Modeling the peptide-T cell receptor interaction by the comparative molecular similarity indices analysis-soft independent modeling of class analogy technique

A set of 38 epitopes and 183 non-epitopes, which bind to alleles of the HLA-A3 supertype, was subjected to a combination of comparative molecular similarity indices analysis (CoMSIA) and soft independent modeling of class analogy (SIMCA). During the process of T cell recognition, T cell receptors (TCR) interact with the central section of the bound nonamer peptide; thus only positions 4−8 were considered in the study. The derived model distinguished 82% of the epitopes and 73% of the non-epitopes after cross-validation in five groups. The overall preference from the model is for polar amino acids with high electron density and the ability to form hydrogen bonds. These so-called “aggressive” amino acids are flanked by small-sized residues, which enable such residues to protrude from the binding cleft and take an active role in TCR-mediated T cell recognition. Combinations of “aggressive” and “passive” amino acids in the middle part of epitopes constitute a putative TCR binding motif

Systems Analysis: the Structure-and-Purpose Approach Based on Logic-linguistic Formalisation

Systems analysis (SA) is widely used in complex and vague problem solving. Initial stages of SA are analysis of problems and purposes to obtain problems/purposes of smaller complexity and vagueness that are combined into hierarchical structures of problems(SP)/purposes(PS). Managers have to be sure the PS and the purpose realizing system (PRS) that can achieve the PS-purposes are adequate to the problem to be solved. However, usually SP/PS are not substantiated well enough, because their development is based on a collective expertise in which logic of natural language and expert estimation methods are used. That is why scientific foundations of SA are not supposed to have been completely formed. The structure-and-purpose approach to SA based on a logic-and-linguistic simulation of problems/purposes analysis is a step towards formalization of the initial stages of SA to improve adequacy of their results, and also towards increasing quality of SA as a whole. Managers of industrial organizing systems using the approach eliminate logical errors in SP/PS at early stages of planning and so they will be able to find better decisions of complex and vague problems.

Mathematical Modeling of the Weaving Structure Design

Красимир Йорджев, Христина Костадинова - В работата се разглежда една релация на еквивалентност в множеството от всички квадратни бинарни матрици. Обсъдена е комбинаторната задача за намиране мощността и елементите на фактормножеството относно тази релация. Разгледана е и възможността за получаване на някои специални елементи на това фактормножество. Предложен е алгоритъм за решаване на поставените задачи. Получените в статията резултати намират приложение при описанието топологията на различните тъкачни структури.

Improving novice analyst performance in modeling the sequence diagram in systems analysis: A cognitive complexity approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.

A nested Petri net framework for modeling and analyzing multi-agent systems

In the past two decades, multi-agent systems (MAS) have emerged as a new paradigm for conceptualizing large and complex distributed software systems. A multi-agent system view provides a natural abstraction for both the structure and the behavior of modern-day software systems. Although there were many conceptual frameworks for using multi-agent systems, there was no well established and widely accepted method for modeling multi-agent systems. This dissertation research addressed the representation and analysis of multi-agent systems based on model-oriented formal methods. The objective was to provide a systematic approach for studying MAS at an early stage of system development to ensure the quality of design. ^ Given that there was no well-defined formal model directly supporting agent-oriented modeling, this study was centered on three main topics: (1) adapting a well-known formal model, predicate transition nets (PrT nets), to support MAS modeling; (2) formulating a modeling methodology to ease the construction of formal MAS models; and (3) developing a technique to support machine analysis of formal MAS models using model checking technology. PrT nets were extended to include the notions of dynamic structure, agent communication and coordination to support agent-oriented modeling. An aspect-oriented technique was developed to address the modularity of agent models and compositionality of incremental analysis. A set of translation rules were defined to systematically translate formal MAS models to concrete models that can be verified through the model checker SPIN (Simple Promela Interpreter). ^ This dissertation presents the framework developed for modeling and analyzing MAS, including a well-defined process model based on nested PrT nets, and a comprehensive methodology to guide the construction and analysis of formal MAS models.^

Population structure of spotted sunfish (Lepomis punctatus) in the Florida Everglades as revealed by DNA microsatellite analysis

Genetic diversity can be used to describe patterns of gene flow within and between local and regional populations. The Florida Everglades experiences seasonal fluctuations in water level that can influence local population extinction and recolonization dynamics. In addition, this expansive wetland has been divided into water management regions by canals and levees. These combined factors can affect genetic diversity and population structure of aquatic organisms in the Everglades. We analyzed allelic variation at six DNA microsatellite loci to examine the population structure of spotted sunfish (Lepomis punctatus) from the Everglades. We tested the hypothesis that recurrent local extinction and recent regional divisions have had an effect on patterns of genetic diversity. No marked differences were observed in comparisons of the heterozygosity values of sites within and among water management units. No evidence of isolation by distance was detected in a gene flow and distance correlation between subpopulations. Confidence intervals for the estimated F-statistic values crossed zero, indicating that there was no significant genetic difference between subpopulations within a region or between regions. Notably, the genetic variation among subpopulations in a water conservation area was greater than variation among regions (Fsp>FPT). These data indicate that the spatial scale of recolonization following local extinction appears to be most important within water management units.

Integrated Ecological Modeling and Decision Analysis Within the Everglades Landscape

Planning for complex ecosystem restoration projects involves integrating ecological modeling with analysis of performance trade-offs among restoration alternatives. The authors used the Everglades Landscape Model and Multi-Criteria Decision Analysis to explore the effect of simulated ecosystem performance, risk preferences, and criteria weights on the ranking of three alternatives to restoring overland sheet flow in the Everglades. The ecological model outputs included both hydrologic and water quality criteria. Results were scored in the decision analysis framework, highlighting the trade-offs between hydrologic restoration and water quality constraints. Given equal weighting of performance measures, the alternative with more homogenous sheet flow was preferred over other alternatives, despite evidence of some localized eutrophication risk.

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Modeling Nymphoides architecture: A morphological analysis of Nymphoides aquatica (Menyanthaceae)

• Premise of the study: Species in the aquatic genus Nymphoides have inflorescences that appear to arise from the petioles of floating leaves. The inflorescence-floating leaf complex can produce vegetative propagules and/or additional inflorescences and leaves. We analyzed the morphology of N. aquatica to determine how this complex relates to whole plant architecture and whether whole plant growth is sympodial or monopodial. • Methods: We used dissections, measurements, and microscopic observations of field-collected plants and plants cultivated for 2 years in outdoor tanks in south Florida, USA. • Key results: Nymphoides aquatica had a submerged plagiotropic rhizome that produced floating leaves in an alternate/spiral phyllotaxy. Rhizomes were composed of successive sympodial units that varied in the number of leaves produced before the apex terminated. The basic sympodial unit had a prophyll that subtended a renewal-shoot bud, a short-petioled leaf (SPL) with floating lamina, and an inflorescence; the SPL axillary bud expanded as a vegetative propagule. Plants produced either successive basic sympodial units or expanded sympodia that intercalated long-petioled leaves between the prophyll and the SPL. • Conclusions: Nymphoides aquatica grows sympodially, forming a rhizome composed of successive basic sympodia and expanded sympodial units. Variations on these types of sympodial growth help explain the branching patterns and leaf morphologies described for other Nymphoides species. Monitoring how these two sympodial phases are affected by water depth provides an ecologically meaningful way to assess N. aquatica’s responses to altered hydrology.

Incorporating variable peak -to -daily ratios in the equilibrium traffic assignment procedure of the Florida Standard Urban Transportation Modeling Structure (FSUTMS)

The standard highway assignment model in the Florida Standard Urban Transportation Modeling Structure (FSUTMS) is based on the equilibrium traffic assignment method. This method involves running several iterations of all-or-nothing capacity-restraint assignment with an adjustment of travel time to reflect delays encountered in the associated iteration. The iterative link time adjustment process is accomplished through the Bureau of Public Roads (BPR) volume-delay equation. Since FSUTMS' traffic assignment procedure outputs daily volumes, and the input capacities are given in hourly volumes, it is necessary to convert the hourly capacities to their daily equivalents when computing the volume-to-capacity ratios used in the BPR function. The conversion is accomplished by dividing the hourly capacity by a factor called the peak-to-daily ratio, or referred to as CONFAC in FSUTMS. The ratio is computed as the highest hourly volume of a day divided by the corresponding total daily volume. ^ While several studies have indicated that CONFAC is a decreasing function of the level of congestion, a constant value is used for each facility type in the current version of FSUTMS. This ignores the different congestion level associated with each roadway and is believed to be one of the culprits of traffic assignment errors. Traffic counts data from across the state of Florida were used to calibrate CONFACs as a function of a congestion measure using the weighted least squares method. The calibrated functions were then implemented in FSUTMS through a procedure that takes advantage of the iterative nature of FSUTMS' equilibrium assignment method. ^ The assignment results based on constant and variable CONFACs were then compared against the ground counts for three selected networks. It was found that the accuracy from the two assignments was not significantly different, that the hypothesized improvement in assignment results from the variable CONFAC model was not empirically evident. It was recognized that many other factors beyond the scope and control of this study could contribute to this finding. It was recommended that further studies focus on the use of the variable CONFAC model with recalibrated parameters for the BPR function and/or with other forms of volume-delay functions. ^

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Fluorescence Characteristics of Size-Fractionated Dissolved Organic Matter: Implications for a Molecular Assembly Based Structure?

Surface freshwater samples from Everglades National Park, Florida, were used to investigate the size distributions of natural dissolved organic matter (DOM) and associated fluorescence characteristics along the molecular weight continuum. Samples were fractionated using size exclusion chromatography (SEC) and characterized by spectroscopic means, in particular Excitation-Emission Matrix fluorescence modeled with parallel factor analysis (EEM-PARAFAC). Most of the eight components obtained from PARAFAC modeling were broadly distributed across the DOM molecular weight range, and the optical properties of the eight size fractions for all samples studied were quite consistent among each other. Humic-like components presented a similar distribution in all the samples, with enrichment in the middle molecular weight range. Some variability in the relative distribution of the different humic-like components was observed among the different size fractions and among samples. The protein like fluorescence, although also generally present in all fractions, was more variable but generally enriched in the highest and lowest molecular weight fractions. These observations are in agreement with the hypothesis of a supramolecular structure for DOM, and suggest that DOM fluorescence characteristics may be controlled by molecular assemblies with similar optical properties, distributed along the molecular weight continuum. This study highlights the importance of studying the molecular structure of DOM on a molecular size distribution perspective, which may have important implications in understanding the environmental dynamics such materials.

Numerical heat transfer analysis of carbon-based foams for use in thermal protection system

The applicability of carbon-based foams as an insulating or active cooling material in thermal protection systems (TPSs) of space vehicles is considered using a computer modeling. This study focuses on numerical investigation of the performance of carbon foams for use in TPSs of space vehicles. Two kinds of carbon foams are considered in this study. For active cooling, the carbon foam that has a thermal conductivity of 100 W/m-k is used and for the insulation, the carbon foam having a thermal conductivity of 0.225 W/m-k is used. A 3D geometry is employed to simulate coolant flow and heat transfer through carbon foam model. Gambit has been used to model the 3D geometry and the numerical simulation is carried out in FLUENT. Numerical results from this thesis suggests that the use of CFOAM and HTC carbon foams in TPS's may effectively protect the aluminum structure of the space shuttle during reentry of the space vehicle.

Improving Novice Analyst Performance in Modeling the Sequence Diagram in Systems Analysis: A Cognitive Complexity Approach

The Unified Modeling Language (UML) has quickly become the industry standard for object-oriented software development. It is being widely used in organizations and institutions around the world. However, UML is often found to be too complex for novice systems analysts. Although prior research has identified difficulties novice analysts encounter in learning UML, no viable solution has been proposed to address these difficulties. Sequence-diagram modeling, in particular, has largely been overlooked. The sequence diagram models the behavioral aspects of an object-oriented software system in terms of interactions among its building blocks, i.e. objects and classes. It is one of the most commonly-used UML diagrams in practice. However, there has been little research on sequence-diagram modeling. The current literature scarcely provides effective guidelines for developing a sequence diagram. Such guidelines will be greatly beneficial to novice analysts who, unlike experienced systems analysts, do not possess relevant prior experience to easily learn how to develop a sequence diagram. There is the need for an effective sequence-diagram modeling technique for novices. This dissertation reports a research study that identified novice difficulties in modeling a sequence diagram and proposed a technique called CHOP (CHunking, Ordering, Patterning), which was designed to reduce the cognitive load by addressing the cognitive complexity of sequence-diagram modeling. The CHOP technique was evaluated in a controlled experiment against a technique recommended in a well-known textbook, which was found to be representative of approaches provided in many textbooks as well as practitioner literatures. The results indicated that novice analysts were able to perform better using the CHOP technique. This outcome seems have been enabled by pattern-based heuristics provided by the technique. Meanwhile, novice analysts rated the CHOP technique more useful although not significantly easier to use than the control technique. The study established that the CHOP technique is an effective sequence-diagram modeling technique for novice analysts.