Sistemas granulares evolutivos

Orientador: Fernando Antonio Campos GomideTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Recentemente tem-se observado um crescente interesse em abordagens de modelagem computacional para lidar com fluxos de dados do mundo real. Métodos e algoritmos têm sido propostos para obtenção de conhecimento a partir de conjuntos de dados muito grandes e, a princípio, sem valor aparente. Este trabalho apresenta uma plataforma computacional para modelagem granular evolutiva de fluxos de dados incertos. Sistemas granulares evolutivos abrangem uma variedade de abordagens para modelagem on-line inspiradas na forma com que os humanos lidam com a complexidade. Esses sistemas exploram o fluxo de informação em ambiente dinâmico e extrai disso modelos que podem ser linguisticamente entendidos. Particularmente, a granulação da informação é uma técnica natural para dispensar atenção a detalhes desnecessários e enfatizar transparência, interpretabilidade e escalabilidade de sistemas de informação. Dados incertos (granulares) surgem a partir de percepções ou descrições imprecisas do valor de uma variável. De maneira geral, vários fatores podem afetar a escolha da representação dos dados tal que o objeto representativo reflita o significado do conceito que ele está sendo usado para representar. Neste trabalho são considerados dados numéricos, intervalares e fuzzy; e modelos intervalares, fuzzy e neuro-fuzzy. A aprendizagem de sistemas granulares é baseada em algoritmos incrementais que constroem a estrutura do modelo sem conhecimento anterior sobre o processo e adapta os parâmetros do modelo sempre que necessário. Este paradigma de aprendizagem é particularmente importante uma vez que ele evita a reconstrução e o retreinamento do modelo quando o ambiente muda. Exemplos de aplicação em classificação, aproximação de função, predição de séries temporais e controle usando dados sintéticos e reais ilustram a utilidade das abordagens de modelagem granular propostas. O comportamento de fluxos de dados não-estacionários com mudanças graduais e abruptas de regime é também analisado dentro do paradigma de computação granular evolutiva. Realçamos o papel da computação intervalar, fuzzy e neuro-fuzzy em processar dados incertos e prover soluções aproximadas de alta qualidade e sumário de regras de conjuntos de dados de entrada e saída. As abordagens e o paradigma introduzidos constituem uma extensão natural de sistemas inteligentes evolutivos para processamento de dados numéricos a sistemas granulares evolutivos para processamento de dados granularesAbstract: In recent years there has been increasing interest in computational modeling approaches to deal with real-world data streams. Methods and algorithms have been proposed to uncover meaningful knowledge from very large (often unbounded) data sets in principle with no apparent value. This thesis introduces a framework for evolving granular modeling of uncertain data streams. Evolving granular systems comprise an array of online modeling approaches inspired by the way in which humans deal with complexity. These systems explore the information flow in dynamic environments and derive from it models that can be linguistically understood. Particularly, information granulation is a natural technique to dispense unnecessary details and emphasize transparency, interpretability and scalability of information systems. Uncertain (granular) data arise from imprecise perception or description of the value of a variable. Broadly stated, various factors can affect one's choice of data representation such that the representing object conveys the meaning of the concept it is being used to represent. Of particular concern to this work are numerical, interval, and fuzzy types of granular data; and interval, fuzzy, and neurofuzzy modeling frameworks. Learning in evolving granular systems is based on incremental algorithms that build model structure from scratch on a per-sample basis and adapt model parameters whenever necessary. This learning paradigm is meaningful once it avoids redesigning and retraining models all along if the system changes. Application examples in classification, function approximation, time-series prediction and control using real and synthetic data illustrate the usefulness of the granular approaches and framework proposed. The behavior of nonstationary data streams with gradual and abrupt regime shifts is also analyzed in the realm of evolving granular computing. We shed light upon the role of interval, fuzzy, and neurofuzzy computing in processing uncertain data and providing high-quality approximate solutions and rule summary of input-output data sets. The approaches and framework introduced constitute a natural extension of evolving intelligent systems over numeric data streams to evolving granular systems over granular data streamsDoutoradoAutomaçãoDoutor em Engenharia Elétric

System Designs for Diabetic Foot Ulcer Image Assessment

For individuals with type 2 diabetes, diabetic foot ulcers represent a significant health issue and the wound care cost is quite high. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and the status of the wound tissue. This method is potentially inaccurate for wound assessment and requires extra clinical workload. In view of the prevalence of smartphones with high resolution digital camera, assessing wound healing by analyzing of real-time images using the significant computational power of today’s mobile devices is an attractive approach for managing foot ulcers. Alternatively, the smartphone may be used just for image capture and wireless transfer to a PC or laptop for image processing. To achieve accurate foot ulcer image assessment, we have developed and tested a novel automatic wound image analysis system which accomplishes the following conditions: 1) design of an easy-to-use image capture system which makes the image capture process comfortable for the patient and provides well-controlled image capture conditions; 2) synthesis of efficient and accurate algorithms for real-time wound boundary determination to measure the wound area size; 3) development of a quantitative method to assess the wound healing status based on a foot ulcer image sequence for a given patient and 4) design of a wound image assessment and management system that can be used both in the patient’s home and clinical environment in a tele-medicine fashion. In our work, the wound image is captured by the camera on the smartphone while the patient’s foot is held in place by an image capture box, which is specially design to aid patients in photographing ulcers occurring on the sole of their feet. The experimental results prove that our image capture system guarantees consistent illumination and a fixed distance between the foot and camera. These properties greatly reduce the complexity of the subsequent wound recognition and assessment. The most significant contribution of our work is the development of five different wound boundary determination approaches based on different computer vision algorithms. The first approach employs the level set algorithm to determine the wound boundary directly based on a manually set initial curve. The second and third approaches are the mean-shift segmentation based methods augmented by foot outline detection and analysis. These two approaches have been shown to be efficient to implement (especially on smartphones), prior-knowledge independent and able to provide reasonably accurate wound segmentation results given a set of well-tuned parameters. However, this method suffers from the lack of self-adaptivity due to the fact that it is not based on machine learning. Consequently, a two-stage Support Vector Machine (SVM) binary classifier based wound recognition approach is developed and implemented. This approach consists of three major steps 1) unsupervised super-pixel segmentation, 2) feature descriptor extraction for each super-pixel and 3) supervised classifier based wound boundary determination. The experimental results show that this approach provides promising performance (sensitivity: 73.3%, specificity: 95.6%) when dealing with foot ulcer images captured with our image capture box. In the third approach, we further relax the image capture constraints and generalize the application of our wound recognition system by applying the conditional random field (CRF) based model to solve the wound boundary determination. The key modules in this approach are the TextonBoost based potential learning at different scales and efficient CRF model inference to find the optimal labeling. Finally, the standard K-means clustering algorithm is applied to the determined wound area for color based wound tissue classification. To train the models used in the last two approaches, as well as to evaluate all three methods, we have collected about 100 wound images at the wound clinic in UMass Medical School by tracking 15 patients for a 2-year period, following an IRB approved protocol. The wound recognition results were compared with the ground truth generated by combining clinical labeling from three experienced clinicians. Specificity and sensitivity based measures indicate that the CRF based approach is the most reliable method despite its implementation complexity and computational demands. In addition, sample images of Moulage wound simulations are also used to increase the evaluation flexibility. The advantages and disadvantages of three approaches are described. Another important contribution of this work has been development of a healing score based mechanism for quantitative wound healing status assessment. The wound size and color composition measurements were converted to a score number ranging from 0-10, which indicates the healing trend based on comparisons of subsequent images to an initial foot ulcer image. By comparing the result of the healing score algorithm to the healing scores determined by experienced clinicians, we assess the clinical validity of our healing score algorithm. The level of agreement of our healing score with the three assessing clinicians was quantified by using the Kripendorff’s Alpha Coefficient (KAC). Finally, a collaborative wound image management system between the PC and smartphone was designed and successfully applied in the wound clinic for patients’ wound tracking purpose. This system is proven to be applicable in clinical environment and capable of providing interactive foot ulcer care in a telemedicine fashion

Dynamics, regulation and function of macrophages in skin repair

Tissue repair is a highly dynamic process comprising the sequential phases of inflammation, tissue formation, and maturation. The mechanisms that orchestrate the natural sequence of the wound healing response remain elusive. Influx of macrophages plays a crucial role in tissue repair. However, the precise function of macrophages during the healing response has remained a subject of debate due to their functional dichotomy as effectors of both, tissue injury and repair. In this study the hypothesis was examined whether macrophages recruited during the diverse phases of skin repair after mechanical injury exert specific functions to restore tissue integrity. For this purpose a mouse model was developed that allows conditional depletion of macrophages during the sequential stages of the repair response by using the inducible diphtheria toxin receptor mouse model in combination with a myeloid cell-specific Cre mouse line. Depletion of macrophages restricted to the early stage of the repair response (inflammatory phase) significantly reduced the formation of a vascularized granulation tissue and showed impaired re-epithelialization. However, recruitment of macrophages during the mid phase of repair, after macrophage depletion was stopped, rescued the impaired healing response and resulted in minimized scar formation. In contrast, depletion of macrophages restricted to the mid stage of the repair response (phase of tissue formation) resulted in severe hemorrhages within the wound tissue. Under these conditions, transition into the subsequent phase of tissue maturation and wound closure did not occur. Finally, macrophage depletion restricted to the late stage of repair (phase of tissue maturation) did not significantly impact the outcome of the repair response. Taken together, these results demonstrate that macrophages exert distinct functions during the different phases of skin repair, which are crucial to control the natural sequence of repair events. Furthermore, the effect of macrophages on endothelial cell function and wound angiogenesis appeared to be critical. Therefore the impact of macrophage-derived vascular endothelial growth factor-A (VEGF-A) on the outcome of the wound healing response was analyzed, by using conditional gene targeting to specifically deplete VEGF-A expression in myeloid cells. It could be shown that during the early phase of repair, myeloid cell-derived VEGF-A is essential to induce the angiogenic response, in contrast, at later stages of the wound healing response epidermal-derived VEGF-A controls vascular growth. We further showed that myeloid cell-derived VEGF-A is critical for tip cell formation, a process fundamental for vascular sprouting. Collectively, our findings propose novel mechanistic insights on macrophage-mediated repair events after skin injury and potentially might identify new therapeutic targets that can promote wound angiogenesis in impaired wound healing conditions

Theoretical Problems in High Resolution Solar Physics, 2

The Science Working Group for the High Resolution Solar Observatory (HRSO) laid plans beginning in 1984 for a series of workshops designed to stimulate a broadbased input from the scientific community to the HRSO mission. These workshops have the dual objectives of encouraging an early start on the difficult theoretical problems in radiative transfer, magnetohydrodynamics, and plasma physics that will be posed by the HRSO data, and maintaining current discussions of results in high resolution solar studies. This workshop was the second in the series. The workshop format presented invited review papers during the formal sessions and contributed poster papers for discussions during open periods. Both are presented

Influence of Polycaprolactone and Basic Fibroblast Growth Factor on Gingival Fibroblasts

Guided tissue regeneration (GTR) to regenerate periodontal tissue involves placement of a cell-occlusive barrier membrane functionally excluding the gingiva and associated oral epithelium from the periodontal defect. Gingival connective tissue (CT) contains a rich vascular plexus and is a source of progenitor cells which could contribute to periodontal regeneration. We propose the use of a novel biodegradable and bioactive electrospun fibrous polycaprolactone (PCL) scaffold loaded with microspheres releasing basic fibroblast growth factor (bFGF) to promote gingival CT growth while maintaining a barrier to the oral epithelium. Scaffolds supported human gingival fibroblast proliferation and mesenchymal cell infiltration in a bFGF dose dependent manner. Oral epithelial cells were excluded from the interior of the scaffolds. Scaffold treatment during early healing of rat gingival wounds showed good biocompatibility. This study suggests that PCL electrospun scaffolds loaded with bFGF microspheres represent a promising alternative to the current generation of GTR barrier membranes

A methodology for automatic parameter-tuning and center selection in density-peak clustering methods

The density-peak clustering algorithm, which we refer to as DPC, is a novel and efficient density-based clustering approach. The method has the advantage of allowing non-convex clusters, and clusters of variable size and density, to be grouped together, but it also has some limitations, such as the visual location of centers and the parameter tuning. This paper describes an optimization-based methodology for automatic parameter/center selection applicable both to the DPC and to other algorithms derived from it. The objective function is an internal/external cluster validity index, and the decisions are the parameterization of the algorithm and the choice of centers. The internal validation measures lead to an automatic parameter-tuning process, and the external validation measures lead to the so-called optimal rules, which are a tool to bound the performance of a given algorithm from above on the set of parameterizations. A numerical experiment with real data was performed for the DPC and for the fuzzy weighted k-nearest neighbor (FKNN-DPC) which validates the automatic parameter-tuning methodology and demonstrates its efficiency compared to the state of the art.El algoritmo de agrupamiento de picos de densidad, al que nos referimos como DPC , es un enfoque de agrupamiento basado en la densidad novedoso y eficiente. El método tiene la ventaja de permitir agrupar clústeres no convexos y clústeres de tamaño y densidad variables, pero también tiene algunas limitaciones, como la ubicación visual de los centros y el ajuste de parámetros. Este artículo describe una metodología basada en la optimización para la selección automática de parámetros/centros aplicable tanto al DPC como a otros algoritmos derivados de él. La función objetivo es un índice de validez de clúster interno/externo, y las decisiones son la parametrización del algoritmo y la elección de los centros. Las medidas de validación interna conducen a un proceso automático de ajuste de parámetros, y las medidas de validación externa conducen al llamadoreglas óptimas , que son una herramienta para limitar el rendimiento de un algoritmo dado desde arriba en el conjunto de parametrizaciones. Se realizó un experimento numérico con datos reales para el DPC y para el k -vecino más cercano ponderado difuso ( FKNN-DPC ) que valida la metodología de ajuste automático de parámetros y demuestra su eficiencia en comparación con el estado del arte

Skin Grafts for Successful Wound Closure

Wounds with full thickness or deep partial thickness skin loss require skin grafts to achieve closure and minimize functional and aesthetic effects of healing. This book presents a comprehensive overview of skin grafts for wound closure. Section I includes three chapters that discuss established methods of wound bed preparation as well as new agents and methods. Section II includes three chapters that provide basic information about skin grafts and grafting procedure techniques

Understanding the Impact of Solvents in Oral Solid Dosage Formulation and Process Development

The successful delivery of chemical compounds for the purpose of therapeutic treatments and prophylactics is a substantial undertaking in modern drug development. Notably, the adoption of high throughput screening techniques has led to the proliferation of poorly water soluble and/or highly potent molecules which further complicate development activities. Spray dried amorphous solid dispersions are an increasingly important formulation strategy to overcome solubility issues while wet granulation approaches are the method of choice for the preparation of highly potent APIs in oral solid dosage forms. A common connection between these critical techniques is their reliance on solvent-based processing that can often result in unexpected outcomes on product quality and performance. Solvent choice has been shown to influence API form, habit, stabilizing interactions, and physical and chemical properties of drug product intermediates, which requires greater understanding. The objective of this dissertation is to provide a general overview and assessment of the role of solvents in the important methods of spray dried dispersions (SDDs) and highly potent compounds by wet shear granulations (HP-WSG) to address concerns related to poorly soluble and/or highly potent APIs. Light scattering (LS) and dilute solution viscometry (DSV) techniques have been utilized to assess critical drug-polymer-solvent interactions in the solution state and explore the mechanisms by which solvent choice may influence SDD physical stability. Next, solid-state characterization techniques were leveraged to understand how the interplay between wet granulation processing parameters, API physical form, and environmental moisture may dictate chemical stability issues of a highly potent API. Conclusions and future work are presented with next steps that can be pursued in expanding our knowledge of complex multi-component solutions which are frequently encountered in pharmaceutical development