Annexin A5-Conjugated Polymeric Micelles For Dual SPECT and Optical Detection of Apoptosis

Apoptosis, a form of programmed cell death, is critical to homoeostasis, normal development, and physiology. Dysregulation of apoptosis can lead to the accumulation of unwanted cells, such as occurs in cancer, and the removal of needed cells or disorders of normal tissues, such as heart, neurodegenerative, and autoimmune diseases. Noninvasive detection of apoptosis may play an important role in the evaluation of disease states and response to therapeutic intervention for a variety of diseases. It is desirable to have an imaging method to accurately detect and monitor this process in patients. In this study, we developed annexin A5-conjugated polymeric micellar nanoparticles dual-labeled with a near-infrared fluorescence fluorophores (Cy7) and a radioisotope (111In), named as 111In-labeled annexin A5-CCPM. In vitro studies demonstrated that annexin A5-CCPM could strongly and specifically bind to apoptotic cells. In vivo studies showed that apoptotic tissues could be clearly visualized by both single photon emission computed tomography (SPECT) and fluorescence molecular tomography (FMT) after intravenous injection of 111In-labeled Annexin A5-CCPM in 6 different apoptosis models. In contrast, there was little signal in respective healthy tissues. All the biodistribution data confirmed imaging results. Moreover, histological analysis revealed that radioactivity count correlated with fluorescence signal from the nanoparticles, and both signals co-localized with the region of apoptosis. In sum, 111In-labeled annexin A5-CCPM allowed visualization of apoptosis by both nuclear and optical imaging techniques. The complementary information acquired with multiple imaging techniques should be advantageous in improving diagnostics and management of patients.

Invisible social control as predictor of daily negative affect and smoking after a self-set quit date

The dual-effects model of social control proposes that social control leads to increased psychological distress but also to better health practices. However, findings are inconsistent, and recent research suggests that the most effective control is unnoticed by the receiver (i. e., invisible). Yet, investigations of the influence of invisible control on daily negative affect and smoking have been limited. Using daily diaries, we investigated how invisible social control was associated with negative affect and smoking. Overall, 100 smokers (72.0 % men, age M = 40.48, SD = 9.82) and their nonsmoking partners completed electronic diaries from a self-set quit date for 22 consecutive days, reporting received and provided social control, negative affect, and daily smoking. We found in multilevel analyses of the within-person process that on days with higher-than-average invisible control, smokers reported more negative affect and fewer cigarettes smoked. Findings are in line with the assumptions of the dual-effects model of social control: Invisible social control increased daily negative affect and simultaneously reduced smoking at the within-person level.

The effect of nontemporal stimulus size on perceived duration as assessed by the method of reproduction

Perceived duration is assumed to be positively related to nontemporal stimulus magnitude. Most recently, the finding that larger stimuli are perceived to last longer has been challenged to represent a mere decisional bias induced by the use of comparative duration judgments. Therefore, in the present study, the method of temporal reproduction was applied as a psychophysical procedure to quantify perceived duration. Another major goal was to investigate the influence of attention on the effect of visual stimulus size on perceived duration. For this purpose, an additional dual-task paradigm was employed. Our results not only converged with previous findings in demonstrating a functional positive relationship between nontemporal stimulus size and perceived duration, but also showed that the effect of stimulus size on perceived duration was not confined to comparative duration judgments. Furthermore, the effect of stimulus size proved to be independent of attentional resources allocated to stimulus size; nontemporal visual stimulus information does not need to be processed intentionally to influence perceived duration. Finally, the effect of nontemporal stimulus size on perceived duration was effectively modulated by the duration of the target intervals, suggesting a hitherto largely unrecognized role of temporal context for the effect of nontemporal stimulus size to become evident.

Examining invisible social control as predictor of daily smoking and negative affect after a self-set quit date

Objectives: The dual-effects model of social control proposes that social control leads to better health practices, but also arouses psychological distress. However, findings are inconsistent in relation to health behavior and psychological distress. Recent research suggests that the most effective control is unnoticed by the receiver (i.e., invisible). There is some evidence that invisible social control is beneficial for positive and negative affective reactions. Yet, investigations of the influence of invisible social control on daily smoking and distress have been limited. In daily diaries, we investigated how invisible social control is associated with number of cigarettes smoked and negative affect on a daily basis. Methods: Overall, 99 smokers (72.0% men, mean age M = 40.48, SD = 9.82) and their non-smoking partners completed electronic diaries from a self-set quit date for 22 consecutive days within the hour before going to bed, reporting received and provided social control, daily number of cigarettes smoked, and negative affect. Results: Multilevel analyses indicated that between-person levels of invisible social control were associated with lower negative affect, whereas they were unrelated to number of cigarettes smoked. On days with higher-than-average invisible social control, smokers reported less cigarettes smoked and more negative affect. Conclusions: Between-person level findings indicate that invisible social control can be beneficial for negative affect. However, findings on the within-person level are in line with the assumptions of the dual-effects model of social control: Invisible social control reduced daily smoking and simultaneously increased daily negative affect within person.

Retrocrural space involvement on computed tomography as a predictor of mortality and disease severity in acute pancreatitis

BACKGROUND Because computed tomography (CT) has advantages for visualizing the manifestation of necrosis and local complications, a series of scoring systems based on CT manifestations have been developed for assessing the clinical outcomes of acute pancreatitis (AP), including the CT severity index (CTSI), modified CTSI, etc. Despite the internationally accepted CTSI having been successfully used to predict the overall mortality and disease severity of AP, recent literature has revealed the limitations of the CTSI. Using the Delphi method, we establish a new scoring system based on retrocrural space involvement (RCSI), and compared its effectiveness at evaluating the mortality and severity of AP with that of the CTSI. METHODS We reviewed CT images of 257 patients with AP taken within 3-5 days of admission in 2012. The RCSI scoring system, which includes assessment of infectious conditions involving the retrocrural space and the adjacent pleural cavity, was established using the Delphi method. Two radiologists independently assessed the RCSI and CTSI scores. The predictive points of the RCSI and CTSI scoring systems in evaluating the mortality and severity of AP were estimated using receiver operating characteristic (ROC) curves. PRINCIPAL FINDINGS The RCSI score can accurately predict the mortality and disease severity. The area under the ROC curve for the RCSI versus CTSI score was 0.962±0.011 versus 0.900±0.021 for predicting the mortality, and 0.888±0.025 versus 0.904±0.020 for predicting the severity of AP. Applying ROC analysis to our data showed that a RCSI score of 4 was the best cutoff value, above which mortality could be identified. CONCLUSION The Delphi method was innovatively adopted to establish a scoring system to predict the clinical outcome of AP. The RCSI scoring system can predict the mortality of AP better than the CTSI system, and the severity of AP equally as well.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

Early Improvement As a Predictor of Later Response to Antipsychotics in Schizophrenia: A Diagnostic Test Review

OBJECTIVE How long clinicians should wait before considering an antipsychotic ineffective and changing treatment in schizophrenia is an unresolved clinical question. Guidelines differ substantially in this regard. The authors conducted a diagnostic test meta-analysis using mostly individual patient data to assess whether lack of improvement at week 2 predicts later nonresponse. METHOD The search included EMBASE, MEDLINE, BIOSIS, PsycINFO, Cochrane Library, CINAHL, and reference lists of relevant articles, supplemented by requests to authors of all relevant studies. The main outcome was prediction of nonresponse, defined as <50% reduction in total score on either the Positive and Negative Syndrome Scale (PANSS) or Brief Psychiatric Rating Scale (BPRS) (corresponding to at least much improved) from baseline to endpoint (4-12 weeks), by <20% PANSS or BPRS improvement (corresponding to less than minimally improved) at week 2. Secondary outcomes were absent cross-sectional symptomatic remission and <20% PANSS or BPRS reduction at endpoint. Potential moderator variables were examined by meta-regression. RESULTS In 34 studies (N=9,460) a <20% PANSS or BPRS reduction at week 2 predicted nonresponse at endpoint with a specificity of 86% and a positive predictive value (PPV) of 90%. Using data for observed cases (specificity=86%, PPV=85%) or lack of remission (specificity=77%, PPV=88%) yielded similar results. Conversely, using the definition of <20% reduction at endpoint yielded worse results (specificity=70%, PPV=55%). The test specificity was significantly moderated by a trial duration of <6 weeks, higher baseline illness severity, and shorter illness duration. CONCLUSIONS Patients not even minimally improved by week 2 of antipsychotic treatment are unlikely to respond later and may benefit from a treatment change.

Nonparametric Measures of Capacity Utilization: A Dual Approach

This paper develops a nonparametric method of obtaining the minimum of the long run average cost curve of a firm to define its capacity output. This provides a benchmark for measuring of capacity utilization at the observed output level of the firm. In the case of long run constant returns to scale, the minimum of the short run average cost curve is determined to measure short run capacity utilization. An empirical application measures yearly rates of capacity utilization in U.S. manufacturing over the period 1968-1998. Nonparametric determination of the short run average cost curve under variable returns to scale using an iterative search procedure is described in an appendix to this paper.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

Nonlinear dimension reduction in pathway-based genome-wide association analysis

Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

Artificial oxygen fluxes measured by the eddy correlation method using stirring-sensitive oxygen microsensor and oxygen optodes in a flume experiment

In the last decade, the aquatic eddy correlation (EC) technique has proven to be a powerful approach for non-invasive measurements of oxygen fluxes across the sediment water interface. Fundamental to the EC approach is the correlation of turbulent velocity and oxygen concentration fluctuations measured with high frequencies in the same sampling volume. Oxygen concentrations are commonly measured with fast responding electrochemical microsensors. However, due to their own oxygen consumption, electrochemical microsensors are sensitive to changes of the diffusive boundary layer surrounding the probe and thus to changes in the ambient flow velocity. The so-called stirring sensitivity of microsensors constitutes an inherent correlation of flow velocity and oxygen sensing and thus an artificial flux which can confound the benthic flux determination. To assess the artificial flux we measured the correlation between the turbulent flow velocity and the signal of oxygen microsensors in a sealed annular flume without any oxygen sinks and sources. Experiments revealed significant correlations, even for sensors designed to have low stirring sensitivities of ~0.7%. The artificial fluxes depended on ambient flow conditions and, counter intuitively, increased at higher velocities because of the nonlinear contribution of turbulent velocity fluctuations. The measured artificial fluxes ranged from 2 - 70 mmol m**-2 d**-1 for weak and very strong turbulent flow, respectively. Further, the stirring sensitivity depended on the sensor orientation towards the flow. Optical microsensors (optodes) that should not exhibit a stirring sensitivity were tested in parallel and did not show any significant correlation between O2 signals and turbulent flow. In conclusion, EC data obtained with electrochemical sensors can be affected by artificial flux and we recommend using optical microsensors in future EC-studies. Flume experiments were conducted in February 2013 at the Institute for Environmental Sciences, University of Koblenz-Landau Landau. Experiments were performed in a closed oval-shaped acrylic glass flume with cross-sectional width of 4 cm and height of 10 cm and total length of 54 cm. The fluid flow was induced by a propeller driven by a motor and mean flow velocities of up to 20 cm s-1 were generated by applying voltages between 0 V and 4 V DC. The flume was completely sealed with an acrylic glass cover. Oxygen sensors were inserted through rubber seal fittings and allowed positioning the sensors with inclinations to the main flow direction of ~60°, ~95° and ~135°. A Clark type electrochemical O2 microsensor with a low stirring sensitivity (0.7%) was tested and a fast-responding needle-type O2 optode (PyroScience GmbH, Germany) was used as reference as optodes should not be stirring sensitive. Instantaneous three-dimensional flow velocities were measured at 7.4 Hz using stereoscopic particle image velocimetry (PIV). The velocity at the sensor tip was extracted. The correlation of the fluctuating O2 sensor signals and the fluctuating velocities was quantified with a cross-correlation analysis. A significant cross-correlation is equivalent to a significant artificial flux. For a total of 18 experiments the flow velocity was adjusted between 1.7 and 19.2 cm s**-1, and 3 different orientations of the electrochemical sensor were tested with inclination angles of ~60°, ~95° and ~135° with respect to the main flow direction. In experiments 16-18, wavelike flow was induced, whereas in all other experiments the motor was driven by constant voltages. In 7 experiments, O2 was additionally measured by optodes. Although performed simultaneously with the electrochemical sensor, optode measurements are listed as separate experiments (denoted by the attached 'op' in the filename), because the velocity time series was extracted at the optode tip, located at a different position in the flume.

Development of Efficient Techniques for the Analysis and Design of Antennas in Dual-Reflectarray Configuration

This thesis contributes to the analysis and design of printed reflectarray antennas. The main part of the work is focused on the analysis of dual offset antennas comprising two reflectarray surfaces, one of them acts as sub-reflector and the second one acts as mainreflector. These configurations introduce additional complexity in several aspects respect to conventional dual offset reflectors, however they present a lot of degrees of freedom that can be used to improve the electrical performance of the antenna. The thesis is organized in four parts: the development of an analysis technique for dualreflectarray antennas, a preliminary validation of such methodology using equivalent reflector systems as reference antennas, a more rigorous validation of the software tool by manufacturing and testing a dual-reflectarray antenna demonstrator and the practical design of dual-reflectarray systems for some applications that show the potential of these kind of configurations to scan the beam and to generate contoured beams. In the first part, a general tool has been implemented to analyze high gain antennas which are constructed of two flat reflectarray structures. The classic reflectarray analysis based on MoM under local periodicity assumption is used for both sub and main reflectarrays, taking into account the incident angle on each reflectarray element. The incident field on the main reflectarray is computed taking into account the field radiated by all the elements on the sub-reflectarray.. Two approaches have been developed, one which employs a simple approximation to reduce the computer run time, and the other which does not, but offers in many cases, improved accuracy. The approximation is based on computing the reflected field on each element on the main reflectarray only once for all the fields radiated by the sub-reflectarray elements, assuming that the response will be the same because the only difference is a small variation on the angle of incidence. This approximation is very accurate when the reflectarray elements on the main reflectarray show a relatively small sensitivity to the angle of incidence. An extension of the analysis technique has been implemented to study dual-reflectarray antennas comprising a main reflectarray printed on a parabolic surface, or in general in a curved surface. In many applications of dual-reflectarray configurations, the reflectarray elements are in the near field of the feed-horn. To consider the near field radiated by the horn, the incident field on each reflectarray element is computed using a spherical mode expansion. In this region, the angles of incidence are moderately wide, and they are considered in the analysis of the reflectarray to better calculate the actual incident field on the sub-reflectarray elements. This technique increases the accuracy for the prediction of co- and cross-polar patterns and antenna gain respect to the case of using ideal feed models. In the second part, as a preliminary validation, the proposed analysis method has been used to design a dual-reflectarray antenna that emulates previous dual-reflector antennas in Ku and W-bands including a reflectarray as subreflector. The results for the dualreflectarray antenna compare very well with those of the parabolic reflector and reflectarray subreflector; radiation patterns, antenna gain and efficiency are practically the same when the main parabolic reflector is substituted by a flat reflectarray. The results show that the gain is only reduced by a few tenths of a dB as a result of the ohmic losses in the reflectarray. The phase adjustment on two surfaces provided by the dual-reflectarray configuration can be used to improve the antenna performance in some applications requiring multiple beams, beam scanning or shaped beams. Third, a very challenging dual-reflectarray antenna demonstrator has been designed, manufactured and tested for a more rigorous validation of the analysis technique presented. The proposed antenna configuration has the feed, the sub-reflectarray and the main-reflectarray in the near field one to each other, so that the conventional far field approximations are not suitable for the analysis of such antenna. This geometry is used as benchmarking for the proposed analysis tool in very stringent conditions. Some aspects of the proposed analysis technique that allow improving the accuracy of the analysis are also discussed. These improvements include a novel method to reduce the inherent cross polarization which is introduced mainly from grounded patch arrays. It has been checked that cross polarization in offset reflectarrays can be significantly reduced by properly adjusting the patch dimensions in the reflectarray in order to produce an overall cancellation of the cross-polarization. The dimensions of the patches are adjusted in order not only to provide the required phase-distribution to shape the beam, but also to exploit the crosses by zero of the cross-polarization components. The last part of the thesis deals with direct applications of the technique described. The technique presented is directly applicable to the design of contoured beam antennas for DBS applications, where the requirements of cross-polarisation are very stringent. The beam shaping is achieved by synthesithing the phase distribution on the main reflectarray while the sub-reflectarray emulates an equivalent hyperbolic subreflector. Dual-reflectarray antennas present also the ability to scan the beam over small angles about boresight. Two possible architectures for a Ku-band antenna are also described based on a dual planar reflectarray configuration that provides electronic beam scanning in a limited angular range. In the first architecture, the beam scanning is achieved by introducing a phase-control in the elements of the sub-reflectarray and the mainreflectarray is passive. A second alternative is also studied, in which the beam scanning is produced using 1-bit control on the main reflectarray, while a passive subreflectarray is designed to provide a large focal distance within a compact configuration. The system aims to develop a solution for bi-directional satellite links for emergency communications. In both proposed architectures, the objective is to provide a compact optics and simplicity to be folded and deployed.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Predictor paramétrico de glucosa subcutánea

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa (por ejemplo la obtenida a partir de los alimentos ingeridos) llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Hoy en día la tecnología actual permite abordar el desarrollo del llamado “páncreas endocrino artificial”, que consta de un sensor continuo de glucosa subcutánea, una bomba de infusión subcutánea de insulina y un algoritmo de control en lazo cerrado que calcule la dosis de insulina requerida por el paciente en cada momento, según la medida de glucosa obtenida por el sensor y según unos objetivos. El mayor problema que presentan los sistemas de control en lazo cerrado son los retardos, el sensor de glucosa subcutánea mide la glucosa del líquido intersticial, que representa la que hubo en la sangre un tiempo atrás, por tanto, un cambio en los niveles de glucosa en la sangre, debidos por ejemplo, a una ingesta, tardaría un tiempo en ser detectado por el sensor. Además, una dosis de insulina suministrada al paciente, tarda un tiempo aproximado de 20-30 minutos para la llegar a la sangre. Para evitar trabajar en la medida que sea posible con estos retardos, se intenta predecir cuál será el nivel de glucosa en un futuro próximo, para ello se utilizara un predictor de glucosa subcutánea, con la información disponible de glucosa e insulina. El objetivo del proyecto es diseñar una metodología para estimar el valor futuro de los niveles de glucosa obtenida a partir de un sensor subcutáneo, basada en la identificación recursiva del sistema glucorregulatorio a través de modelos lineales y determinando un horizonte de predicción óptimo de trabajo y analizando la influencia de la insulina en los resultados de la predicción. Se ha implementado un predictor paramétrico basado en un modelo autorregresivo ARX que predice con mejor precisión y con menor RMSE que un predictor ZOH a un horizonte de predicción de treinta minutos. Utilizar información relativa a la insulina no tiene efecto en la predicción. El preprocesado, postprocesado y el tratamiento de la estabilidad tienen un efecto muy beneficioso en la predicción. Diabetes mellitusis a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. Nowadays, the actual technology allows raising the development of the “artificial endocrine pancreas”. It involves a continuous glucose sensor, an insulin bump, and a full closed loop algorithm that calculate the insulin units required by patient at any time, according to the glucose measure obtained by the sensor and any target. The main problem of the full closed loop systems is the delays, the glucose sensor measures the glucose in the interstitial fluid that represents the glucose was in the blood some time ago. Because of this, a change in the glucose in blood would take some time to be detected by the sensor. In addition, insulin units administered by a patient take about 20-30 minutes to reach the blood stream. In order to avoid this effect, it will try to predict the glucose level in the near future. To do that, a subcutaneous glucose predictor is used to predict the future glucose with the information about insulin and glucose. The goal of the proyect is to design a method in order to estimate the future valor of glucose obtained by a subcutaneous sensor. It is based on the recursive identification of the regulatory system through the linear models, determining optimal prediction horizon and analyzing the influence of insuline on the prediction results. A parametric predictor based in ARX autoregressive model predicts with better precision and with lesser RMSE than ZOH predictor in a thirty minutes prediction horizon. Using the relative insulin information has no effect in the prediction. The preprocessing, the postprocessing and the stability treatment have many advantages in the prediction.

Column Generation Algorithms for Nonlinear Optimization II: Numerical Investigations

García et al. present a class of column generation (CG) algorithms for nonlinear programs. Its main motivation from a theoretical viewpoint is that under some circumstances, finite convergence can be achieved, in much the same way as for the classic simplicial decomposition method; the main practical motivation is that within the class there are certain nonlinear column generation problems that can accelerate the convergence of a solution approach which generates a sequence of feasible points. This algorithm can, for example, accelerate simplicial decomposition schemes by making the subproblems nonlinear. This paper complements the theoretical study on the asymptotic and finite convergence of these methods given in [1] with an experimental study focused on their computational efficiency. Three types of numerical experiments are conducted. The first group of test problems has been designed to study the parameters involved in these methods. The second group has been designed to investigate the role and the computation of the prolongation of the generated columns to the relative boundary. The last one has been designed to carry out a more complete investigation of the difference in computational efficiency between linear and nonlinear column generation approaches. In order to carry out this investigation, we consider two types of test problems: the first one is the nonlinear, capacitated single-commodity network flow problem of which several large-scale instances with varied degrees of nonlinearity and total capacity are constructed and investigated, and the second one is a combined traffic assignment model