Capillaries within compartments: Microvascular interpretation of dynamic positron emission tomography data

Measurement of exchange of substances between blood and tissue has been a long-lasting challenge to physiologists, and considerable theoretical and experimental accomplishments were achieved before the development of the positron emission tomography (PET). Today, when modeling data from modern PET scanners, little use is made of earlier microvascular research in the compartmental models, which have become the standard model by which the vast majority of dynamic PET data are analysed. However, modern PET scanners provide data with a sufficient temporal resolution and good counting statistics to allow estimation of parameters in models with more physiological realism. We explore the standard compartmental model and find that incorporation of blood flow leads to paradoxes, such as kinetic rate constants being time-dependent, and tracers being cleared from a capillary faster than they can be supplied by blood flow. The inability of the standard model to incorporate blood flow consequently raises a need for models that include more physiology, and we develop microvascular models which remove the inconsistencies. The microvascular models can be regarded as a revision of the input function. Whereas the standard model uses the organ inlet concentration as the concentration throughout the vascular compartment, we consider models that make use of spatial averaging of the concentrations in the capillary volume, which is what the PET scanner actually registers. The microvascular models are developed for both single- and multi-capillary systems and include effects of non-exchanging vessels. They are suitable for analysing dynamic PET data from any capillary bed using either intravascular or diffusible tracers, in terms of physiological parameters which include regional blood flow. (C) 2003 Elsevier Ltd. All rights reserved.

Direction of Causation Modeling Between Cross-Sectional Measures of Parenting and Psychological Distress in Female Twins

Under certain conditions, cross-sectional analysis of cross-twin intertrait correlations can provide important information about the direction of causation (DOC) between two variables. A community-based sample of Australian female twins aged 18 to 45 years was mailed an extensive Health and Lifestyle Questionnaire (HLQ) that covered a wide range of personality and behavioral measures. Included were self-report measures of recent psychological distress and perceived childhood environment (PBI). Factor analysis of the PBI yielded three interpretable dimensions: Coldness, Overprotection, and Autonomy. Univariate analysis revealed that parental Overprotection and Autonomy were best explained by additive genetic, shared, and nonshared environmental effects (ACE), whereas the best-fitting model for PBI Coldness and the three measures of psychological distress (Depression, Phobic Anxiety, and Somatic Distress) included only additive genetic and nonshared environmental effects (AE). A common pathway model best explained the covariation between (1) the three PBI dimensions and (2) the three measures of psychological distress. DOC modeling between latent constructs of parenting and psychological distress revealed that a model which specified recollected parental behavior as the cause of psychological distress provided a better fit than a model which specified psychological distress as the cause of recollected parental behavior. Power analyses and limitations of the findings are discussed.

Biaxial failure model for fiber reinforced concrete

Steel fiber reinforced concrete (SFRC) is widely applied in the construction industry. Numerical elastoplastic analysis of the macroscopic behavior is complex. This typically involves a piecewise linear failure curve including corner singularities. This paper presents a single smooth biaxial failure curve for SFRC based on a semianalytical approximation. Convexity of the proposed model is guaranteed so that numerical problems are avoided. The model has sufficient flexibility to closely match experimental results. The failure curve is also suitable for modeling plain concrete under biaxial loading. Since this model is capable of simulating the failure states in all stress regimes with a single envelope, the elastoplastic formulation is very concise and simple. The finite element implementation is developed to demonstrate the conciseness and the effectiveness of the model. The computed results display good agreement with published experimental data.

Sensor-driven agenda for intelligent home care of the elderly

The exponential increase of home-bound persons who live alone and are in need of continuous monitoring requires new solutions to current problems. Most of these cases present illnesses such as motor or psychological disabilities that deprive of a normal living. Common events such as forgetfulness or falls are quite common and have to be prevented or dealt with. This paper introduces a platform to guide and assist these persons (mostly elderly people) by providing multisensory monitoring and intelligent assistance. The platform operates at three levels. The lower level, denominated ‘‘Data acquisition and processing’’performs the usual tasks of a monitoring system, collecting and processing data from the sensors for the purpose of detecting and tracking humans. The aim is to identify their activities in an intermediate level called ‘‘activity detection’’. The upper level, ‘‘Scheduling and decision-making’’, consists of a scheduler which provides warnings, schedules events in an intelligent manner and serves as an interface to the rest of the platform. The idea is to use mobile and static sensors performing constant monitoring of the user and his/her environment, providing a safe environment and an immediate response to severe problems. A case study on elderly fall detection in a nursery home bedroom demonstrates the usefulness of the proposal.

Mechanical Behavior of the Lamellar Structure in Semi-Crystalline Polymers

We have employed molecular dynamics simulations to study the behavior of virtual polymeric materials under an applied uniaxial tensile load. Through computer simulations, one can obtain experimentally inaccessible information about phenomena taking place at the molecular and microscopic levels. Not only can the global material response be monitored and characterized along time, but the response of macromolecular chains can be followed independently if desired. The computer-generated materials were created by emulating the step-wise polymerization, resulting in self-avoiding chains in 3D with controlled degree of orientation along a certain axis. These materials represent a simplified model of the lamellar structure of semi-crystalline polymers,being comprised of an amorphous region surrounded by two crystalline lamellar regions. For the simulations, a series of materials were created, varying i) the lamella thickness, ii) the amorphous region thickness, iii) the preferential chain orientation, and iv) the degree of packing of the amorphous region. Simulation results indicate that the lamella thickness has the strongest influence on the mechanical properties of the lamella-amorphous structure, which is in agreement with experimental data. The other morphological parameters also affect the mechanical response, but to a smaller degree. This research follows previous simulation work on the crack formation and propagation phenomena, deformation mechanisms at the nanoscale, and the influence of the loading conditions on the material response. Computer simulations can improve the fundamental understanding about the phenomena responsible for the behavior of polymeric materials, and will eventually lead to the design of knowledge-based materials with improved properties.

Modelling the Mechanical Behavior of Polymer-Based Nanocomposites

Molecular dynamics simulations were employed to analyze the mechanical properties of polymer-based nanocomposites with varying nanofiber network parameters. The study was focused on nanofiber aspect ratio, concentration and initial orientation. The reinforcing phase affects the behavior of the polymeric nanocomposite. Simulations have shown that the fiber concentration has a significant effect on the properties, with higher loadings resulting in higher stress levels and higher stiffness, matching the general behavior from experimental knowledge in this field. The results also indicate that, within the studied range, the observed effect of the aspect ratio and initial orientation is smaller than that of the concentration, and that these two parameters are interrelated.

Coupling Mechanical and Electrical Behavior in the Multi-scale Simulation of Polymer-based CNT Nanocomposites

A numeric model has been proposed to investigate the mechanical and electrical properties of a polymeric/carbon nanotube (CNT) composite material subjected to a deformation force. The reinforcing phase affects the behavior of the polymeric matrix and depends on the nanofiber aspect ratio and preferential orientation. The simulations show that the mechanical behavior of a computer generated material (CGM) depends on fiber length and initial orientation in the polymeric matrix. It is also shown how the conductivity of the polymer/CNT composite can be calculated for each time step of applied stress, effectively providing the ability to simulate and predict strain-dependent electrical behavior of CNT nanocomposites.

A brief survey on online analysis of movement data

The increasing availability of mobility data and the awareness of its importance and value have been motivating many researchers to the development of models and tools for analyzing movement data. This paper presents a brief survey of significant research works about modeling, processing and visualization of data about moving objects. We identified some key research fields that will provide better features for online analysis of movement data. As result of the literature review, we suggest a generic multi-layer architecture for the development of an online analysis processing software tool, which will be used for the definition of the future work of our team.

Assessment of 3D scanners for modeling Pectus Carinatum corrective bar

Pectus Carinatum (PC) is a chest deformity consisting on the anterior protrusion of the sternum and adjacent costal cartilages. Non-operative corrections, such as the orthotic compression brace, require previous information of the patient chest surface, to improve the overall brace fit. This paper focuses on the validation of the Kinect scanner for the modelling of an orthotic compression brace for the correction of Pectus Carinatum. To this extent, a phantom chest wall surface was acquired using two scanner systems – Kinect and Polhemus FastSCAN – and compared through CT. The results show a RMS error of 3.25mm between the CT data and the surface mesh from the Kinect sensor and 1.5mm from the FastSCAN sensor

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Predicting the mechanical behavior of amorphous polymeric materials under strain through multi-scale simulation

Polymeric materials have become the reference material for high reliability and performance applications. However, their performance in service conditions is difficult to predict, due in large part to their inherent complex morphology, which leads to non-linear and anisotropic behavior, highly dependent on the thermomechanical environment under which it is processed. In this work, a multiscale approach is proposed to investigate the mechanical properties of polymeric-based material under strain. To achieve a better understanding of phenomena occurring at the smaller scales, the coupling of a finite element method (FEM) and molecular dynamics (MD) modeling, in an iterative procedure, was employed, enabling the prediction of the macroscopic constitutive response. As the mechanical response can be related to the local microstructure, which in turn depends on the nano-scale structure, this multiscale approach computes the stress-strain relationship at every analysis point of the macro-structure by detailed modeling of the underlying micro- and meso-scale deformation phenomena. The proposed multiscale approach can enable prediction of properties at the macroscale while taking into consideration phenomena that occur at the mesoscale, thus offering an increased potential accuracy compared to traditional methods.

Consumer behavior and profile in cross border tourism destinations

Tourism is a phenomenon that moves millions of people around the world, taking as a major driver of the global economy. Such relevance is reflected in the proliferation of studies in the overall area known as tourism, under various perspectives and backgrounds. In the light of such multitude of insights our study aims at gaining a deeper understanding of customer profiling and behavior in cross-border tourism destinations. Previous studies conducted in such contexts suggest that cross-border regions (CBRs) are an attractive and desirable idea, yet requiring further theoretical and empirical research. The new configuration of many CBRs calls for a debate on issues concerning its development, raising up important dimensions, such as, organization and planning of common tourism destinations. There is still a gap in the understanding of destination management in CBRs and the customer profile and motivations. Overall this research aims at attaining a deeper understanding of the profile and behavior of consumers in tourism settings, addressing the predisposition for the destination. The study addresses the following research question: “What factors influence customer behavior and attitudes in a CBRs tourism destination?” To address our question we will take an interdisciplinary perspective bringing together inputs from marketing, tourism and local economics. When addressing consumer behavior in tourism previous studies considered the following constructs: involvement, place attachment, satisfaction and destination loyalty. In order to establish the causal relationships in our theoretical model, we intend to develop a predominant quantitative design, yet we plan to conduct exploratory interviews. In the analysis and discussion of results, we intend to use Structural Equation Modeling. It will further allow understanding how the constructs in the research model relate to each other in the specified context. Results are also expected to have managerial implications. Consequently our results may assist decision makers in developing their local policies.

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling. The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.

Assessment of 3D scanners for modeling pectus carinatum corrective bar

Pectus Carinatum (PC) is a chest deformity consisting on the anterior protrusion of the sternum and adjacent costal cartilages. Non-operative corrections, such as the orthotic compression brace, require previous information of the patient chest surface, to improve the overall brace fit. This paper focuses on the validation of the Kinect scanner for the modelling of an orthotic compression brace for the correction of Pectus Carinatum. To this extent, a phantom chest wall surface was acquired using two scanner systems – Kinect and Polhemus FastSCAN – and compared through CT. The results show a RMS error of 3.25mm between the CT data and the surface mesh from the Kinect sensor and 1.5mm from the FastSCAN sensor.

Modeling the Diffusion of Energy Performance Contracting

The Portuguese Energy Policy considers the development of a commercially viable and competitive market for energy performance contracting (EPC) as a main mechanism to achieve the objectives of energy efficiency improvement. This paper proposes a study to investigate how to achieve widespread adoption of energy performance contracting by means of system dynamics modelling and simulation. To explore and gather insights on this question, a system dynamics model representing the system of the Portuguese EPC market at industry level will be created. The simulation of that model will provide a helpful basis for analysing and explaining the development of key variables, and accelerating learning on the managerial, organizational and political adaptation processes that foster the diffusion of EPC adoption. The first phase of this research project aims at identifying and analysing the key factors and critical cause-effect relations that drive the adoption of EPC. With this purpose, a qualitative content analysis on relevant documents was performed and a set of interviews was conducted. That data was analysed to capture the critical variables and its interrelation to formulate a preliminary representation of the system structure as stock and flow diagrams.