Membrane microdialysis: Evaluation of a new method to assess splanchnic tissue metabolism

OBJECTIVE: Measuring peritoneal lactate concentrations could be useful for detecting splanchnic hypoperfusion. The aims of this study were to evaluate the properties of a new membrane-based microdialyzer in vitro and to assess the ability of the dialyzer to detect a clinically relevant decrease in splanchnic blood flow in vivo. DESIGN: A membrane-based microdialyzer was first validated in vitro. The same device was tested afterward in a randomized, controlled animal experiment. SETTING: University experimental research laboratory. SUBJECTS: Twenty-four Landrace pigs of both genders. INTERVENTIONS: In vitro: Membrane microdialyzers were kept in warmed sodium lactate baths with lactate concentrations between 2 and 8 mmol/L for 10-120 mins, and microdialysis lactate concentrations were measured repeatedly (210 measurements). In vivo: An extracorporeal shunt with blood reservoir and roller pump was inserted between the proximal and distal abdominal aorta, and a microdialyzer was inserted intraperitoneally. In 12 animals, total splanchnic blood flow (measured by transit time ultrasound) was reduced by a median 43% (range, 13% to 72%) by activating the shunt; 12 animals served as controls. MEASUREMENTS AND MAIN RESULTS: In vitro: The fractional lactate recovery was 0.59 (0.32-0.83) after 60 mins and 0.82 (0.71-0.87) after 90 mins, with no further increase thereafter. At 60 and 90 mins, the fractional recovery was independent of the lactate concentration. In vivo: Abdominal blood flow reduction resulted in an increase in peritoneal microdialysis lactate concentration from 1.7 (0.3-3.8) mmol/L to 2.8 (1.3-6.2) mmol/L (p = .006). At the same time, mesenteric venous-arterial lactate gradient increased from 0.1 (-0.2-0.8) mmol/L to 0.3 (-0.3 -1.8) mmol/L (p = .032), and mesenteric venous-arterial Pco2 gradients increased from 12 (8-19) torr to 21 (11-54) torr (p = .005). CONCLUSIONS: Peritoneal membrane microdialysis provides a method for the assessment of splanchnic ischemia, with potential for clinical application.

Model Evaluation Based on the Distribution of Estimated Absolute Prediction Error

The construction of a reliable, practically useful prediction rule for future response is heavily dependent on the "adequacy" of the fitted regression model. In this article, we consider the absolute prediction error, the expected value of the absolute difference between the future and predicted responses, as the model evaluation criterion. This prediction error is easier to interpret than the average squared error and is equivalent to the mis-classification error for the binary outcome. We show that the distributions of the apparent error and its cross-validation counterparts are approximately normal even under a misspecified fitted model. When the prediction rule is "unsmooth", the variance of the above normal distribution can be estimated well via a perturbation-resampling method. We also show how to approximate the distribution of the difference of the estimated prediction errors from two competing models. With two real examples, we demonstrate that the resulting interval estimates for prediction errors provide much more information about model adequacy than the point estimates alone.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.

Microscopic wire guide-based orotracheal mouse intubation: description, evaluation and comparison with transillumination

Airway access is needed for a number of experimental animal models, and the majority of animal research is based on mouse models. Anatomical conditions in mice are small, and the narrow glottic opening allows intubation only with a subtle technique. We therefore developed a microscopic endotracheal intubation method with a wire guide technique in mice anaesthetized with halothane in oxygen. The mouse is hung perpendicularly with its incisors on a thread fixed on a vertical plate. The tongue is placed with a pair of forceps between the left hand's thumb and forefinger and slightly pulled, while the neck and thorax are positioned using the third and fourth fingers. By doing so, the neck can be slightly stretched, which allows optimal visualization of the larynx and the vocal cords. To ensure a safe intubation, a fine wire guide is placed under vision between the vocal cords and advanced about 5 mm into the trachea. An intravenous 22G x 1 in. plastic or Teflon catheter is guided over this wire. In a series of 41 mice, between 21 and 38 g, the success rate for the first intubation attempt was >95%. Certainty of the judgement procedure was 100% and success rate was higher using the described method when compared with a transillumination method in a further series. The technique is safe, less invasive than tracheostomy and suitable for controlled ventilation and pulmonary substance application.

A fuzzy risk attitude classification based on prospect theory

Traditional methods do not actually measure peoples’ risk attitude naturally and precisely. Therefore, a fuzzy risk attitude classification method is developed. Since the prospect theory is usually considered as an effective model of decision making, the personalized parameters in prospect theory are firstly fuzzified to distinguish people with different risk attitudes, and then a fuzzy classification database schema is applied to calculate the exact value of risk value attitude and risk be- havior attitude. Finally, by applying a two-hierarchical clas- sification model, the precise value of synthetical risk attitude can be acquired.

Evaluation of a novel photography-based home assessment protocol for identification of environmental risk factors for falls in elderly persons

PRINCIPLES To evaluate the validity and feasibility of a novel photography-based home assessment (PhoHA) protocol, as a possible substitute for on-site home assessment (OsHA). METHODS A total of 20 patients aged ≥65 years who were hospitalised in a rehabilitation centre for musculoskeletal disorders affecting mobility participated in this prospective validation study. For PhoHA, occupational therapists rated photographs and measurements of patients' homes provided by patients' confidants. For OsHA, occupational therapists conducted a conventional home visit. RESULTS Information obtained by PhoHA was 79.1% complete (1,120 environmental factors identified by PhoHA vs 1416 by OsHA). Of the 1,120 factors, 749 had dichotomous (potential hazards) and 371 continuous scores (measurements with tape measure). Validity of PhoHA to potential hazards was good (sensitivity 78.9%, specificity 84.9%), except for two subdomains (pathways, slippery surfaces). Pearson's correlation coefficient for the validity of measurements was 0.87 (95% confidence interval [CI 0.80-0.92, p <0.001). Agreement between methods was 0.52 (95%CI 0.34-0.67, p <0.001, Cohen's kappa coefficient) for dichotomous and 0.86 (95%CI 0.79-0.91, p <0.001, intraclass correlation coefficient) for continuous scores. Costs of PhoHA were 53.0% lower than those of OsHA (p <0.001). CONCLUSIONS PhoHA has good concurrent validity for environmental assessment if instructions for confidants are improved. PhoHA is potentially a cost-effective method for environmental assessment.

More volunteers in football clubs. An evaluation of a method to increase the number of volunteers

An increasing number of clubs experience difficulties in recruiting and retaining sufficient numbers of volunteers to manage and staff their clubs (Lamprecht, Fischer, & Stamm, 2012). In order to facilitate volunteer recruitment, sport clubs need a specific strategy to recruit and retain volunteers for both formal positions and ad hoc tasks. Therefore, the intervention “More Volunteers in Football Clubs” was designed and its impact was evaluated in detail. The question this evaluation research wants to address is: Can football clubs recruit and retain volunteers successfully by implementing the intervention “More Volunteers in Football Clubs”? The designed intervention is based on the different expectations and needs of volunteers, as well as non-profit human resource management and organisational development management, with a strong emphasis on club-specific counseling and support. Task forces of the twelve participating football clubs attended four workshops in which they received tailor made counseling to reach the desired number of volunteers. The intervention has been implemented and its effectiveness tested in cooperation with the Swiss Football Federation with twelve Swiss football clubs following a pretest, intervention, posttest design Data have been gathered and analysed using a combination of qualitative and quantitative methods. Outcome measurements are: volunteer rate, number of recruited volunteers, number of filled volunteer positions and volunteer satisfaction. Four months after the intervention all clubs that completed the proposed intervention were successful in recruiting the desired number of volunteers. Further, all participating clubs found the intervention helpful and would recommend other clubs to participate as well. With the development of this practical intervention a solution for football clubs is provided to overcome the difficulties in recruiting and retaining sufficient numbers of volunteers. Lamprecht, M., Fischer, A., & Stamm, H.-P. (2012). Sportvereine in der Schweiz. Strukturen, Leistungen, Herausforderungen. Zürich, Switzerland: Seismo.

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland

BACKGROUND: This study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway. METHODS: A framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013. RESULTS: A cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99%, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey. CONCLUSIONS: The seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.

Use of empowerment evaluation to determine a sustainability plan for a community-based preconception care program

Women With IMPACT (WWI) is a community-based preconception care educational intervention. WWI is being implemented by the Impacting Maternal and Prenatal Care Together (IMPACT) Collaborative and targets zip codes in Harris County, Texas at high risk for infant mortality, low birthweight, and preterm birth. WWI started March 2012 and continues through August 2013. Three workshop series are planned. This study was conducted with participants and facilitators from the first workshop series. This study aimed to 1) evaluate the WWI program using empowerment evaluation, 2) engage all WWI stakeholders in an empowerment evaluation so the method could be adopted as a participatory evaluation process for future IMPACT activities, and 3) develop recommendations for sustainability of the WWI intervention, based on empowerment evaluation findings and results from the pre/post program evaluation completed by WWI participants. Study participants included WWI participants and facilitators and IMPACT Collaborative Steering Committee members. WWI participants were female, 18-35 year-old, non-pregnant residents of zip codes at high risk of adverse birth outcomes. All other study participants were 18 years or older. A two-phased empowerment evaluation (EE) was utilized in this study. Sessions 1-4 were conducted independently of one another – 3 with participants at different sites and one with the facilitators. The fifth session included WWI participant and facilitator representatives, and IMPACT Steering Committee members. Session 5 built upon the work of the other sessions. Observation notes were recorded during each session. Thematic content analysis was conducted on all EE tables and observation notes. Mission statements drafted by each group focused on improvement of physical and mental health through behavior change and empowerment of all participants. The top 5 overall program components were: physical activity, nutrition, self-worth, in-class communication, and stress. Goals for program improvement were set by EE participants for each of these components. Through thematic content analysis of the tables and observation notes, social support emerged as an important theme of the program among all participant groups. Change to a healthy lifestyle emerged as an important theme in terms of program improvement. Two-phased EE provided an opportunity for all program stakeholders to provide feedback regarding important program components and provide suggestions for program improvement. EE, thematic content analysis, pre/post evaluation results, and inherent program knowledge were triangulated to make recommendations to sustain the program once the initial funding ends. ^

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Student academic performance stochastic simulator based on the Monte Carlo method

In this paper, a computer-based tool is developed to analyze student performance along a given curriculum. The proposed software makes use of historical data to compute passing/failing probabilities and simulates future student academic performance based on stochastic programming methods (MonteCarlo) according to the specific university regulations. This allows to compute the academic performance rates for the specific subjects of the curriculum for each semester, as well as the overall rates (the set of subjects in the semester), which are the efficiency rate and the success rate. Additionally, we compute the rates for the Bachelors degree, which are the graduation rate measured as the percentage of students who finish as scheduled or taking an extra year and the efficiency rate (measured as the percentage of credits of the curriculum with respect to the credits really taken). In Spain, these metrics have been defined by the National Quality Evaluation and Accreditation Agency (ANECA). Moreover, the sensitivity of the performance metrics to some of the parameters of the simulator is analyzed using statistical tools (Design of Experiments). The simulator has been adapted to the curriculum characteristics of the Bachelor in Engineering Technologies at the Technical University of Madrid(UPM).

A Fuzzy approach based on dynamic programming and metaheuristics for selecting safeguards for risk management for information systems

In this paper we focus on the selection of safeguards in a fuzzy risk analysis and management methodology for information systems (IS). Assets are connected by dependency relationships, and a failure of one asset may affect other assets. After computing impact and risk indicators associated with previously identified threats, we identify and apply safeguards to reduce risks in the IS by minimizing the transmission probabilities of failures throughout the asset network. However, as safeguards have associated costs, the aim is to select the safeguards that minimize costs while keeping the risk within acceptable levels. To do this, we propose a dynamic programming-based method that incorporates simulated annealing to tackle optimizations problems.

Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.