Top PDF The biological and mathematical basis of L systems

The biological and mathematical basis of L systems

The biological and mathematical basis of L systems

The biological and mathematical basis of L systems Christine Kelly-Sacks Follow this and additional works at: http://scholarworks.rit.edu/theses This Thesis is brought to you for free and open access by the Thesis/Dissertation Collections at RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact ritscholarworks@rit.edu.

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Robustness of mathematical models for biological systems

Robustness of mathematical models for biological systems

6 Conclusions For studying the robustness of mathematical models for biological systems, we should address three sources of uncertainty: errors in estimated param- eters; external noise for environmental fluctuations; and internal noise due to small numbers of regulatory molecules. The analysis for each source of uncertainty is the first step in finding robustness properties of mathemati- cal models. It would be very important to search relationships between the robustness properties of each source and the impact of combined sources on mathematical models. The work in this paper is an attempt in this direction.
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Mathematical Basis of Sensor Fusion in Intrusion Detection Systems

Mathematical Basis of Sensor Fusion in Intrusion Detection Systems

Associate Director, Indian Institute of Science, Bangalore India 1. Introduction Intrusion Detection Systems (IDS) gather information from a computer or a network, and ana- lyze this information to identify possible security breaches against the system or the network. The network traffic (with embedded attacks) is often complex because of multiple communi- cation modes with deformable nature of user traits, evasion of attack detection and network monitoring tools, changes in users’ and attackers’ behavior with time, and sophistication of the attacker’s attempts in order to avoid detection. This affects the accuracy and the relia- bility of any IDS. An observation of various IDSs available in the literature shows distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on other classes. The availability of enormous computing power has made it pos- sible for developing and implementing IDSs of different types on the same network. With the advances in sensor fusion, it has become possible to obtain a more reliable and accurate decision for a wider class of attacks, by combining the decisions of multiple IDSs.
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Biological Basis of Emotions: Brain Systems and Brain Development

Biological Basis of Emotions: Brain Systems and Brain Development

Synaptic pruning is not a random phenomenon, but rather is based on activity-dependent stabiliza- tion. In other words, repeated neuronal activity in- volving certain circuits during a critical period will result in stabilization of those circuits rather than in elimination during the pruning process. 30 The advan- tage of activity-dependent stabilization of neuronal pathways is that there will not be an unnecessary expenditure of genes to code precisely for the large number of connections in the brain. Rather, repeated early environmental exposure will serve to guide the molding of an optimum cortical cytoarchitecture for the individual’s future needs. The molecular basis for the stabilization and retention of some pathways and vulnerability of others to be pruned or eliminated is an area of intense investigation. Recent studies have suggested that in the visual cortex of kittens, activity- dependent stabilization may involve activation of the N-methyl-d-aspartate subclass of glutamate recep- tors, associated perhaps with the expression of spe- cific neuronal proteins. 31,32
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Biological Basis Of Deception

Biological Basis Of Deception

Biological Basis Of Deception The broadest definition portrays deception as social behavior in which one individual deliberately attempts to persuade or convince another to accept as true what the deceiver believes to be false. Self-presentation is one of the reasons for lying and people have lied about their emotions and feelings, actions, accomplishments and knowledge (DePaulo, Kashy, &

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The Biological basis of schizophrenia

The Biological basis of schizophrenia

The Biological basis of schizophrenia Franz Sugarman Follow this and additional works at: http://scholarworks.rit.edu/theses This Thesis is brought to you for free and open access by the Thesis/Dissertation Collections at RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact ritscholarworks@rit.edu.

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Ventilation systems failure prediction on the basis of the stochastic 
		branching processes mathematical model

Ventilation systems failure prediction on the basis of the stochastic branching processes mathematical model

Penza State University of Architecture and Construction, Penza, Russian Federation E-Mail: bgrishin@rambler.ru ABSTRACT The article considers a procedure of reliability evaluation of ventilation systems on the basis of controlled stochastic branching processes. The ventilation system under study is presented as a set of four main subsystems-modules interacting in the process of operation. The reliability indicators of functioning of the considered modules are defined, i.e.

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BIOLOGICAL BASIS OF NICOTINE ADDICTION

BIOLOGICAL BASIS OF NICOTINE ADDICTION

Nicotine, the primary component of tobacco produces reinforcing effects both in humans and animals. The neurochemical, anatomical and molecular basis of nicotine dependence is very similar to the other drugs of abuse, particularly the psychostimulants. Nicotine has specific acetylcholine receptors (nAChRs) in the brain and other organs. The stimulation of presynaptic acetylcholine receptors increases trans- mitter release as well as the metabolism. Nicotine, like other drugs of abuse triggers the dopamine reward system and increases the extracellular level of dopamine in nucleus accumbens (NAc), which is thought to be responsible for the reinforcing behavior, stimulant and dependence properties of nico- tine. Nicotine also exerts its effect in the brain on non-dopaminergic structures that may account for its positive rewarding effects and some of the symptoms of nicotine withdrawal. Moreover, the actions of nicotine on many systems, including brain stem cholinergic, GABAergic, noradrenergic, and seroton- ergic nuclei, may also help to mediate nicotine effects related to addiction. Further, the neurochemical pathway to nicotine reinforcement is likely to be due to binding of nicotine to nAChRs containing the β
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3. BIOLOGICAL BASIS TO CRIME

3. BIOLOGICAL BASIS TO CRIME

ideas. It suggested that controlling who could have children (and for the Nazis even killing), would make society a better place. In the first half of the 20th century, in the USA, there were approximately 70 000 sterilisations of mothers with low IQ. By 1931, 27 US states had compulsory sterilisation laws for "feeble- minded", insane and habitual criminals (Gibbs 1995). 5. A biological approach is reductionist ignoring the complexity of behaviour and the multiple causes for criminal behaviour.

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The Biological Basis of Wastewater Treatment

The Biological Basis of Wastewater Treatment

This involves the passage of organic carbon compounds, other molecules and ions from the mixed liquor into the bacterium. To do this, they have to pass through the cell wall and the inner membrane. The cell wall does not present much of a barrier, and control over entry is exercised at the inner membrane. Ions such as sodium diffuse in because the concentration in the mixed liquor is higher than inside the bacterium. They then have to be ‘pumped’ back out again to maintain the internal steady state. Small organic molecules similarly pass in along a concentration gradient, or may be assisted in entry by various mechanisms located in the inner membrane. Most large molecules are excluded. In order to use these for their nutrition and growth, the bacteria secrete enzymes into the water to digest them into small monomers, which can then pass into the cell. Different species of bacteria are specific for what enzymes they secrete, and this determines which chemicals they can exploit as a food source. The ability to secrete a particular enzyme may be latent. In other words, the bacterium requires the presence of the particular chemical compound in the water to switch on the genes for the synthesis of the enzyme required for its digestion. This is the basis of the process of Acclimation or Adaptation in activated sludge, mentioned previously.
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CiteSeerX — Mathematical Basis for Physical Inference

CiteSeerX — Mathematical Basis for Physical Inference

Abstract While the axiomatic introduction of a probability distribution over a space is common, its use for making predictions, using physical theories and prior knowl- edge, suffers from a lack of formalization. We propose to introduce, in the space of all probability distributions, two operations, the or and the and operation, that bring to the space the necessary structure for making inferences on possible values of physical parameters. While physical theories are often asumed to be analytical, we argue that consistent inference needs to replace analytical theories by proba- bility distributions over the parameter space, and we propose a systematic way of obtaining such “theoretical correlations”, using the or operation on the results of physical experiments. Predicting the outcome of an experiment or solving “inverse problems” are then examples of the use of the and operation. This leads to a simple and complete mathematical basis for general physical inference.
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Mathematical modelling of biological wastewater treatment of oxidation pond and constructed wetland systems

Mathematical modelling of biological wastewater treatment of oxidation pond and constructed wetland systems

It all started around the early twentieth when many researchers are trying to design an environmental friendly system utilizing biological treatment. This biological treatment was constructed to preserve the environment and to treat the wastewater. Since then, the treatment system has become the foundation of many wastewater treatment systems worldwide. The treatment method involves retaining bacteria naturally present in high concentration or population of wastewater treatment plant. It comprises several types of bacteria and protozoa found in treatment plant collectively referred as activated sludge [2]. The essence of the treatment is that bacteria break down organic carbon as a source of energy and food. As a result, bacteria can grow while the wastewater is being cleansed. Treated sewage at treatment plant is usually safe to be discharged into rivers or sea. Although the idea of applying bacteria into this treatment looks simple, the process is actually more complex considering many parameters that affect the treatment system. These include the changes in composition of bacteria, external factors such as weather, temperature and sunlight for an exposed treatment plant, as well as the changes in sewage passing through the treatment plant.
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Mathematical modeling of task managers for multiprocessor systems on the 
		basis of open loop queuing networks

Mathematical modeling of task managers for multiprocessor systems on the basis of open loop queuing networks

Consider Task Manager with the discipline FIFO (first in first out - «first come, first served») according to which tasks are served “first in first out” that is in the order of their appearance. Task Manager queues tasks which are not executed during the time given by the processor (quantum) again in front of the CPU for further processing. This approach allows you to implement the strategy of the service «if it is possible to finish calculations in order of their appearance». This discipline requires no external intervention during calculations; there is no redistribution of CPU time. We can say that it refers to nonpreemptive disciplines. The advantages are as follows. It is easy to implement and low system resources are used to form a tasks queue. However, this discipline leads to the fact that an increase of the computing system usage results in the growth of the average response time for the service, and short tasks (requiring small amount of computer time) have to wait as long as time-consuming ones [5, 16, 18]. The queue of tasks ready for processing in queuing systems S 1 is a queue with response and length limitations.
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Generalized Mathematical Model for Biological Growths

Generalized Mathematical Model for Biological Growths

ABSTRACT In this paper, we present a generalization of the commonly used growth models. We introduce Koya-Goshu biological growth model, as a more general solution of the rate-state ordinary differential equation. It is shown that the commonly used growth models such as Brody, Von Bertalanffy, Richards, Weibull, Monomolecular, Mitscherlich, Gompertz, Lo- gistic, and generalized Logistic functions are its special cases. We have constructed growth and relative growth func- tions as solutions of the rate-state equation. The generalized growth function is the most flexible so that it can be useful in model selection problems. It is also capable of generating new useful models that have never been used so far. The function incorporates two parameters with one influencing growth pattern and the other influencing asymptotic behav- iors. The relationships among these growth models are studies in details and provided in a flow chart.
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Biological and mathematical modeling of melanocyte development

Biological and mathematical modeling of melanocyte development

We aim to evaluate environmental and genetic effects on the expansion/proliferation of committed single cells during embryonic development, using melanoblasts as a paradigm to model this phenomenon. Melanoblasts are a specific type of cell that display extensive cellular proliferation during development. However, the events controlling melanoblast expansion are still poorly understood due to insufficient knowledge concerning their number and distribution in the various skin compartments. We show that melanoblast expansion is tightly controlled both spatially and temporally, with little variation between embryos. We established a mathematical model reflecting the main cellular mechanisms involved in melanoblast expansion, including proliferation and migration from the dermis to epidermis. In association with biological information, the model allows the calculation of doubling times for melanoblasts, revealing that dermal and epidermal melanoblasts have short but different doubling times. Moreover, the number of trunk founder melanoblasts at E8.5 was estimated to be 16, a population impossible to count by classical biological approaches. We also assessed the importance of the genetic background by studying gain- and loss- of-function b-catenin mutants in the melanocyte lineage. We found that any alteration of b-catenin activity, whether positive or negative, reduced both dermal and epidermal melanoblast proliferation. Finally, we determined that the pool of dermal melanoblasts remains constant in wild-type and mutant embryos during development, implying that specific control mechanisms associated with cell division ensure half of the cells at each cell division to migrate from the dermis to the epidermis. Modeling melanoblast expansion revealed novel links between cell division, cell localization within the embryo and appropriate feedback control through b -catenin.
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The biological basis of expected utility anomalies

The biological basis of expected utility anomalies

Rather than proposing another alternative theory, this paper will change perspective and go back to Allais paradox in order to investigate the biological reasons why people departs from expected utility theory. The insights gained in this line of research can be useful for extra fruitful generalizations of expected utility theory. By applying the questionnaire in Kahneman and Tversky (1979), which is made up of versions of the Allais paradox, we will replicate the paradox and further consider the biological characteristics of the respondents. We will find that the bio-characteristics matter for the anomalies.
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Exploring the biological basis of affective disorders

Exploring the biological basis of affective disorders

The purpose of the chapter is also to collect biological information concerning the set of genes in order to better understand the molecular biology and the function of subsets of the genes. Using the renowned web application Ingenuity, the selected genes are grouped according to their location in the cell, that is, in the nucleus, cytoplasm, plasma membrane or extracellular space. Also, the genes are grouped into three biological networks whose main functions deal with hematological and immunological diseases, cellular growth and proliferation as well as cell death. The relation to cell death is expressed through the neurogenesis hypothesis which posits that depression is caused by neuronal death and that antidepressant drugs cause neuronal growth. The three networks include other genes involved in the same functions, which might give ideas to new possible biomarkers. Other significant functions of the selected genes are also described, like cancer, metabolic and cardiovascular diseases, indicating the possible links between these diseases and the
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Biological basis of dyslexia: A maturing perspective

Biological basis of dyslexia: A maturing perspective

Keywords: Brain, candidate gene, chromosomes, dyslexia, linkage, loci. L ANGUAGE is truly a unique human gift, a complex process that enables communication and social functioning. Lan- guage gave human an enormous edge over other animals and increased the chances of humans survival 1 . Most chil- dren acquire language naturally in the sequence of listen- ing, speaking, reading and writing. Failure in any of these processes may lead to lifelong socioeconomic and mental health consequences 2 . There are many causes of language disability; the most common is dyslexia. No single definition currently exists to adequately define dyslexia and there is much controversy regarding the definition of dyslexia due to the complex expression of the disorder. But most of the definitions do agree that it cannot be attributed to any impairment in vision or hearing or intelligence and it is widely accepted that cognitive skills which are related to reading are affected. One of the most acceptable definitions is that it is a difficulty in learning to read and spell despite adequate education, intelligence and socio-cultural oppor- tunities and without any obvious sensory deficits 3 . Dyslexia accounts for 80% of learning disabilities. Prevalence of the trait ranges from 3 to 17.5% of school-age children 4–6 . It is found that males are more frequently affected than fe- males 7 . Hormonal factors such as foetal testosterone levels during late pregnancy may play a critical role and this is possibly reflected in the large male predominance of dys- lexia 8 .
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A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

By whatever mechanism, language development raises other key issues. How can one maintain the delicate balance of expressiveness and readability - can the language concisely describe all systems of interest while still being understand- able without extensive training? When does the ability to derive more expressive icons begin to diminish readability as viewers are required to recognize and interpret subtle differ- ences between similar icons? Even if successfully developed for selected domains and purposes, inevitably there will be edges to any language for describing all domains and for all analytical purposes - hence the continued appearance of new computer languages such as Java.
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Case studies in mathematical modelling for biological conservation

Case studies in mathematical modelling for biological conservation

Considered in this chapter is the population of one such species, the north- ern brown kiwi, Apteryx mantelli, whose chicks and juveniles are particularly vulnerable [r]

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