Generalized Nets Model of an E-Learning System Software Architecture

The paper has been presented at the International Conference Pioneers of Bulgarian Mathematics, Dedicated to Nikola Obreshko ff and Lubomir Tschakaloff , Sofi a, July, 2006.

Architecture of Extensible Computations Driven Systems

Никола Вълчанов, Тодорка Терзиева, Владимир Шкуртов, Антон Илиев - Една от основните области на приложения на компютърната информатика е автоматизирането на математическите изчисления. Информационните системи покриват различни области като счетоводство, електронно обучение/тестване, симулационни среди и т. н. Те работят с изчислителни библиотеки, които са специфични за обхвата на системата. Въпреки, че такива системи са перфектни и работят безпогрешно, ако не се поддържат остаряват. В тази работа описваме механизъм, който използва динамично библиотеките за изчисления и взема решение по време на изпълнение (интелигентно или интерактивно) за това как и кога те да се използват. Целта на тази статия е представяне на архитектура за системи, управлявани от изчисления. Тя се фокусира върху ползите от използването на правилните шаблони за дизайн с цел да се осигури разширяемост и намаляване на сложността.

Fluctuation-driven traffic congestion in a scale-free model of the Internet

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analysing network failures caused by hardware faults or overload. There network reaction was modelled as rerouting of traffic away from failed or congested elements. Here we model network reaction to congestion on much shorter time scales when the input traffic rate through congested routes is reduced. As an example we consider the Internet where local mismatch between demand and capacity results in traffic losses. We describe the onset of congestion as a phase transition characterised by strong, albeit relatively short-lived, fluctuations of losses caused by noise in input traffic and exacerbated by the heterogeneous nature of the network manifested in a power-law load distribution. The fluctuations may result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © 2013 IEEE.

Refinement methods for software architecture design using the software architecture model

Modern software systems are often large and complicated. To better understand, develop, and manage large software systems, researchers have studied software architectures that provide the top level overall structural design of software systems for the last decade. One major research focus on software architectures is formal architecture description languages, but most existing research focuses primarily on the descriptive capability and puts less emphasis on software architecture design methods and formal analysis techniques, which are necessary to develop correct software architecture design. ^ Refinement is a general approach of adding details to a software design. A formal refinement method can further ensure certain design properties. This dissertation proposes refinement methods, including a set of formal refinement patterns and complementary verification techniques, for software architecture design using Software Architecture Model (SAM), which was developed at Florida International University. First, a general guideline for software architecture design in SAM is proposed. Second, specification construction through property-preserving refinement patterns is discussed. The refinement patterns are categorized into connector refinement, component refinement and high-level Petri nets refinement. These three levels of refinement patterns are applicable to overall system interaction, architectural components, and underlying formal language, respectively. Third, verification after modeling as a complementary technique to specification refinement is discussed. Two formal verification tools, the Stanford Temporal Prover (STeP) and the Simple Promela Interpreter (SPIN), are adopted into SAM to develop the initial models. Fourth, formalization and refinement of security issues are studied. A method for security enforcement in SAM is proposed. The Role-Based Access Control model is formalized using predicate transition nets and Z notation. The patterns of enforcing access control and auditing are proposed. Finally, modeling and refining a life insurance system is used to demonstrate how to apply the refinement patterns for software architecture design using SAM and how to integrate the access control model. ^ The results of this dissertation demonstrate that a refinement method is an effective way to develop a high assurance system. The method developed in this dissertation extends existing work on modeling software architectures using SAM and makes SAM a more usable and valuable formal tool for software architecture design. ^

Endothelin 3 induces skin pigmentation in a keratin-driven inducible mouse model

Endothelin 3 (Edn3) is a ligand important to developing neural crest cells (NCC). Some NCC eventually migrate into the skin and give rise to the pigment-forming melanocytes found in hair follicles. Edn3's effects on NCC have been largely explored through spontaneous mutants and cell culture experiments. These studies have shown the Endothelin receptor B/Edn3 signaling pathway to be important in the proliferation/survival and differentiation of developing melanocytes. To supplement these investigations I have created doxycycline-responsive transgenic mice which conditionally over-express Edn3. These mice will help us clarify Edn3's role during the development of early embryonic melanoblasts, differentiating melanocyte precursors in the skin, and fully differentiated melanocytes in the hair follicle. The transgene mediated expression of Edn3 was predominantly confined to the roof plate of the neural tube and surface ectoderm in embryos and postnatally in the epidermal keratinocytes of the skin. Relative to littermate controls, transgenics develop increased pigmentation on most areas of the skin. My doxycycline-based temporal studies have shown that both embryonic and postnatal events are important for establishing and maintaining pigmented skin. The study of my Edn3 transgenic mice may offer some insight into the genetics behind benign dermal pigmentation and offer clues about the time periods important in establishing these conditions. This apparently abnormal development is echoed in a benign condition of human skin. Cases of dermal melanocytosis, such as common freckles, Mongolian spotting, and nevus of Ito demonstrate histological and etiological characteristics similar to those of the transgenic mice generated in this study.

Development of test-based wind-driven rain intrusion model for hurricane-induced building interior and contents damage

Major portion of hurricane-induced economic loss originates from damages to building structures. The damages on building structures are typically grouped into three main categories: exterior, interior, and contents damage. Although the latter two types of damages, in most cases, cause more than 50% of the total loss, little has been done to investigate the physical damage process and unveil the interdependence of interior damage parameters. Building interior and contents damages are mainly due to wind-driven rain (WDR) intrusion through building envelope defects, breaches, and other functional openings. The limitation of research works and subsequent knowledge gaps, are in most part due to the complexity of damage phenomena during hurricanes and lack of established measurement methodologies to quantify rainwater intrusion. This dissertation focuses on devising methodologies for large-scale experimental simulation of tropical cyclone WDR and measurements of rainwater intrusion to acquire benchmark test-based data for the development of hurricane-induced building interior and contents damage model. Target WDR parameters derived from tropical cyclone rainfall data were used to simulate the WDR characteristics at the Wall of Wind (WOW) facility. The proposed WDR simulation methodology presents detailed procedures for selection of type and number of nozzles formulated based on tropical cyclone WDR study. The simulated WDR was later used to experimentally investigate the mechanisms of rainwater deposition/intrusion in buildings. Test-based dataset of two rainwater intrusion parameters that quantify the distribution of direct impinging raindrops and surface runoff rainwater over building surface — rain admittance factor (RAF) and surface runoff coefficient (SRC), respectively —were developed using common shapes of low-rise buildings. The dataset was applied to a newly formulated WDR estimation model to predict the volume of rainwater ingress through envelope openings such as wall and roof deck breaches and window sill cracks. The validation of the new model using experimental data indicated reasonable estimation of rainwater ingress through envelope defects and breaches during tropical cyclones. The WDR estimation model and experimental dataset of WDR parameters developed in this dissertation work can be used to enhance the prediction capabilities of existing interior damage models such as the Florida Public Hurricane Loss Model (FPHLM).^

A "Transforming the School-to-Prison Pipeline" Initiative: Mentoring Model Pilot Project Symposium

Abstract: This informative and interactive teaching symposium posits the Positive Peer Leadership Mentoring Program (PPLM) as an evidence-based wrap-around service for youth and families in Miami-Dade who are involved in the school-to-prison pipeline. Presenters first provide information to initiate the dialogic process of discerning and interpreting the school-to-prison pipeline, impacted by costs of incarceration for Black youth and families and the move toward effective mental health services in the juvenile justice system. Then, participants experience an interactive pedagogical mentoring format set forth in PPLM as the first step toward transforming the school-to-prison pipeline in their own classroom or other educational setting.

Development of an antigen-driven colitis model to study presentation of antigens by antigen presenting cells to T cells

Inflammatory bowel disease (IBD) is a chronic inflammation which affects the gastrointestinal tract (GIT). One of the best ways to study the immunological mechanisms involved during the disease is the T cell transfer model of colitis. In this model, immunodeficient mice (RAG-/-recipients) are reconstituted with naive CD4+ T cells from healthy wild type hosts. This model allows examination of the earliest immunological events leading to disease and chronic inflammation, when the gut inflammation perpetuates but does not depend on a defined antigen. To study the potential role of antigen presenting cells (APCs) in the disease process, it is helpful to have an antigen-driven disease model, in which a defined commensal-derived antigen leads to colitis. An antigen driven-colitis model has hence been developed. In this model OT-II CD4+ T cells, that can recognize only specific epitopes in the OVA protein, are transferred into RAG-/- hosts challenged with CFP-OVA-expressing E. coli. This model allows the examination of interactions between APCs and T cells in the lamina propria.

Longitudinal Micro CT-driven biomarkers as a tool to evaluate lung fibrosis progression and antifibrotic efficacy in a refined Bleomycin mouse model

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with no curative pharmacological treatment. Animal models play an essential role in revealing molecular mechanisms involved in the pathogenesis of the disease. Bleomycin (BLM)-induced lung fibrosis is the most widely used and characterized model for anti-fibrotic drugs screening. However, several issues have been reported, such as the identification of an optimal BLM dose and administration scheme as well as gender-specificity. Moreover, the balance between disease resolution, an appropriate time window for therapeutic intervention and animal welfare remains critical aspects yet to be fully elucidated. In this thesis, Micro CT imaging has been used as a tool to identify the ideal BLM dose regimen to induce sustained lung fibrosis in mice as well as to assess the anti-fibrotic effect of Nintedanib (NINT) treatment upon this BLM administration regimen. In order to select the optimal BLM dose scheme, C57bl/6 male mice were treated with BLM via oropharyngeal aspiration (OA), following either double or triple BLM administration. The triple BLM administration resulted in the most promising scheme, able to balance disease resolution, appropriate time-window for therapeutic intervention and animal welfare. The fibrosis progression was longitudinally assessed by micro-CT every 7 days for 5 weeks after BLM administration and 5 animals were sacrificed at each timepoint for the BALF and histological evaluation. The antifibrotic effect of NINT was assessed following different treatment regimens in this model. Herein, we have developed an optimized mouse model of pulmonary fibrosis, enabling three weeks of the therapeutic window to screen putative anti-fibrotic drugs. micro-CT scanning, allowed us to monitor the progression of lung fibrosis and the therapeutical response longitudinally in the same subject, drastically reducing the number of animals involved in the experiment.

Data driven regularization models of non-linear ill-posed inverse problems in imaging

Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

Bicoherence in electrostatic turbulence driven by high magnetohydrodynamic activity in Tokamak Chauffage Alfven Bresilien

During some discharges in Tokamak Chauffage Alfven Bresilien [R. M. O. Galvao et al., Plasma Phys. Controlled Fusion 43, 1181 (2001)] high magnetohydrodynamic activity may appear with a peaked frequency spectrum. Whenever this peak occurs, the ambient broadband electrostatic turbulence is remarkably modified, synchronizing into the dominant magnetic fluctuation frequency and presenting high bicoherence in the whole plasma edge with a maximum bicoherence inside the plasma. A phenomenological model is introduced to investigate this driven turbulence bicoherence, consisting of nonlinearly coupled phase-randomized drift modes with time-periodic external driving at the dominant magnetic fluctuation frequency. The bicoherence spectrum of this model can mimic features of the experimental results. (C) 2009 American Institute of Physics. [DOI: 10.1063/1.3099701]

Crystallization and preliminary structural analysis of the giant haemoglobin from Glossoscolex paulistus at 3.2 angstrom

Glossoscolex paulistus is a free-living earthworm encountered in south-east Brazil. Its oxygen transport requirements are undertaken by a giant extracellular haemoglobin, or erythrocruorin (HbGp), which has an approximate molecular mass of 3.6 MDa and, by analogy with its homologue from Lumbricus terrestris (HbLt), is believed to be composed of a total of 180 polypeptide chains. In the present work the full 3.6 MDa particle in its cyanomet state was purified and crystallized using sodium citrate or PEG8000 as precipitant. The crystals contain one-quarter of the full particle in the asymmetric unit of the I222 cell and have parameters of a = 270.8 angstrom, b = 320.3 angstrom and c = 332.4 angstrom. Diffraction data were collected to 3.15 angstrom using synchrotron radiation on beamline X29A at the Brookhaven National Laboratory and represent the highest resolution data described to date for similar erythrocruorins. The structure was solved by molecular replacement using a search model corresponding to one-twelfth of its homologue from HbLt. This revealed that HbGp belongs to the type I class of erythrocruorins and provided an interpretable initial electron density map in which many features including the haem groups and disulfide bonds could be identified.