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What Constitutes Fitness to Plead

The basic legal criteria of fitness to plead or competence to stand trial, arising from the cases of Pritchard in England and Dusky in the USA remain substantially unchanged, although Jackson v. Indiana did bring treatability issues into the USA criteria, and Gray et al. (2001) have argued that ability to give evidence may become part of the fitness to plead criteria in England, since the abolition of the right to silence. In both England and the USA courts have taken advice from psychiatrists and psychologists about fitness to plead, although in the USA they are not obliged to do so (Grisso, 1986). In England there have been no standardised tests of fitness to plead, although there have been several analyses of the criteria which mental health professionals use. Grubin (1991a), for example, found that in his examination of the 295 reports of cases of fitness to plead between 1976 and 1988 In Mackay and Kearns' (2000) more recent analysis of 125 cases of fitness to plead in England,...

Fitness Function Specification

The genetic programming code that we used searched for the minimum fitness from the most perfect score possible, i.e., a perfect foresight score. This allowed for the possibility of a model of seemingly infinite badness without encountering numerical difficulties with scaling. You can well imagine that we created such models during our search As an aside, the discussions that took place as we developed the fitness function were illuminating and incorporated a lot of really good suggestions - we'll see additional benefits from these discussions in future factor model research. Equation (6-1) describes our fitness function. Recall that the genetic program was configured to minimize the fitness function value, i.e., the closer we got to perfect the more fit the formula. Fitnessy (TBperfect + TMperfect) - (TBy + TMy - Penaltiesy) (6-1) the fitness score of formula y top to bottom deciles spread Information Ratios for the perfect foresight and formula y cases top to middle deciles spread...

Grappling With A Multiobjective Fitness Measure

The fitness measures used in previously published examples of the automated synthesis of analog circuits by means of genetic programming and genetic algorithms have usually consisted of only a few elements (rarely as many as four). For example, only three elements (gain, bias, and distortion) were incorporated into the fitness measure employed to synthesize the amplifier in chapter 45 of Koza, Bennett, Andre, and Keane 1999 and only four elements (gain, bias, distortion, and the area of the bounding rectangle after placement and routing) were considered in chapter 5 of Koza, Keane, Streeter, Mydlowec, Yu, and Lanza 2003. In contrast, the data sheets for commercial circuits typically specify a circuit's performance for well over a dozen characteristics. As the number of disparate elements in a fitness measure increases, it becomes increasingly difficult to combine the elements in a way that enables the fitness measure to navigate a complex search space. In our ongoing project in which...

What Is Meant by Fitness

Fittest are those that have a higher chance of passing on their genes to the next generation. There are many ways to achieve this. To put it differently, the term fitness in this genetic sense does not necessarily refer to strong muscles or the ability to jog several miles. The fittest individuals are not necessarily the strongest, the smartest, or the healthiest. For example, it could be said that white four-o'clock flowers are less fit, not because they are sickly or smaller or have fewer flowers, but because they are not chosen by insect pollinators that prefer red flowers. In such a case, if insect pollinators prefer red flowers, they will not pollinate white or pink flowers, with the result that the white version of the gene will be underrepresented in subsequent generations. Therefore, the genes from the fittest individuals are those that are selected for in such a way that their proportion will increase in successive generations. The genes from less fit individuals are selected...

Fitness Depends Upon the Environment

Let us imagine a mutation in an insect that made it lose its wings. How would this affect its fitness We might expect that this would be bad, that is, an insect without wings would have lower fitness compared to the same insect with wings. But what if loss of wings happened to insects that were blown off shore, onto an island, in an area that is often windy The island is small and the area windy, so it might be safer for insects to walk around rather than try to fly and get blown away into the ocean. Thus whether a particular phenotype is higher or lower in fitness depends upon the environment or circumstances in which an individual lives. The case of insect pests demonstrates the way in which human activity changes the environment to affect selection. Various weevils thrive on agricultural crops and destroy them. Populations of weevils have all types of natural genetic variations because they breed freely in the wild and accumulate random, spontaneous mutations. But farmers started...


Wild plants, or weeds, have high fitness because they possess many or all of the following characteristics stress tolerance, enhanced ability to make use of available soil nutrients, broad pest and disease resistance, early germination, rapid growth, successive flowerings, early seed-ripening, high seed viability, and so on. Such traits are usually of a quantitative character and a specific combination of several genes determines overall fitness. It may not therefore be an easy step to transfer such traits between crops and wild relatives, let alone more distant species. However, if the properties of a single gene clearly affect stress resistance, and thus fitness, special attention should be devoted to the risk assessment. While annual crops such as cereals do not seem to be a weedy threat, perennial plants, including genetically engineered trees and grasses, could prove to be hardier than their wild counterparts. If genes from GM crops cross out and into wild relatives, as genes...

The Fitness Function

The fitness function, as we quickly found, was the linchpin to making the genetic program produce progressively better results. Due to the nature of the portfolio construction process, it is pretty hard to simulate the various portfolio tradeoffs necessary to emulate the performance of a particular model. In particular, there are a huge number of interactions of both risk and return that can create massive combinatorial problems even with a small number of candidate stocks.

Fitness to plead

It has always been recognized that the accused person has to have a basic understanding of the legal process in order to have a fair trial. Standard tests have grown up in order to determine 'fitness to plead'. The grounds for a patient being considered unfit to plead are inability to Psychiatric reports are important in helping the court to determine the question of fitness to plead. The question of fitness to plead used to come up only rarely, and in the most serious cases, because persons found unfit to plead were sent to a Special Hospital without limit of time. However, in recent years, the court has had flexibility in how it 'disposes' of such cases, including community disposals and absolute discharge with no order. It seems, perhaps unsurprisingly, that the question of fitness to plead is now raised more frequently by the defence in a range of much less severe cases.

Fitness Measure

Each tree represents a detector and so the fitness measure should quantify the detection performance. A detector outputs a positive value when it judged the current traffic data to represent an incident onset. Each detector processed a set of training examples including incident cases and non-incident cases. Let TP denote the number of true positives (incidents detected) and FP denote the number of false positives (false alarms) that result after a detector had processed all the training cases. The detection performance was quantified by the following fitness measure where the variable controlled the balance between high sensitivity (high TP) and high specificity (low FP)

Please Readimportant Information

Kind, including without limitation, warranties of merchantability or fitness for a particular purpose, nor does it guarantee the accuracy, comprehensiveness, or timeliness of the information contained in this product. Readers should be aware that the universe of medical knowledge is constantly growing and changing, and that differences of medical opinion exist among authorities. Readers are also advised to seek professional diagnosis and treatment of any medical condition, and to discuss information obtained from this book with their health care provider.

Immunological and virologic events during acute HIV1 infection

Several factors can influence viral replication during acute infection and the establishment of a viral setpoint. These include the fitness of the infecting virus, host genetic factors and host immune responses. While antibodies against HIV-1 with neutralizing capacities are rarely detectable during primary HIV-1 infection, a number of studies have demonstrated a crucial role of HIV-1-specific cellular immune responses for the initial control of viral replication during this stage of infection. A massive, oligoclonal expansion of CD8+ T cell responses has been described during acute HIV-1 infection (Pantaleo 1994), and the appearance of HIV-1-specific CD8+ T cells has been temporally associated with the initial decline of viremia (Koup 1994, Borrow 1994). These CD8+ T cells have the ability to eliminate HIV-1-infected cells directly by MHC class I-restricted cytolysis or indirectly

Cisregulatory elements

At a greater distance are called cis-regulatory elements. Together with the transcribed regions of genes, the promoters and cis-regulatory elements form the working parts of the genome. It has been estimated that around 5 of the human genome is under evolutionary constraint, and hence may be assumed to contribute to the fitness of the organism in some way. However, less than a third of this functional DNA comprises coding regions, while the rest is made up of different classes of regulatory elements such as promoters, enhancers and silencers (which control gene expression) and locus control regions, insulators and matrix attachment regions (which mediate chromatin organization). There is, as yet, no clear understanding of how exactly promoters interact with the various cis-regulatory elements.

GA Population Sizing from the Perspective of Competing Building Blocks

Considers how the GA can derive accurate estimates of BB fitness in the presence of detrimental noise. It recognizes that, while selection is the principal decision maker, it distinguishes among individuals based on fitness and not by considering BBs. Therefore, there is a possibility that an inferior BB gets selected over a better BB in a competition due to noisy observed contributions from adjoining BBs that are also engaged in competitions. Figure 4-2. Fitness distribution of individuals in the population containing the two competing building blocks, the best BB Hi , and the second best BB H2. When two mean fitness distributions overlap, low sampling increases the likelihood of estimation error. When sampling around each mean fitness is increased, fitness distributions are less likely to be inaccurately estimated. Figure 4-2. Fitness distribution of individuals in the population containing the two competing building blocks, the best BB Hi , and the second best BB H2. When two mean...

GP Population Sizing Model

The first way the GP population size derivation diverges from the GA case is how BB fitness variance (i.e., cr and a2H2) is estimated (for reference, see Equation 4.6). Recall that for the GA the source of a BB's fitness variance was collateral noise from the (rn 1) competitions of its adjoining BBs. In GP, the source of collateral noise is the average number of adjoining BBs present and expressed in each tree, denoted as Thus

Introduction Dimensions of Developmental Psychology

Often, however, mechanistic and reductionist models were used to conceptualize the relations among levels. For example, Homans's (1961) social exchange theory used principles of operant learning to reduce dyadic relationships to psychogenic terms. Wilson (1975), in turn, reduced instances of (seemingly) moral behaviors (labeled as altruistic) to purported biogenic explanations (involving the concepts of ga-metic potential and inclusive fitness).

Theory Concerning Network

By the same token, it is irrelevant to the test problem to categorize which fragments (i.e., subtrees) are introns and which are not, even if bloat were present. Introns presume executability (i.e., syntactically correct code) and functionality (i.e., upon execution, something happens). Neither applies to Highlander because code is not executed during the course of evaluating an individual. Consequently, it is entirely possible to point to a specific branch in a Highlander solution and not know whether it is an intron or whether it is the part of the tree that contributes to a fitness score. The specific through networking. (For this reason, then, no mutation was used.) The tuning parameter is the specified percentage of N uniquely labeled nodes that an individual tree must have. As a crude measure of problem difficulty, we used a successful-trials ratio i.e., the number of trials that produced a correct solution, which is then normalized to the total number of GP trials. Figure 5-4...

Theory Concerning Content

I would say that much of the theoretical work in the GP community occurs at this level, where content is no longer abstracted away, where problem domains matter, and where fitness depends on executing code. Consequently, current theories on schema, bloat, and diversity (to name a few) have resided at this level. My own group's current work at this level is characterized by the following motivating question How do the consequences of lattice and network affect what happens at the level of content The Binomial-3 is an instance taken from symbolic regression and involves solving for the function J x) + 3x + 3x2 + x3. Fitness cases are 50 equidistant points generated from J x) over the interval -1, 0). The function set is +, -, x, -f , which corresponds to arithmetic operators of addition, subtraction, multiplication, and protected division. Its terminal set is x, R , where x is the symbolic variable and R is the set of ephemeral random constants that are distributed uniformly over the...

Practical Implications of Content

What Figure 5-6 indicates is that it may be possible to overload GP's space with too many choices. Fitness-proportionate selection allows for a significant fraction of what is theoretically allowable for recombination of initial population material. In the Binomial-3, much of this allowable material would be unique and in the form of ephemeral random constants. The selection) that retained Use tournament selection. For our work, we used a tournament selection size of 7. Although fitness-proportionate selection is beneficial in maintaining diversity, tournament selection removes choices as a natural consequence of the method. Fewer choices might result in fewer costs of overloading GP's space.

Selection and the shaping of localized LD

Most forms of selection seen in nature are frequency-independent. Such selection can be either directional or balancing. Directional selection drives a variant either to extinction or fixation whilst balancing selection favours maintenance of heterozygosity. Less common forms of selection such as frequency-dependant selection (selection in which fitness is a function of gene frequency) will also maintain variation in a population in a similar manner to balancing selection. Given the driving force behind selection, the ability to detect its genetic signals would help in understanding the forces that have shaped human traits.

From Philosophy To Theory

Such a search for fundamental principles, we maintain, should begin with human evolution. Just as each person is composed of a total patterning of variables across all domains of human expression, it is the total organism that survives and reproduces, carrying forth both its adaptive and maladaptive potentials into subsequent generations. As the evolutionary success of organisms is dependent on the entire configuration of the organism's characteristics and potentials, so, too, does psychological fitness derive from the relation of the entire configuration of personal characteristics to the environments in which the person functions.

Watch and Wait or Even Simplifying ART

The critical question relates to how intensively treatment should be continued Some drugs can certainly be discontinued. NNRTIs such as nevirapine or efavirenz can be stopped if resistance mutations have been found, since NNRTI mutations do not influence replicative fitness (Piketty 2004). What about PIs First data from a small pilot study on this issue gained some attention in February 2003. The results showed that it might even be possible to simplify a failing regimen if no other options are available (Deeks 2003). 15 patients failing therapy and without further treatment options stopped only their protease inhibitors, and continued with nucleo-side analogs. Only 2 of the 15 patients had a viral load increase of more than half a log by week 24. Results from one of our own patients (we now have several) where this approach has now been successful for many months are shown in Table 9.3. Resistance testing after more than one year showed, as in the Deeks cohort, that there were no...

Future Prospects In Olfactory Genetics

Pseudogenes, nonfunctional copies of genes, have been considered always as molecular relics with no effect on human traits. Therefore, they have been attributed always to the neglected genomic majority of non-coding junk DNA. With the completion of the human genome sequencing, it became clear that pseudogenes are comparably distributed in our genome as coding genes (73,74). Consequently, there is a higher interest in improving the pseudogene annotation in the human genome and in studying their functional roles (75). In this realm, the special evolutionary state of the human OR gene family where many members exist at the border between functional genes and nonfunctional pseudogenes provides an unusual opportunity to explore the effect of pseudogene accumulation to human fitness. Finding the phenotypic correlates of segregating pseudogenes in the human olfactory system could shed new light on the function of pseudogenes in the human genome.

Additional Pathways That Impact Replicative Aging

Several additional genes have been suggested to play a role in replicative life-span determination that cannot be easily ascribed to the relatively well-characterized pathways discussed thus far. Many of these genes affect aging in a strain-specific manner, and their relevance is uncertain. This class includes RTG1, RTG3, LAG1, LAG2, and RPD3 (Kaeberlein and Kennedy, 2005). Others, such as SGS1, DNA2, and ATP2, shorten life span when mutated, which could be due to accelerated aging, but this effect is most likely the result of a nonspecific reduction in fitness. Several reviews present a more comprehensive analysis of the aging phenotypes associated with these strain-specific modifiers of life

STI in Multidrug Resistance

This shift is particularly pronounced in modestly immunosuppressed patients. The time to shift is increased in more advanced stages of disease and with a longer duration of treatment (Miller 2000, Izopet 2000). PI mutations are the first to disappear, while NNRTI mutations are the most protracted NNRTIs probably impair viral fitness less than other antiretroviral drugs (Deeks 2001, Birk 2001). It is assumed that the wild-type merely dominates the resistant mutants. Special PCR methods are still able to detect low quantities of resistant viruses during STI (Izopet 2000), and after treatment is restarted, resistance mutations rapidly dominate again (Delaugerre 2001). Only a few cases have been described in which resistance mutations were apparently flushed out completely. One such patient, from Erlangen, Germany, has been described (Walter 2002), who was not able to attain sufficient viral suppression despite intensified HAART, and who then interrupted treatment. During the following...

Health Maintenance And Disease Prevention

Even in old age, there are many things that can be done to maintain a reasonably healthy state and consequently continue to enjoy life. Among the recommendations for adding both years to life and life to years are to maintain physical fitness and positive wellness by proper exercise, nutritional awareness, effective stress management, and refraining from or reducing cigarette

Macroevolution and the Fall of Goldschmidt

Aside from the problems of Goldschmidt's mechanism of the rise of novelties, his ideas of spread and speciation also were not well received. The arguments against the spread of novel and extreme variants appearing only rarely had been well understood by then and have been subsequently amplified. Rare variants tend to become extinct very rapidly. Dramatically different mutations are most likely of low fitness relative to the population mean phenotype (Fisher 1930). Relative to extreme phe-notypes, mutants of less extreme form are much more common and therefore contribute in greater proportion to a population's evolutionary potential (e.g., H. J. Muller 1949).

Other Genetic Program Parameters

We used many standard tree operators to grow, mutate, and express new formulae from good fitness candidates. We experimented with a wide variety of operators and found that the simplest crossover and mutation operators provided very good results. Termination Conditions, including the Number of Generations, Fitness Tolerance, and Fitness Invariance Over Time The genetic programming results seemed fairly insensitive to the number (probability) of mutations and crossovers, contrary to most literature that we've read. We did find that there were some reasonable levels that allowed convergence with fewer generations it turns out they were awfully close to the genetic program library defaults. The population sizes and number of demes certainly had impact on the diversity of the initial formulae that were built - generally the higher the better if you have time. Migration wait is basically a parameter that controls how long the demes will act independently of other demes before local best...

Iiis Obesity Preventable

Attempts to reduce the rising rates of obesity and poor physical fitness in Singapore appear to have been successful, at least in the short term. Intensive programs of physical training and influence over dietary intake resulted in a significant reduction in the number of schoolchildren being classified as overweight between 1992 and 1995 (9). Studies of young men inducted into the Singapore army also showed improvements in mean BMI during their periods of service, which unfortunately are reversed when they are released from the military.

Learning About Lifespan Evolution From S Ratti

As a consequence, populations experiencing higher extrinsic mortality will accumulate such late-acting deleterious alleles, which cause aging. If alleles are pleiotropic, and capable of producing phenotypic effects at different time in an animal's life, there may be selection for alleles which enhance fitness due to early effects, despite later deleterious effects (antagonistic pleiotropy).

Why Are Freeliving S Ratti So Very Short Lived

One remaining oddity of S. ratti is that the free-living adults are really very short-lived, even by the standards of short-lived free-living nematode species. There are several possible explanations for this. First, the free-living adult phase of the life cycle is facultative (Viney, 1996). Hence when it does not occur, this may weaken selection on lifespan in the same manner as high extrinsic mortality. Second, it might result from antagonistic pleiotropy between the effects of genes on fitness in the free-living and parasitic forms. Aging may reflect action of alleles that increase early-life fitness (e.g., by increasing reproductive output) but have deleterious late-life effects (Williams, 1957). Such antagonistic pleiotropy is supported by experimental investigation (Kirkwood and Austad, 2000 Partridge and Gems, 2002). Hence, in the case of S. ratti, the short life of the free-living adults may result from the greater fecundity of the parasitic female, which may favor pleiotropic...

Post Genetic Programming Portfolio Simulations

The penultimate step to final implementation of the new model was to backtest (or simulate) the newly found model in a full portfolio construction context. Recall that our genetic program's fitness function was only a proxy for this final, more involved step. Using our judgment, we produced results that were somewhat out of sample (though not completely out of sample due to data limitations). This process is similar to what we'd do in our more traditional factor testing approach.

Selection And Demographic Experiments

Williams proposed antagonistic pleiotropy as an explanation for the evolution of aging (Williams, 1957). According to the theory, the declining force of selection with age results in selection for pleiotropic genes that enhance fitness early in life but reduce it later. The accumulation of many such genes could result in a deterioration of condition with age. This hypothesis became a driving force for most evolutionary studies of aging. Current research on the topic is less explicitly genetic, referring more to ''trade-offs'' than ''pleiotropy'' a recognition that constraints may come from physiological, developmental, or even behavioral conflicts.

Causes and symptoms

Prevalence of Type II diabetes in American society and for the appearance of Type II diabetes in children, previously a rarity. Because obesity promotes degenerative disease of joints and heart and blood vessels, it increases the need for some surgical procedures. At the same time, surgical complication rates are higher in obese patients. Obesity contributes to fatigue, high blood pressure, menstrual disorders, infertility, digestive complaints, low levels of physical fitness, and to the development of some cancers. The social costs of obesity that include decreased productivity, discrimination, depression, and low self-esteem, are less easily described and measured. Worldwide, obesity has reached epidemic proportions in the last thirty years, affecting both sexes and all ethnic, age, and socioeconomic groups. More than 50 of adults in the United States currently fall into overweight or obese classifications, and 22 of preschool children are classified as overweight. The increasing...

Measures of Brain Dynamics Functional Connectivity

As many of the structural studies reviewed in the previous section illustrate, brain networks (like other biological networks) are neither completely random nor completely regular. instead their local and global structure exhibits significant departures from randomness. A key question concerns how these nonrandom features of brain structural connectivity relate to brain function or dynamics. A consideration of brain evolution may guide our answer. In the course of evolution, brain connectivity is one of the prime substrates, the gradual modification of which in an adaptive context contributes to enhanced fitness and survival. Biological structure function relationship often become more comprehensible when viewed in the context of evolution, for example when we consider the structure and function of proteins, cellular organelles, or entire body plans. The evolutionary history of the primate and especially human brain may ultimately hold the key for understanding the structural basis of...

Mechanisms of resistance

Which are selected for early in the process of resistance to one drug and which are located within the active site of the target enzyme, the HIV protease. They reduce the ability of the protease inhibitor to bind to the enzyme. Major or primary mutations may also lead to reduced activity of the protease. Minor or secondary mutations are located outside the active site and usually occur after primary mutations. They compensate for the reduction in viral fitness caused by primary mutations (Johnson 2004). However, the differentiation of primary and secondary mutations can only provide an approximate estimation of the degree of resistance. Fusion inhibitors differ from NRTIs, NNRTIs and PIs, which block the replication of HIV in the infected cell. Instead, fusion inhibitors prevent HIV from entering its target cells. The first step in cell entry occurs when the HIV envelope glycoprotein, gp120, binds to the CD4-receptor and the chemokine co-receptors, CCR5 or CXCR4, of the target cell....

Spreading of the GMO in the Environment

What is the degree of invasiveness of conventional crops, and can transgenic traits increase the potential of survival in non-cultivated surrounding areas or as volunteers on the same plot Many GM crops developed today carry herbicide tolerance as a new trait,which is not expected to increase the fitness of the plants in the absence of the selecting factor, i.e. the respective herbicide. The situation might be different when new traits such as increased tolerance to dryness, salt or a reduced need for nutrients are developed (see also Sect. 2.5.3).

Stress Resistance And Extended Longevity

It has long been observed that mild or nonlethal stress often has the apparently paradoxical effect of benefiting the organism by increasing its longevity (Minois, 2000). Conversely, it has also been suggested that all long-lived strains and mutants exhibit some form of stress resistance (Parsons, 1995 Johnson et al., 1996). This relationship is thought to reflect the fact that their natural environment usually exerts substantial, albeit variable, stresses on organisms. Evolutionary considerations of Darwinian fitness will thus impose a premium on genotypes conferring metabolic efficiency and stress resistance (Parsons, 1997, 2003). The magnitude of the effects of stress resistance on longevity are summarized in Table 25.3.

Interpretation of genotypic resistance profiles NRTIs

For several NRTIs, such as lamivudine, and for NNRTIs, a high degree of resistance can develop following only a single mutation (Havlir 1996, Schuurman 1995). For this reason, such drugs should only be used in highly effective regimens. However, the lamivudine-specific mutation, M184V, also reduces viral replication capacity (often referred to as reduced viral fitness) by 40 - 60 (Sharma 1999, Miller 2003). After 52 weeks with lamivudine monotherapy, the viral load remained 0.5 log below the initial levels despite early development of the M184V mutation (Eron 1995). When compared to treatment interruptions, continuous monotherapy with 3TC delays virological and immunological deterioration (Castagna 2004).

Toward Automated Design Of Industrialstrength Analog Circuits By Means Of Genetic Programming

Circuits) and has also generated two patentable new inventions (controllers). There are seven promising factors suggesting that these previous results can be extended to deliver industrial-strength automated design of analog circuits, but two countervailing factors. This chapter explores the question of whether the seven promising factors can overcome the two countervailing factors by reviewing progress on an ongoing project in which we are employing genetic programming to synthesize an amplifier circuit. The work involves a multiobjective fitness measure consisting of 16 different elements measured by five different test fixtures. The chapter describes five ways of using general domain knowledge applicable to all analog circuits, two ways for employing problem-specific knowledge, four ways of improving on previously published genetic programming techniques, and four ways of grappling with the multi-objective fitness measures associated with real-world design problems.

Number of Yeast Genes

Figure 6.13 Measuring fitness of deletion strains of S. cerevisiae in galactose medium. Strains numbered from 1 to 12 were grown together in the same tube. The growth of each strain was quantitated by quantifying the barcodes associated with each mutant using an oligonucleotide array (microarray) as described in the text. (From Glaever et al. (2002).) Figure 6.13 Measuring fitness of deletion strains of S. cerevisiae in galactose medium. Strains numbered from 1 to 12 were grown together in the same tube. The growth of each strain was quantitated by quantifying the barcodes associated with each mutant using an oligonucleotide array (microarray) as described in the text. (From Glaever et al. (2002).)

Improving Techniques Of Genetic Programming

First, our earliest work on the automatic synthesis of circuits (Koza, Bennett, Andre and Keane 1996) employed the VIA function to connect distant points in a developing circuit. However, a connection could be made only when the circuit-constructing program tree contained two (or more) appropriately coordinated VIA functions. The PAIR_CONNECT function (Koza, Bennett, Andre, and Keane 1999) eliminated this shortcoming. Nonetheless, both the VIA and PAIR_CONNECT functions were brittle in the sense that they were easily disrupted when crossover was performed on the circuit-constructing program trees. The premise behind the crossover operation in genetic programming (and the genetic algorithm) is that an individual with relatively high fitness is likely to contain some local substructures which, when recombined, will (at least some of the time) create offspring with even higher fitness. In genetic programming, the conventional crossover operation recombines a subtree from one parent's...

Monogamy in mammals

Monogamous social structures among mammals, which is estimated at 3-5 (Kleiman, 1977). Those rare cases of monogamous social structure among mammals appear to reflect harsher environmental conditions where pair bonding and paternal care increase reproductive fitness (Emlen and Oring, 1977). Therefore, for a species to be monogamous, something in the neurobiology of social behavior has to change dramatically. Monogamy, even though rare, has emerged multiple times across diverse mammalian taxa. The repeated appearance of monogamous social structure in distantly related taxa and the diversity of social structure among closely related species suggest that these dramatic changes in underlying neurobiology must happen rapidly, independently, and perhaps reversibly.

Health promotion and the cult of the body

This is a reference to the near-obsessional interest displayed by many individuals in the Western world concerning personal appearance and body management. Prost cites increases in concern with personal hygiene, physical fitness and healthy eating as evidence of the development of such a cult.43 The consequence of all of this, he notes, is that the body Increased interest in the body leads to increased concern with threats to the body. Arguably, the most consistent and persistent of threats is illness. Not surprisingly, therefore, concerns about ill health have escalated in recent times,45 to such an extent that the promotion of health and wellbeing has become of paramount importance. Of course, the health of individuals is of importance to all societies, but it is with unwavering conviction that Western states place the pursuit of health as primary among the prerequisites of a good life. Further, health has come to mean, not just the absence of illness, but the attainment of a state...

Repeat Liver Resections

Various studies have looked at the predictors of outcome after repeat liver resection (39,41). Petrowsky et al. (40) identified the number (1 vs. > 1) and largest tumor size (> 5 vs. < 5 cm) of the hepatic tumors as independent risk factors related to the second liver resection. Interestingly, no tumor factor related to the first resection predicted outcome after repeat resection. Thus, in selecting patients for repeat resection, medical fitness, ability to remove all diseases, and long disease-free interval are the most important criteria for consideration.

Avian Immunosenescence In The Wild

The physiological declines associated with senescence, including declines in both innate and acquired immune defenses against parasites and pathogenic microorganisms, have been thoroughly documented in laboratory animals and humans (Wollscheid-Lengeling, 2004). But the fitness deficits associated with advancing age in the wild, where animals experience a full range of natural hazards, stresses and diseases, are far less well understood (Miller, 1996). Recently, reliable aging-related declines in aspects of either cellular or humoral immunity have been reported in wild populations of several bird species, including barn swallows (Hirundo rustica), collared flycatchers (Ficedula hypoleuca), and ruffs (Philomachus pugnax) (Saino et al., 2003 Cichon et al., 2003 Lozano and Lank, 2003).

Avian Models Of Extremely Slow To Negligible Reproductive Aging

Wild seabirds, including gulls, albatrosses, fulmars and terns, typically exhibit little or no loss of reproductive fitness even at the end of their natural life spans in nature (> 50 yrs for some fulmars), and even when rising mortality rates suggest significant deterioration of other physiological systems. Since few seabirds have been maintained in captivity, it remains unclear how long the postreproductive life spans might be for these species if their natural life spans could be prolonged in captivity. Terns (order Charadriiformes), for example, have an extreme life-history strategy typical of pelagic seabirds, characterized by slow sexual maturation, low lifelong reproduction rates (2-3 chicks fledged per year), long life spans, and very slight to negligible declines in reproductive success after peak fledging success is reached at about 15 yrs (Nisbet et al., 1999 Nisbet, 2002a,b). This kind of very sustained reproductive investment is thought to have evolved only in animal...

Sustainable Genetic Programming Based on the Hierarchical Fair Competition Model

Standard genetic programming has a strong tendency toward premature convergence of the GP tree structures, as illustrated by the visualization of GP tree populations by Daida et al. (Daida et al., 2003), which can be partially explained by the loss-of-exploration-capability hypothesis (Hu et al., 2003). In this work, we employ QHFC-GP, an improved version of the sustainable genetic programming method, HFC-GP, as introduced in (Hu and Goodman, 2002). The basic idea of the HFC artificial evolution model (HFC) for sustainable search is that evolutionary search needs to be sustained by continuously incorporating new genetic material into the evolving pool and by keeping lower-and intermediate-level evolutionary processes going on all the time, rather than relying only upon survival of the fittest. The strategy of HFC is to stratify the population of standard genetic programming into cascading fitness levels and to put a random individual generator at the bottom fitness level. In this way,...

Evolving Robust Analog Filters by QHFCGP

The typical approach for evolving robust designs is to use multiple Monte Carlo samplings with different environmental or system configurations to calculate an average fitness for a given candidate solution. One speciality of evolving robustness in genetic programming is that solutions evolved in GP are grown by a developmental process and the robustness of early intermediate individuals does not necessarily imply the robustness of the final solutions. But if the robustness is only evaluated after the fitness of the population reaches a high level, standard genetic programming has difficulty coming up with much variety in the space of solutions, because of convergence of the GP tree structure. The The fitness evaluation for top-level individuals is as follows

Experiments and Results

As mentioned above, two types of robustness are examined. One is the robustness with respect to (w.r.t.) variation of parameter values of the components in the system the other is the robustness with respect to failure of components, which in our case is simply modeled as removal of the components from the system. The perturbation of the component values during evolution is implemented by perturbing all component parameters with Gaussian noise with mean n at 0 and standard deviation a at 25 of parameter values. The failure of components during evolution is implemented by disconnecting a uniformly selected number (between 1 and 5) of components randomly from the systems. The number of Monte Carlo samplings for fitness evaluation of each individual with respect to parameter and topology perturbation is set as SPI 10. The robustness of an evolved solution w.r.t. parameter perturbation is evaluated against a series of perturbation magnitudes Gaussian noise N( j,, a) with mean at 0 and...

Analog Filters with Different Topologies Have Different Noise Robustness and Fault Tolerance Capability

In this experiment, ten analog filters with approximately equal functional performance but with different topologies are evolved, each with 2,000,000 evaluations without incorporating a robustness criterion in the fitness function (9.1). We then choose two filters, one complex solution with 52 components and one compact solution with only 23 components, to test their capabilities for fault tolerance and noise tolerance over the degradation or variation of the component parameters with different perturbation magnitudes. As described above, the evaluation of robustness w.r.t. parameter perturbation is conducted by running 5000 samplings of the configurations of the perturbations. The robustness w.r.t. component failures is evaluated with only 100 samplings as topological robustness is much more complex to evaluate. The reason is that topology modification usually leads to dramatic degradation of functional performance or leads to invalid physical system models, which can be checked out...

Evolving Robustness to Component Failure

In the following experiments, we try to evolve a robust analog filter that can tolerate the failure of its components and has graceful performance degradation. The running parameters are the same as stated in the beginning of this section. Remember that because a significant portion of the topologically perturbed systems are causally ill-posed and can not be simulated with our simulator, the final fitness of the solutions (and the resulting conclusion) is much less reliable than that in the previous subsection. Topology perturbation during evolution is applied by removing a uniformly chosen number (between 1 and 5) of components from each candidate solution for 10 samplings. The evolved filter, in bond graph form, is shown in Figure 9-7 and the performance degradation levels are illustrated in Figure 9-6 (b). Comparing Figure 9-6 (b) with Figure 9-4 (b), it is clear that a more fault-tolerant filter has been evolved. Removing 3 faulty components, the robust solution can still achieve...

Broad etiological groups

Non-disjunction of homologous chromosomes is the commonest mechanism leading to trisomies 13, 18 and 21 in humans. Post-zygotic loss of either an X or a Y chromosome leads to Turner syndrome which is characterized by a variety of cardiac, urological, skeletal and endocrine defects. More recently a host of disorders have been identified that are caused by recurrent stereotypic deletion of segments of DNA, mediated by long complex flanking repetitive sequences. Examples of these disorders include 22q11 deletion syndrome, Smith Magenis syndrome (chromosome 17p11.2) and Angelman Prader-Willi (chromosome 15q11) syndromes. These contiguous gene deletion syndromes have been labeled ''genomic disorders'' in recognition of both the size and the recurrent deletional mechanism that leads to their appearance (Inoue and Lupski, 2002). It is possible that smaller stereotypic chromosomal deletions may underlie other as yet uncharacterized disorders, especially those that involve genes encoding...

Sulfur In Plant Physiology

The sulfur requirement varies strongly between species and it may fluctuate during plant growth. The sulfur requirement can be defined as 'the minimum rate of sulfur uptake and utilization that is sufficient to obtain the maximum yield, quality, and fitness,' which for crop plants is equivalent to 'the minimum content of sulfur in the plant associated with maximum yield' and is regularly expressed as kg S ha1 in the harvested crop. In physiological terms the sulfur requirement is equivalent to the rate of sulfur uptake, reduction, and metabolism needed per gram plant biomass produced over time and can be expressed as mol S g_1 plant day1. The sulfur requirement of a crop at various stages of development under specific growth conditions may be predicted by upscaling the sulfur requirement in imol S g_1 plant day1 to mol S ha1 day1 by estimating the

Multiallelic balancing selection

Takahata (1990) developed such a theory with the major histocom-patibility complex in mind, but the theory is easily extendable to self-incompatibility systems as well. We assume symmetrical, balancing selection where all homozygotes have fitness 1 s and all heterozygotes have fitness 1. Some self-incompatibility systems can be modelled by setting s 1 (Vekemans and Slatkin 1994). Because of the strong balancing selection, Takahata assumed that a fixed number of different alleles, k, are being maintained at equal frequencies, 1 k. This fixed number is the number of common alleles at mutation-selection-drift equilibrium. Sometimes an allele is lost by genetic drift and sometimes a new specificity arises by mutation and invades the population and quickly attains its equilibrium frequency if it is not lost by genetic drift immediately. Takahata approximated this allelic turnover process by assuming that with intervals determined by the average allelic turnover time a random allele is lost...

Experimental Methods Experiments

Our first experiment forces a design on the evolutionary process by fixing the root node throughout the evolutionary process. In each of the experiments a different function is chosen to be the root node. It is fixed in the initial population and is not allowed to change either through mutation or crossover. In order to ensure significant results 500 trials are performed with each nonterminal function as the root. We then average the fitness of the best individual in each trial and define the function that generates the highest average fitness as the optimal root node and the best top-down design. The root node that produces the best performance in this experiment is assumed to represent the best initial design decision.

Resection Specimens

Neck dissection is either elective (clinically negative neck) or therapeutic (known metastasis). Justification for an elective neck dissection rests on three observations occult disease will develop into clinically evident disease, sometimes inoperable when eventually detected there is a risk of distant metastasis with untreated occult neck metastasis and additional histological information of prognostic value may be gained. Arguments against elective neck dissection include unnecessary treatment when there is a low risk of metastasis and significant morbidity and a risk of mortality in elective surgery. The decision to perform an elective neck dissection is based on a risk of metastasis of more than 20 , whether or not the neck nodes can be easily assessed clinically, the availability of the patient for close follow-up and the fitness of the patient for surgery. Sentinel node sampling is being developed as a technique to identify occult metastasis but requires considerable...

The Function of Free Standing Endonucleases

Selfish genetic elements are not commonly thought of as providing either a selective benefit or burden to a host genome, but are considered to be phe-notypically neutral with respect to host fitness (Doolittle and Sapienza 1980). This assumption is supported by the experimental observation that none of the characterized homing endonucleases of phage T4 are essential phage carrying mutations in the endonuclease genes are viable and do not exhibit reduced burst size or altered plaque morphology as compared to wild-type phage, a result likely to hold true for the remaining uncharacterized endonucleases in T4. In the absence of an apparent selective advantage for the retention of a mobile element gene in the host genome, mobile endonucleases will

Discussion and Conclusions

In both of these cases the fixing of the root node can be viewed as an example of partial premature convergence the population converges on a particular function for the root node without sufficient exploration to determine if that is the ideal root node. However, unlike a GA where prematurely fixing a bit can have significant affects on fitness, GP appears to be fairly adept at finding a near optimal solution even when a poor choice is made for the root node. An alternative, and more ad hoc approach, would be to begin with a very large population. This would improve the GP's sampling of the root node choices and may make it more likely that the population will converge on the optimal root function. After the population begins to converge, the population size would be reduced to more typical values. However, if design complexity were to increase linearly, it is expected that the population size would need to increase exponentially to be as effective. Another possibility would be to...

The Pneumococcal Cell Surface

This family of pneumococcal surface proteins are anchored to the cell wall by covalent linkage to peptidoglycan via a carboxy-terminal motif, LPXTG. This motif is recognized by a sortase enzyme, which links the threonine residue of the motif to the cell wall. Analysis of the pneumococal genome sequence (Tettelin et al., 2001) reveals a family of these proteins including hyaluronidase and neur-aminidase enzymes. Hyaluronidase breaks down the hyaluronic acid component of mammalian connective tissue and extracellular matrix and is secreted by 99 of clinical isolates of pneumococcus (Humphrey, 1948). Deletion of the hyaluronidase gene alone does not affect virulence in a mouse model of infection but deletion of hyaluronidase in a pneumolysin-negative background reduces the virulence of the pneumolysin-negative mutant (Berry and Paton, 2000). Neuramindase cleaves N-acetylneuraminic acid from glycolipids, lipoproteins and oligosaccharides on cell surfaces and in body fluids (Camara et al.,...

Assessment for Underlying Risk Factors

Sedentary life habits are a major underlying risk factor for both cardiovascular disease and type 2 diabetes (22). The detection of physical inactivity can be assessed in two ways (1) by history, and (2) by detection of cardiovascular fitness. Since the recommendation for physical activity calls for 30 min of moderately intense activity daily, lesser amounts of activity constitute varying degrees of physical inactivity. Some investigators contend that quantitative measures of cardiovascular fitness through exercise testing provide a more reliable indication of physical activity status with respect to future cardiovascular risk this advantage, however, has not been proven with certainty (23).

Linear GP with Sequence Generators

Here we shall use 3-address machine instructions. The genotype of an individual is a list of those instructions. Each instruction consists of an operation, a destination register, and two source registers . Initially, individuals are produced by randomly choosing instructions. As is usual, we employ a set of fitness cases in order to evaluate (and subsequently select) individuals.

A register machine as an Algorithmic Chemistry

It should be noted that there are registers with different features Some registers are read-only. They can only be used as source registers. These registers contain constant values and are initialized for each fitness case at the start of program execution. All other registers can be read from and written into. These are the connection registers among which information flows in the course of the computation. Initially they are set to zero.

Regression Sine Function Approximation

Approximation of a sine function with non-trigonometric functions is a nontrivial but illustrative problem. The set of fitness cases V (xi,j i), ( 2> 2 2), , (xn, yn) is created in the following way In the interval 7r, 7r random values Xi are used to calculate values yt sin(xi), i e 1,2, , n . Given a subset V' of the training set V, the fitness function is the mean squared error of the individual I applied to all fitness cases of the subset (x, y) denotes a fitness case in the subset V' of size V' , x the input and y the desired output.

Classification Thyroid Problem

The thyroid-problem is a real world problem. The individual's task is to classify humans thyroid function. The dataset was obtained from the UCI-repository (Blake and Merz, 1998). It contains 3772 training and 3428 testing samples, each measured from one patient. A fitness case consists of a measurement vector containing 15 binary and 6 real valued entries of one human being and the appropriate thyroid function (class). classification error is the percentage of misclassified dataset. We use the classification error as our fitness function.

Visualization of an Algorithmic Chemistry

The result register of this AC is register 11 shown at top left. Just one instruction is doing a write access on this register. It is a subtraction available six times in this AC. One of its source registers is register 29 of the register set that just allows read access. While the first 21 Registers in this set contain the inputs of the fitness case, the others contain evolved constants. The second input is a writable register (numbered 26). At this point of time in evolution there is also just one write access to this register. Here it is another subtraction available three times in this chemistry. It subtracts two values of the fitness case.

The attachment dynamic and systemic thinking

Whilst being relatively stable over time, the family also needs to be change to allow for developmental progress and crisis situations. Families differ in their degree of flexibility (Olsen et al., 1988) and that will determine the ability to cope with change. Folkman (1984) has categorised the resources needed by the family under three headings material (relating to the economic resources), physical (which are to do with health and fitness) and social (to include practical and emotional support within the family and wider system). The task for the family is how to collaborate to manage stress, conflict, share emotions and support one another.

Illustrative Experiments

The sake of sorting, trees with fitness values differing by no more than 2 of the fitness range in the population were considered the same on fitness (and thus ordered ascending by size). Moreover, unless otherwise noted, all results are averages of the best of five independent populations while executed with a single set of heuristics.

Varying Iteration Length and Regrow

Fitness growth for iteration 5 generations. Figure 12-16. Fitness growth for iteration 5 generations. Figure 12-17. Fitness growth for iteration 10 generations. Figure 12-17. Fitness growth for iteration 10 generations. Figure 12-18. Fitness growth for iteration 25 generations. Figure 12-18. Fitness growth for iteration 25 generations.

Varying Population and Sampling Sizes

In this section, we empirically study the relationship between population size, sampling rate, and the resulting fitness. All results in this section were obtained with on-line runs (iteration 1 generation). Figure 12-19 illustrates the average fitness of the best individuals from the 5 populations, after 50 generations, as a function of the population size. The top curve is that of a plain GP. As expected, the 50 generations lead to better fitness with increasing population size, due to more trees sampled. ACGP under-performs, but this was expected Figure 12-15 already illustrated that regrow in combination with iteration l is destructive. One other observation is that decreasing effective sampling rate does improve the performance, which was observed especially for the larger populations. Figure 12-19. Average fitness after 50 Figure 12-20. Average fitness after 50 Figure 12-19. Average fitness after 50 Figure 12-20. Average fitness after 50 Figure 12-20 presents the same fitness...

The Question of Donor Cell State

Whether stem cells contribute preferentially to the production of clones that develop to term could affect conclusions derived from the study of cloned progeny. Stem cells can differ from differentiated cells in fundamental respects such as the number of past rounds of cell division, telomere length, and telomerase expression. Because reprogramming is slow, these phenotypic differences between stem cells and differentiated cells will likely persist to some degree in cloned embryos. Thus, conclusions regarding somatic mutation load, mitochondrial fitness, and replicative potential of the genome as reflected in telomere length in the context of cloned embryo and cloned stem cell derivation need to account for possible effects of donor cell state.

Lessons Learned Using Genetic Programming In A Stock Picking Context

Abstract This is a narrative describing the implementation of a genetic programming technique for stock picking in a quantitatively driven, risk-controlled, US equity portfolio. It describes, in general, the problems that the authors faced in their portfolio context when using genetic programming techniques and in gaining acceptance of the technique by a skeptical audience. We discuss in some detail the construction of the fitness function, the genetic programming system's parameterization (including data selection and internal function choice), and the interpretation and modification of the generated programs for eventual implementation. Key words genetic programming, stock selection, data mining, fitness functions, quantitative portfolio management.

Using Genetic Programming To Search For Supply Chain Reordering Policies

Abstract The authors investigate using genetic programming as a tool for finding good heuristics for supply chain restocking strategies. In this paper they outline their method that integrates a supply chain simulation with genetic programming. The simulation is used to score the population members for the evolutionary algorithm which is, in turn, used to search for members that might perform better on the simulation. The fitness of a population member reflects its relative performance in the simulation. This paper investigates both the effectiveness of this method and the parameter settings that make it more or less effective.

Genetic programming parameters

Selection method The three choices that we test are tournament, fitness proportionate, and rank. For the tournament method, two agents are selected for the tournament the agent with the lower (better) score wins and is selected for the next generation. The more fit against the current demand instantiation is guaranteed to win but it is still the case that fitness against

Rearrangements Related to Classical Deletions

Ironically, although the gr gr deletion may not be in mutation selection balance, the AZFc deletion characterized by the same authors provides a clear example of such a balance. The incomplete penetrance of the AZFc deletion leads to its infrequent but recurrent transmission from father to son (see The AZFa Deletion) and results in the AZFc deletion reaching a population frequency higher than its de novo mutation rate, but being kept in check by the deletion's substantial fitness costs.

AZF Genes and Spermatogenic Failure

Independent replication of the association study between gr gr deletions and spermatogenic failure is needed, and further work should identify the deletion breakpoints and thus the individual members of gene families that are lost. In addition, more thorough investigation of the effect of the common partial deletions within AZFc on spermatogenesis is desirable, taking into account both the phylogenetic background and any associated duplications. Lineages Db2 and N would be of particular interest. Population genetic approaches might also provide information have these lineages experienced negative selection and expanded less rapidly than expected for a neutral lineage Methods that compare the age of a lineage with its frequency and determine whether the observed pattern is compatible with neutrality (33,34) could be used to address this question. If some partial deletions are associated with fitness costs, these might indicate the underlying selective pressures that have operated to...

Cartesian Genetic Programming

When Cartesian genotypes are initialised one finds that many of the nodes are inactive. In many CGP implementations on various problems it is often found that this figure changes relatively little. Thus it is clear that during evolution many mutations have no effect on the phenotype (and hence do not change the fitness of the genotype). We refer genotypes with the same fitness as being neutral with respect to each other. A number of studies (mainly on Boolean problems) have shown that the constant genetic change that happens while the best population fitness remains fixed is very advantageous for search (Miller and Thomson, 2000, Vassilev and Miller, 2000, Yu and Miller, 2001, Yu and Miller, 2002). In the results section of this chapter we will show that such neutral search is also highly beneficial for the ligand docking problem. To date no work on CGP has required any action to deal with bloat. Bloat is not observed even when enormous genotypes are allowed. Miller (Miller, 2001)...

Evolutionary Algorithm

2 Evaluate fitness for each individual in the population (a) If there are offspring that have a better fitness than the parent has, the best offspring becomes the winner. (b) Otherwise, if there are offspring which have the same fitness as the parent then one is randomly selected and becomes the winner (NDEA) If this is done, the only way a genotype can supplant its parent is by having a superior fitness. Some have argued that allowing neutral drift is equivalent to using a higher mutation rate in an EA (Knowles and Watson, 2002). In results later we show empirically that this is not the case for the problem studied here, this accords with previous work reported on Boolean problems (Yu and Miller, 2001).

Experiments Comparing NDEA vs EA

In the next set of experiments (Figures 14-5) we compare the performance of the evolutionary algorithm with and without neutral drift and also the behaviour of both scenarios with varying amounts of mutation. It is immediately clear that at mutation rates below 0.3 NDEA is superior to the EA. With high mutation rates (> 0.3) the behaviour of the two algorithms is similar both in fitness and program size. Fitness stagnates at about 12 and program size randomly varies around 22 active nodes (out of 200). The behaviour of the NDEA when the mutation rates are much lower is very different. Firstly we see a continuous improvement in fitness with time which is still growing after 10,000 generations. Secondly the improvement in fitness is accompanied by a steady growth in program size. It is interesting that the optimal mutation rate also produces the strongest growth in active code. The rate of code growth drops eventually. This indicates that if evolution was continued longer the active...

Application of NDEA over Docking

In the initial implementation of CGP for the docking problem, a series of experiments were conducted in which system parameters such as the structure of the matrix, mutation rate, etc. were varied, although not in such detail as the experiments shown in sections 4 and 5. At that time it was not possible to conduct very rigorous tests because of the severe time restrictions associated with the business environment, although another reason was caused by this being a classification problem. The fitness function in the CGP implementation is based on the result of applying the current filter on the training set. Since we are considering a classification problem, our aim is to maximize the classification accuracy over the test set. Our goal was not to find the global optimum for the training set as this would have almost surely been equivalent to overfitting and would have produced a filter that would have performed poorly over new data. Because of this, once a system capable of finding...

Compensatory mutations

Several researchers (Lenski 1997, Levin et al 1997, Schrag & Perrot 1996) have studied the effects of the acquisition of an antibiotic resistance plasmid, or a mutation conferring antibiotic resistance, on the ability (fitness) of bacteria to survive in competition with wild-type organisms or to tolerate a stressful environment (pathogenesis). It was found that the change from sensitive to resistant had negative effects on fitness in other words, the antibiotic-resistant mutants were enfeebled. However, during prolonged growth of antibiotic-resistant strains, variants arose spontaneously that were as fit as the wild-type strains without a change in the resistant phenotype. This restoration of fitness was due to compensatory mutations occurring intra- or extragenically with It is reasonable to ask if the same situation applies to mycobacteria do streptomycin-resistant and rifampicin-resistant strains of M. tuberculosis isolated during the course of infection possess both target...

Parental investment and sexual selection

Lactation is a classic example of parental investment in mammals, since it is commonly associated with a cessation of normal reproductive function in the female (e.g., lactational amenorrhea) and requires considerable energy resources and potential health risks (e.g., insulin resistance). This is an issue of costs and benefits. Increased time and energy invested in lactation might increase the growth and survival of an individual offspring, perhaps enhancing the ability to compete for resources and the opportunity for successful reproduction. But these outcomes are achieved at the cost of limiting the ability to produce subsequent offspring. A critical issue is whether increased parental investment within the environment in which reproduction is occurring will actually enhance reproductive fitness in the offspring. Parental investment in the young comes at the cost of future opportunities for mating. Importantly, this cost benefit equation commonly has different implications for males...

Post Processing Analysis

2.1.2 Fitness Traces A fitness trace is a plot of the fitness of the current frontrunner over time. An example of a fitness trace is shown in Figure 15-2. The fitness is the accuracy of the rule in predicting a sample's class membership with perfect being 1.0. The top line shows the fitness of the best individual from the training set. The bottom line is the fitness on the same individual when calculated on the test set. Figure 15-2. Example Fitness Trace Figure 15-2. Example Fitness Trace

Life history and reproduction

Evolutionary theory defines the ultimate challenge of life as that of maximizing reproductive fitness. Reproductive fitness is determined by the ability to survive to reproductive maturity, to reproduce, and to rear the offspring to reproductive age. Reproductive success itself is a function of investments in reproductive processes, as well as in growth and survival. Life history theory (Charnov, 1993 Roff, 1992 Stearns, 1992) attempts to define variations in investment strategies across and within species in the manner in which limited energy resources are allocated to the major challenges of life (1) growth and development, (2) maintenance, defense, and survival, and (3) reproduction. Resources are limited. Those allocated in the interest of survival limit investment in reproduction, and so on. The challenge is to establish the most effective investment strategies and the efficacy of the solutions vary as a function of the environment. There is no optimal strategy one size does not...

Box 111 continued

Random genetic drift is a process that occurs in a small population after the founding of that population. As the name indicates, the process is random, that is, it is not due to a fitness advantage or disadvantage. We will demonstrate this with a real-life example of the group represented by Old Order Amish Mennonite Church. This group arose in central Europe during the seventeenth century and began migrating to the United States in the early eighteenth century, predominantly to Pennsylvania and Ohio. Those who espouse the traditional teachings of this church wear plain clothing men wear hats and do not trim beards, while women wear long dresses, capes, and bonnets. They also use horses and buggies rather than automobiles and generally shun modern conveniences. These people stay in relatively small communities and tend to socialize within their groups. The necessary ingredients for observing random genetic drift is present in this situation, a small founding population that tends to...

Strengthening the Exercise Component

Physical activity researchers have shown that it is possible to increase fitness using either supervised exercise or home-based physical activity (62). In weight loss programs, however, home-based programs appear to produce better maintenance of weight loss (Table 6). Andersen and colleagues (25) randomly assigned overweight participants to weight loss programs that involved either three supervised sessions of aerobic dance each week for 16 weeks or home-based activity (goal of 30 min of moderate to vigorous activity most days in the week). Weight losses in the two groups were similar at week 16 (8.3 kg for aerobics and 7.9 kg for lifestyle), but the aerobic dance group regained 1.6 kg from week 16 to 1-year follow-up whereas the lifestyle group regained .08 kg (P .06). Perri and colleagues (24) also found evidence of similar initial weight losses in home-based and supervised programs, but better maintenance of weight loss in the home-based program. Forty-nine obese women participated...

Environmental adversity and sexual maturation

In early life (Belsky et al., 1991 Cameron et al., 2005 Coall and Chisholm, 2003). The rationale for such phenotypic plasticity is that in adverse environmental conditions with high risk and uncertainty, when the probability of extended periods of growth and survival is low, the optimal strategy is to maximize offspring quantity through enhanced mating. Maximizing offspring quantity enhances the chances that at least some offspring will survive to reproductive maturity. Moreover, since such adverse environments are characterized by high, unavoidable risks, parental investment in offspring quality is seen as futile (Coall and Chisholm, 2003). Increased risk of mortality thus favors a shift in parental investment away from offspring quality to quantity (Coall and Chisholm, 2003 Gangestad and Simpson, 2000). In contrast, more propitious environmental conditions favor greater investment in individual offspring at the cost of mating. In more favorable environments, competition for...

Why Worry about Species

In the recognition species concept, species are the most inclusive population of individual biparental organisms that share a common fertilization system (McEvey 1993 Paterson 1985). Paterson believed that Mayr overemphasized isolating mechanisms between species. He argued that species arise as incidental consequences of adaptive evolution entailing individual selection, as opposed to species being adaptations, having coadapted gene complexes that isolate them from other species. Isolating mechanisms would have an advantage in the zone of overlap between incipient species but not otherwise. The cohesive species concept (Templeton 1989) also argues for the importance of cohesive properties of species. This latter notion, however, is consistent with Dobzhansky's ideas of an integrated genotype, fashioned by natural selection, whose fitness would be lowered by cross-breeding with other closely related species.

Comparison of the Four models

A cross-validation approach is used to determine the optimal number of component Gaussians, for each breast type. The determined value of m is then used for all training folds comprising each breast type. To determine the optimal value of m, models with a different number of components are trained and evaluated with a WGMMS strategy, using an independent validations set. Model fitness is quantified by examining the log likelihood resulting from the validation set. Training files are created by taking 200 samples randomly drawn with replacement from each normal and abnormal images for each breast type. For training we use 50 training images per breast type (n 25 normal, n 25 abnormal) giving a training size of 10,000 samples per breast type. Repeating the procedure for 50 remaining validation image per breast type, we get 10,000 samples for validation.

Parameter Estimation for High Level Process

By using the Bayes classifier, we get initial labeling image. In order to run the Metropolis algorithm, first we must know the coefficients of potential function E(x), so we will use GA to estimate the coefficient of E(x) and evaluate these coefficients through the fitness function. Fitness Function Since our goal is to select the high-level process X that maximize Eq. 9.5, we can use Eq. 9.5 as the fitness function. 2. Apply the Metropolis algorithm for each chromosome on each image and then compute the fitness function as shown in Eq. 9.5. 3. If the fitness values for all chromosomes do not change from one population to another population, then stop and select the chromosome, which gives maximum fitness value. (If there are two chromosomes that give the same fitness value, we select the chromosome which represents lower order system.) Otherwise go to step 2.

Health Benefits of Exercise Training with or Without Substantial Weight Loss

Normalization of body weight or body fat content through exercise is not necessary to improve health of obese individuals with metabolic disorders that are thought to be weight related. For example, Lamarche and associates (30) have shown that a 6-month exercise program consisting of four to five weekly 90-min exercise sessions at 55 of VO2max improved metabolic profile of obese women in spite of the fact that these women gained 2.3 kg body weight and 2.8 kg body fat during the same time period. Brown et al. (31) have shown that only seven days of aerobic exercise improved insulin sensitivity and glucose-stimulated plasma insulin levels in obese women. Furthermore, some studies have shown that fitness, rather than fatness, is the determinant for disease and mortality (32-34). Although it is not well understood how fitness and fatness interplay as determinants of health and disease, it is well established in the literature that regular exercise participation will improve the health of...

The Exercise Prescription

Physical fitness is evaluated in terms of body composition ( body fat), cardiovascular capacity (VO2 max), muscular strength and endurance, and flexibility. The ideal would be for all persons to participate in an exercise training program to improve or maintain fitness in each of these categories. However, the majority of Americans do not participate in any type of regular exercise program. To promote the message of increased activity for all Americans, the American College of Sports Medicine (ACSM) and the Centers for Disease Control (CDC) have recommended that every adult should accumulate 30 min or more of moderate-intensity physical activity on most, preferably all, days of the week (35). Moderate activity in this recommendation is defined as activity that elicits an energy expenditure of three to six times resting metabolic rate (3-6 METS). In layman's terms, this means simple activities such as walking, gardening, playing golf, walking the dog as well as incorporating more...

Intraspecific Variation

Fitness is often used interchangeably with adaptedness. Fitness should refer to the relative ability of genotypes to survive and leave offspring. One can also define fitness in terms of alleles at a locus. If we have a locus segregating for two alleles, A1 and A2, let the respective fitnesses be W1 and W2. We can then define a selection coefficient, s, which equals W1 W2 - 1. If p is the frequency of A1 and q is the frequency of A2, then the change in p over one generation will be where w is the mean fitness of the entire population. Changes in allele frequencies are therefore associated with a fitness parameter. This expression is oversimplified and applies to haploid organisms. For a more complete discussion of selection in diploid organisms, see Ewens (1969). The assessment of relative fitness of genotypes at a locus implies a complete randomization of the background genotype (Lewontin 1974). In practice, this is nearly impossible to achieve, given the great difficulty of...

Evolving secondstage detectors

The use of extensive traffic data posed a challenging generalization task (compared to the proof of concept study (Howard and Roberts, 2002) (Roberts and Howard, 2002)). Hence, many GP runs were conducted to investigate the influence of many input parameters on detection performance. Some of these parameters were specific to GP (e.g. population size and tournament size) whereas others were problem specific. The population size was increased to range between 1000 and 32000, and in order to compensate for this with regards to computation time, the maximum number of generations was reduced to 20 (other GP parameters are given in Table 16-4). The most important problem-specific parameters were the fitness variable and the input window dimensions T and S (as explained below). At least 10 runs were conducted for each parameter configuration. Second-stage detectors were trained to have high specificity in preference to high sensitivity in order to minimize the false alarm rate. The fitness...

Validating Second Stage Detectors

Figure 16-6 displays the second-stage performance on validation. The plot shows two clusters of points due to the fact that the fitness variable was set to target for two different false alarm rates on evolution. The false alarm Table 16-6. Performance metrics for the best first-stage and second-stage detectors on validation (unless training is stated). The following evolution metrics are also given generation, fitness rank and size (metric definitions are given in the text). Table 16-6. Performance metrics for the best first-stage and second-stage detectors on validation (unless training is stated). The following evolution metrics are also given generation, fitness rank and size (metric definitions are given in the text).

Conclusion If The Gle Were Judge

As important as it has been, however, seeing is not a specific problem to be solved by organisms, and no environment demands any particular type of vision. Indeed, the presence of various primitive photoreception mechanisms shows that organisms can use light information without having a brain (e.g., primitive organellar vision in unicellular organisms jellyfish). Vision probably also illustrates the role organismal selection may play in nature. Organisms use what they have, and this may sort them out as well as classical darwinian selection does, but without fitness differences.

Curriculum Based Programs

The pressure to devote school time to examinable academic subjects has led to the marginalization of non-examinable activities. Although New York State education laws contain explicit guidelines on classroom time for health education - including sex education, information about HIV AIDS and physical education - there is concern that these goals are not being met (Stringer, 2003). Nationally, too, the amount of school time devoted to physical education is minimal and has declined substantially in the past ten years (Gerberding, et al., 2004). In New York City, efforts are underway to invigorate school-based physical activity and health education programming, with the selection of a single curriculum for each and identification of regional physical education coordinators. The physical activity curriculum includes a fitness report to parents that will allow students and parents to track progress. In aggregate, these data (which include BMI measurements) will allow tracking of program...

Pareto Exploitation User Selection

Of course, the user also benefits from the improved discovery speed and performance (both accuracy and robustness) which result from the algorithmic exploitation of the Pareto front. An example is shown in Figure 17-4 which displays the Pareto front for a biomass inferential sensor (Kordon et al., 2004). Every dot in this graph represents a GP-model with its associated fitness (in this case i.e. lower values are better) and a normalized complexity measure

ParetoGP Algorithm Performance

GP was rarely able to generate any solutions with fitness greater than 0.9 for the 300 runs. In contrast, ParetoGP generated superior results with the maximum fitness exceeding 0.9 for almost every case of a similar set of 300 runs as shown in Figure 17-6. Similar results have been confirmed in a number of other projects (Kordon et al., 2004).

Genetic Algorithm Approach

In this step a fitness function is applied to evaluate the fitness of all chromosomes in the population. The type of fitness function or criterion is determined by the specific applications. Since the main purpose of medical image processing is to improve the diagnostic accuracy, and ROC methodology has become a standard to evaluate the diagnostic accuracy, the areas under ROC curve (Az) are often used as a fitness criterion. Because the fitness function must be applied to assess the fitness level of each chromosome in the population, evaluation is typically the most difficult and computationally costly step. (3) Selection. This step involves rewarding high fitness chromosomes (e.g., the chromosomes that generate high Az value for the classifier) and eliminating the low fitness ones. Thus, using different selection methods, such as roulette wheel selection, tournament selection, and elite selection, the chromosomes with better fitness levels can expand to take up a...

Nonpoultry Domestic Avian Models For Aging Studies

Changes in mortality rates and reproductive success consistent with aging have been documented for many bird populations (Holmes and Austad, 1995 Holmes et al., 2001). Other indications of avian aging in the wild include higher parasite loads in older birds, as well as reduced fitness of offspring produced by aging parents.

Fitting Exercise Into A Busy Schedule

Fitting Exercise Into A Busy Schedule

Fit exercise into your busy schedule? Thats as absurd as saying that there are eight days in a week! First, youve never exercised before or engaged regularly in a sport second, youve never been into the fitness crowd and have had meager time for such pursuits, and third, youre far too busy to even think of exercise.

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