Nonlinear dynamics and chaos simulation system analysis for improved design

Small errors proved catastrophic. Our purpose to remark that a very small cause which escapes our notice determined a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. Small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. When dealing with any kind of electrical device specification, it is important to note that there exists a pair of test conditions that define a test: the forcing function and the limit. Forcing functions define the external operating constraints placed upon the device tested. The actual test defines how well the device responds to these constraints. Forcing inputs to threshold for example, represents the most difficult testing because this put those inputs as close as possible to the actual switching critical points and guarantees that the device will meet the Input-Output specifications. ^ Prediction becomes impossible by classical analytical analysis bounded by Newton and Euclides. We have found that non linear dynamics characteristics is the natural state of being in all circuits and devices. Opportunities exist for effective error detection in a nonlinear dynamics and chaos environment. ^ Nowadays there are a set of linear limits established around every aspect of a digital or analog circuits out of which devices are consider bad after failing the test. Deterministic chaos circuit is a fact not a possibility as it has been revived by our Ph.D. research. In practice for linear standard informational methodologies, this chaotic data product is usually undesirable and we are educated to be interested in obtaining a more regular stream of output data. ^ This Ph.D. research explored the possibilities of taking the foundation of a very well known simulation and modeling methodology, introducing nonlinear dynamics and chaos precepts, to produce a new error detector instrument able to put together streams of data scattered in space and time. Therefore, mastering deterministic chaos and changing the bad reputation of chaotic data as a potential risk for practical system status determination. ^

Effects of hydrologic and water quality drivers on periphyton dynamics in the southern Everglades

Everglades periphyton mats are tightly-coupled autotrophic (algae and cyanobacteria) and heterotrophic (eubacteria, fungi and microinvertebrates) microbial assemblages. We investigated the effect of water column total phosphorus and nitrogen concentrations, water depth and hydroperiod on periphyton of net production, respiration, nutrient content, and biomass. Our study sites were located along four transects that extended southward with freshwater sheetflow through sawgrass-dominated marsh. The water source for two of the transects were canal-driven and anchored at canal inputs. The two other transects were rain-driven (ombrotrophic) and began in sawgrass-dominated marsh. Periphyton dynamics were examined for upstream and downstream effects within and across the four transects. Although all study sites were characterized as short hydroperiod and phosphorus-limited oligotrophic, they represent gradients of hydrologic regime, water source and water quality of the southern Everglades. Average periphyton net production of 1.08 mg C AFDW−1 h−1 and periphyton whole system respiration of 0.38 mg C AFDW−1 h−1 rates were net autotrophic. Biomass was generally highest at ombrotrophic sites and sites downstream of canal inputs. Mean biomass over all our study sites was high, 1517.30 g AFDW m−2. Periphyton was phosphorus-limited. Average periphyton total phosphorus content was 137.15 μg P g−1 and average periphyton total N:P ratio was 192:1. Periphyton N:P was a sensitive indicator of water source. Even at extremely low mean water total phosphorus concentrations ( ≤ 0.21 μmol l−1), we found canal source effects on periphyton dynamics at sites adjacent to canal inputs, but not downstream of inflows. These canal source effects were most pronounced at the onset of wet season with initial rewetting. Spatial and temporal variability in periphyton dynamics could not solely be ascribed to water quality, but was often associated with both hydrology and water source.

Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patient's antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.