A method for the reconstruction of unknown non-monotonic growth functions in the chemostat

We propose an adaptive control law that allows one to identify unstable steady states of the open-loop system in the single-species chemostat model without the knowledge of the growth function. We then show how one can use this control law to trace out (reconstruct) the whole graph of the growth function. The process of tracing out the graph can be performed either continuously or step-wise. We present and compare both approaches. Even in the case of two species in competition, which is not directly accessible with our approach due to lack of controllability, feedback control improves identifiability of the non-dominant growth rate.Comment: expansion of ideas from proceedings paper (17 pages, 8 figures), proceedings paper is version v

Plasma Dynamics

Contains reports on three research projects.National Science Foundation (Grant G-9330)United States Air Force, Air Force Cambridge Research Center (Contract AF19(604)-5992)United States ArmyUnited States Air Force (Contract AF19(604)-7400)Lincoln Laboratory (Purchase Order B-00306)Flight Accessories Laboratory, Wright-Patterson Air Force Base (WADD Contract AF33(616)-7624)United States Air Force, Air Force Cambridge Research Laboratories (Contract AF19(604)-4551)United States NavyUnited States Atomic Energy Commission (Contract AT(30-1)-1842

Plasma Electronics

Contains research objectives and reports on six research objectives.National Science Foundation (Grant G-24073)Lincoln Laboratory, Purchase Order DDL BB-107U. S. Air Force under Contract AF 19(628)-50

Plasma Dynamics

Contains reports on two research projects.National Science Foundation under Grant G-9330WADD Contract AF33(616)-7624 with Flight Accessories Laboratory, Wright-Patterson Air Force Base, OhioAtomic Energy Commission under Contract AT(30-1)-1842Air Force Command and Control Development Division under Contract AF19(604)-599

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal)

Autoimmune Disease Classification by Inverse Association with SNP Alleles

With multiple genome-wide association studies (GWAS) performed across autoimmune diseases, there is a great opportunity to study the homogeneity of genetic architectures across autoimmune disease. Previous approaches have been limited in the scope of their analysis and have failed to properly incorporate the direction of allele-specific disease associations for SNPs. In this work, we refine the notion of a genetic variation profile for a given disease to capture strength of association with multiple SNPs in an allele-specific fashion. We apply this method to compare genetic variation profiles of six autoimmune diseases: multiple sclerosis (MS), ankylosing spondylitis (AS), autoimmune thyroid disease (ATD), rheumatoid arthritis (RA), Crohn's disease (CD), and type 1 diabetes (T1D), as well as five non-autoimmune diseases. We quantify pair-wise relationships between these diseases and find two broad clusters of autoimmune disease where SNPs that make an individual susceptible to one class of autoimmune disease also protect from diseases in the other autoimmune class. We find that RA and AS form one such class, and MS and ATD another. We identify specific SNPs and genes with opposite risk profiles for these two classes. We furthermore explore individual SNPs that play an important role in defining similarities and differences between disease pairs. We present a novel, systematic, cross-platform approach to identify allele-specific relationships between disease pairs based on genetic variation as well as the individual SNPs which drive the relationships. While recognizing similarities between diseases might lead to identifying novel treatment options, detecting differences between diseases previously thought to be similar may point to key novel disease-specific genes and pathways

On the dynamics of the adenylate energy system: homeorhesis vs homeostasis.

Biochemical energy is the fundamental element that maintains both the adequate turnover of the biomolecular structures and the functional metabolic viability of unicellular organisms. The levels of ATP, ADP and AMP reflect roughly the energetic status of the cell, and a precise ratio relating them was proposed by Atkinson as the adenylate energy charge (AEC). Under growth-phase conditions, cells maintain the AEC within narrow physiological values, despite extremely large fluctuations in the adenine nucleotides concentration. Intensive experimental studies have shown that these AEC values are preserved in a wide variety of organisms, both eukaryotes and prokaryotes. Here, to understand some of the functional elements involved in the cellular energy status, we present a computational model conformed by some key essential parts of the adenylate energy system. Specifically, we have considered (I) the main synthesis process of ATP from ADP, (II) the main catalyzed phosphotransfer reaction for interconversion of ATP, ADP and AMP, (III) the enzymatic hydrolysis of ATP yielding ADP, and (IV) the enzymatic hydrolysis of ATP providing AMP. This leads to a dynamic metabolic model (with the form of a delayed differential system) in which the enzymatic rate equations and all the physiological kinetic parameters have been explicitly considered and experimentally tested in vitro. Our central hypothesis is that cells are characterized by changing energy dynamics (homeorhesis). The results show that the AEC presents stable transitions between steady states and periodic oscillations and, in agreement with experimental data these oscillations range within the narrow AEC window. Furthermore, the model shows sustained oscillations in the Gibbs free energy and in the total nucleotide pool. The present study provides a step forward towards the understanding of the fundamental principles and quantitative laws governing the adenylate energy system, which is a fundamental element for unveiling the dynamics of cellular life

Fatores de influência no comportamento de compra de alimentos por crianças

A escolha alimentar nas sociedades contemporâneas passa, inevitavelmente, pelo comércio, pois o alimento constitui-se mercadoria que é consumida, assim como tantos outros bens e serviços. Atualmente muitas crianças já definem sozinhas suas escolhas alimentares, provocando a atenção tanto de empresas como de organizações preocupadas com sua nutrição. Utilizando o modelo BPM (Behavioral Perpective Model), criado por Foxall (2010), fundamentado na psicologia do consumidor e estruturado na tríplice contingência de Skinner, analisaram-se os fatores que influenciam crianças em seu comportamento de compra de alimentos. Tendo como sujeitos 175 alunos com idades compreendidas entre 10 e 12 anos, identificaram-se 35 variáveis que foram classificadas entre estímulos antecedentes (cenário ou histórico de aprendizado) e consequentes (reforço utilitário ou informativo) no comportamento de compra. Verificou-se que os estímulos reforçadores (consequentes) têm maior grau de importância para a decisão de compra de alimentos desses sujeitos do que os estímulos antecedentes, sendo que as consequências utilitárias são mais influentes do que as informativas. Conclui-se que os atributos dos produtos, como sabor e qualidade, têm maior influência na decisão de compra do que os estímulos ambientais, como as promoções e publicidade dos alimentos.Food choice in contemporary societies is, inevitably, a buying decision. Food is a product that is consumed, like so many other goods and services. Nowadays many children choose their food themselves, which attracts attention not only from companies that develop products and advertising for that segment, but also organizations concerned with their nutrition. This paper analyzed the factors that influence children's food purchasing behavior using the Perpective Behavioral Model (BPM) created by Foxall (2010), which in turn is based on consumer psychology and structured on Skinner's triple contingency. The subjects were 175 students between 10 and 12 years old. Thirty-five variables were identified and classified as antecedent stimuli (setting or learning history) or purchase reinforcers (utilitarian or informational reinforcement). It was seen that reinforcement stimuli (consequent stimuli) are more important to these children's decisions than antecedent stimuli, and that utilitarian consequences are more influential than informational consequences. It was concluded that product attributes such as taste and quality have greater influence on purchasing decisions than environmental stimuli such as promotions and food advertising