Maximum Likelihood Methods for Inverse Learning of Optimal Controllers

This paper presents a framework for inverse learning of objective functions for constrained optimal control problems, which is based on the Karush-Kuhn-Tucker (KKT) conditions. We discuss three variants corresponding to different model assumptions and computational complexities. The first method uses a convex relaxation of the KKT conditions and serves as the benchmark. The main contribution of this paper is the proposition of two learning methods that combine the KKT conditions with maximum likelihood estimation. The key benefit of this combination is the systematic treatment of constraints for learning from noisy data with a branch-and-bound algorithm using likelihood arguments. This paper discusses theoretic properties of the learning methods and presents simulation results that highlight the advantages of using the maximum likelihood formulation for learning objective functions.Comment: 21st IFAC World Congres

Social Capital

This paper surveys research on social capital. We explore the concepts that motivate the social capital literature, efforts to formally model social capital using economic theory, the econometrics of social capital, and empirical studies of the role of social capital in various socioeconomic outcomes. While our focus is primarily on the place of social capital in economics, we do consider its broader social science context. We argue that while the social capital literature has produced many insights, a number of conceptual and statistical problems exist with the current use of social capital by social scientists. We propose some ways to strengthen the social capital literature.development, growth, identification, inequality, networks, social capital, trust,

Social Capital

This paper surveys research on social capital. We explore the concepts that motivate the social capital literature, efforts to formally model social capital using economic theory, the econometrics of social capital, and empirical studies of the role of social capital in various socioeconomic outcomes. While our focus is primarily on the place of social capital in economics, we do consider its broader social science context. We argue that while the social capital literature has produced many insights, a number of conceptual and statistical problems exist with the current use of social capital by social scientists. We propose some ways to strengthen the social capital literature.

Non-invasive monitoring of renal transplant recipients: Urinary excretion of soluble adhesion molecules and of the complement-split product C4d

Background: The number of inducible adhesion molecules known to be involved in cell-mediated allograft rejection is still increasing. In addition, recent data describe complement activation during acute humoral allograft rejection. The aim of this study was to assess whether specific molecules from either pathway are excreted into urine and whether they can provide useful diagnostic tools for the monitoring of renal transplant recipients. Methods: Urinary concentrations of soluble adhesion molecules (sICAM-1, sVCAM-1) and of the complement degradation product C4d were determined by standardized ELISA technique in 75 recipients of renal allografts and 29 healthy controls. Patient samples were assigned to four categories according to clinical criteria: group 1: acute steroid-sensitive rejection (ASSR, n=14), group 2: acute steroid-resistant rejection (ASRR, n=12), group 3: chronic allograft dysfunction (CAD, n=20) and group 4: stable graft function (SGF, n=29). Results: All patients with rejection episodes (groups 1-3) had significantly higher values of urinary sC4d compared with healthy controls and patients with stable graft function (p<0.05). The urinary levels of sVCAM-1 were significantly higher in group 2 (ASRR) compared with all other groups (p<0.001). Uniformly low amounts of s-VCAM-1 and complement-split product C4d were excreted by healthy controls (group 0). In contrast, urinary sICAM-1 concentration in healthy controls was almost as high as in group 2 (ASRR) whereas patients with a stable functioning graft (group 4) excreted significantly less sICAM-1 (p<0.05). Conclusion: The evaluation of sVCAM-1 and sC4d excretion in urine can provide a valuable tool with regard to the severity and type of allograft rejection. With respect to long-term allograft survival, serial measurements of these markers should have the potential to detect rejection episodes and prompt immediate treatment. Copyright (C) 2003 S. Karger AG, Basel

Reduced CD40L expression on ex vivo activated CD4+T-lymphocytes from patients with excellent renal allograft function measured with a rapid whole blood flow cytometry procedure

Background: The CD40-CD40L (CD154) costimulatory pathway plays a critical role in the pathogenesis of kidney allograft rejection. In renal transplant biopsies, CD4+ CD40L+ graft-infiltrating cells were detected during chronic rejection in contrast to acute rejection episodes. Using a rapid noninvasive FACS procedure, we were able to demonstrate CD40L upregulation in peripheral blood of patients with chronic renal allograft dysfunction. Materials and Methods: Whole blood from recipients of renal allografts was stimulated with PMA and ion-omycin and measured by flow cytometry. Patients were assigned to three groups based on transplant function. Group 1: 26 patients with excellent renal transplant function; group 2: 28 patients with impaired transplant function; group 3: 14 patients with chronic allograft dysfunction and group 4: 8 healthy controls. Results: The median percentage +/-SEM of CD4+/ CD40L+ cells stimulated ex vivo at 10 ng/ml PMA was as follows: group 1: 28.3 +/- 4.1%; group 2: 18.4 +/- 2.4%; group 3: 50.1 +/- 5.0% and group 4: 40.4 +/- 3.4%. Subdivisions of groups 2 and 3 resulted in different CD40L expression patterns. Patients with increased serum creatinine since the initial phase after transplantation ( groups 2a and 3a) revealed a higher percentage of CD4+ CD40L+ cells than patients showing a gradual increase over time ( groups 2b and 3b). Consequently, patients of group 3a exhibited a significantly reduced transplant function compared with those of group 3b. Conclusion: After PMA + ionomycin stimulation, patients with excellent kidney graft function displayed significantly reduced expression of CD40L surface molecules on CD4+ cells early after transplantation. Those with a chronic dysfunction of the renal graft showed significantly more CD4+ cells expressing CD40L compared to the other transplanted groups. These results demonstrate that the percentage of CD4+ CD40L+ cells stimulated ex vivo in peripheral blood may be a valuable marker for chronic allograft nephropathy. Copyright (C) 2004 S. Karger AG, Basel

Setting Parameters for Biological Models With ANIMO

ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical) nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings

Rhyolite generation prior to a Yellowstone supereruption: insights from the Island Park-Mount Jackson rhyolite series

The Yellowstone volcanic field is one of the largest and best-studied centres of rhyolitic volcanism on Earth, yet it still contains little-studied periods of activity. Such an example is the Island Park–Mount Jackson series, which erupted between the Mesa Falls and Lava Creek caldera-forming events as a series of rhyolitic domes and lavas. Here we present the first detailed characterisation of these lavas and use our findings to provide a framework for rhyolite generation in Yellowstone between 1·3 and 0·6 Ma, as well as to assess whether magmatic evolution hints at a forthcoming super-eruption. These porphyritic (15–40% crystals) lavas contain mostly sanidine and quartz with lesser amounts of plagioclase (consistent with equilibrium magmatic modelling via rhyolite-MELTS) and a complex assemblage of mafic minerals. Mineral compositions vary significantly between crystals in each unit, with larger ranges than expected from a single homogeneous population in equilibrium with its host melt. Oxygen isotopes in quartz and sanidine indicate slight depletions (δ18Omagma of 5·0–6·1‰), suggesting some contribution by localised remelting of hydrothermally altered material in the area of the previous Mesa Falls Tuff-related caldera collapse. The preservation of variable O isotopic compositions in quartz requires crystal entrainment less than a few thousand years prior to eruption. Late entrainment of rhyolitic material is supported by the occurrence of subtly older sanidines dated by single-grain 40Ar/39Ar geochronology. The eruption ages of the lavas show discrete clusters illustrating that extended quiescence (&gt;100 kyr) in magmatic activity may be a recurring feature in Yellowstone volcanism. Ubiquitous crystal aggregates, dominated by plagioclase, pyroxene and Fe–Ti oxides, are interpreted as cumulates co-erupted with their extracted liquid. Identical crystal aggregates are found in both normal-δ18O and low-δ18O rocks from Yellowstone, indicating that common petrogenetic processes characterise both volcanic suites, including the late-stage extraction of melt from an incrementally built upper crustal mush zone