastases will have important clinical benefits. To achieve this goal understanding the mechanisms through which bone metastases develop and progress may provide targets to inhibit the metastases. In the past few years, there have been advances in both understanding the mechanisms through which bone metastases develop and how they impact bone remodeling. Additionally, gains in promising clinical strategies to target bone metastases have been developed. In this prospectus, we will discuss some of these advances. J. Cell. Biochem. 102: 1095–1102, 2007. Β© 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57363/1/21540_ftp.pd

    Diel activity patterns of vector mosquito species in the urban environment: Implications for vector control strategies

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    Mathematical models have been widely used to study the population dynamics of mosquitoes as well as to test and validate the effectiveness of arbovirus outbreak responses and mosquito control strategies. The objective of this study is to assess the diel activity of mosquitoes in Miami-Dade, Florida, and Brownsville, Texas, the most affected areas during the Zika outbreak in 2016–2017, and to evaluate the effectiveness of simulated adulticide treatments on local mosquito populations. To assess variations in the diel activity patterns, mosquitoes were collected hourly for 96 hours once a month from May through November 2019 in Miami-Dade County, Florida, and Brownsville, Texas. We then performed a PERMANOVA followed by a SIMPER analysis to assess whether the abundance and species richness significantly varies at different hours of the day. Finally, we used a mathematical model to simulate the population dynamics of 5 mosquito vector species and evaluate the effectiveness of the simulated adulticide applications. A total of 14,502 mosquitoes comprising 17 species were collected in Brownsville and 10,948 mosquitoes comprising 19 species were collected in Miami-Dade County. Aedes aegypti was the most common mosquito species collected every hour in both cities and peaking in abundance in the morning and the evening. Our modeling results indicate that the effectiveness of adulticide applications varied greatly depending on the hour of the treatment. In both study locations, 9 PM was the best time for adulticide applications targeting all mosquito vector species; mornings/afternoons (9 AM– 5 PM) yielded low effectiveness, especially for Culex species, while at night (12 AM– 6 AM) the effectiveness was particularly low for Aedes species. Our results indicate that the timing of adulticide spraying interventions should be carefully considered by local authorities based on the ecology of the target mosquito species in the focus area

    Tracking the decline of the world’s largest seabream against policy adjustments

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    For most rare marine species, abundance trends are poorly estimated. This uncertainty often translates into disagreement on management regulations, impeding conservation efforts when they are most urgently required. The world’s largest sea bream, the red steenbras Petrus rupestris, has undergone a substantial and widely acknowledged decline during the 20th century. Standardised probability of encounter over the last 3 decades was used to track red steenbras abundance trajectories in 2 regions, which together represent the species’ distribution. The results predicted a reduction in abundance of 44% in the East region and 96% in the South-West region, from what was already considered to be a collapsed population at the start of the time series. The species is now largely confined to areas in the centre of its historical abundance. Content analysis of a recreational angling magazine revealed a concurrent 50% decrease in reported size between 1984 and 2012. Shore-based observer data (2009-2010) indicate that the impact of recreational fishers on this species far exceeded that of commercial fishers at the time. Regulations in the form of progressively more stringent catch and effort restrictions appear to have been largely ineffective, too lenient, implemented too late or were unsuitable to control fishing mortality for this species. This study highlights 2 fundamental challenges in management of rare marine fish species: (1) providing decision makers with a credible measure of abundance for species whose rarity limits data availability and (2) implementing effective policy changes before the specific measures become ineffective and obsolete

    Challenges and opportunities in transdisciplinary science: The experience of next generation scientists in an agriculture and climate research collaboration

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    Agriculture in the twenty-first century faces unprecedented challenges from increasing climate variability to growing demands on natural resources to globalizing economic markets. These emerging agricultural issues, spanning both human and natural dimensions, are uniquely formulated, exceedingly complex, and difficult to address within existing disciplinary domains (Eigenbrode et al. 2007; Reganold et al. 2011; Foley et al. 2005; Hansen et al. 2013). Therefore, the next generation of scientists working on these issues must not only be highly trained within a disciplinary context but must also have the capacity to collaborate with others to solve systems-level problems

    Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

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    Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity - i.e. the tendency to form two separate subgraphs - than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network

    An Iterative Jackknife Approach for Assessing Reliability and Power of fMRI Group Analyses

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    For functional magnetic resonance imaging (fMRI) group activation maps, so-called second-level random effect approaches are commonly used, which are intended to be generalizable to the population as a whole. However, reliability of a certain activation focus as a function of group composition or group size cannot directly be deduced from such maps. This question is of particular relevance when examining smaller groups (<20–27 subjects). The approach presented here tries to address this issue by iteratively excluding each subject from a group study and presenting the overlap of the resulting (reduced) second-level maps in a group percent overlap map. This allows to judge where activation is reliable even upon excluding one, two, or three (or more) subjects, thereby also demonstrating the inherent variability that is still present in second-level analyses. Moreover, when progressively decreasing group size, foci of activation will become smaller and/or disappear; hence, the group size at which a given activation disappears can be considered to reflect the power necessary to detect this particular activation. Systematically exploiting this effect allows to rank clusters according to their observable effect size. The approach is tested using different scenarios from a recent fMRI study (children performing a β€œdual-use” fMRI task, nβ€Š=β€Š39), and the implications of this approach are discussed

    A Uniform Genomic Minor Histocompatibility Antigen Typing Methodology and Database Designed to Facilitate Clinical Applications

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    BACKGROUND: Minor Histocompatibility (H) antigen mismatches significantly influence the outcome of HLA-matched allogeneic stem cell transplantation. The molecular identification of human H antigens is increasing rapidly. In parallel, clinical application of minor H antigen typing has gained interest. So far, relevant and simple tools to analyze the minor H antigens in a quick and reliable way are lacking. METHODOLOGY AND FINDINGS: We developed a uniform PCR with sequence-specific primers (PCR-SSP) for 10 different autosomal minor H antigens and H-Y. This genomic minor H antigen typing methodology allows easy incorporation in the routine HLA typing procedures. DNA from previously typed EBV-LCL was used to validate the methodology. To facilitate easy interpretation for clinical purposes, a minor H database named dbMinor (http://www.lumc.nl/dbminor) was developed. Input of the minor H antigen typing results subsequently provides all relevant information for a given patient/donor pair and additional information on the putative graft-versus-host, graft-versus-tumor and host-versus-graft reactivities. SIGNIFICANCE: A simple, uniform and rapid methodology was developed enabling determination of minor H antigen genotypes of all currently identified minor H antigens. A dbMinor database was developed to interpret the genomic typing for its potential clinical relevance. The combination of the minor H antigen genomic typing methodology with the online dbMinor database and applications facilitates the clinical application of minor H antigens anti-tumor targets after stem cell transplantation
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