Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network

[EN] Here we present monthly, basin-wide maps of the partial pressure of carbon dioxide (pCO2) for the North Atlantic on a latitude by longitude grid for years 2004 through 2006 inclusive. The maps have been computed using a neural network technique which reconstructs the non-linear relationships between three biogeochemical parameters and marine pCO2. A self organizing map (SOM) neural network has been trained using 389 000 triplets of the SeaWiFSMODIS chlorophyll-a concentration, the NCEP/NCAR reanalysis sea surface temperature, and the FOAM mixed layer depth. The trained SOM was labelled with 137 000 underway pCO2 measurements collected in situ during 2004, 2005 and 2006 in the North Atlantic, spanning the range of 208 to 437atm. The root mean square error (RMSE) of the neural network fit to the data is 11.6?atm, which equals to just above 3 per cent of an average pCO2 value in the in situ dataset. The seasonal pCO2 cycle as well as estimates of the interannual variability in the major biogeochemical provinces are presented and discussed. High resolution combined with basin-wide coverage makes the maps a useful tool for several applications such as the monitoring of basin-wide air-sea CO2 fluxes or improvement of seasonal and interannual marine CO2 cycles in future model predictions. The method itself is a valuable alternative to traditional statistical modelling techniques used in geosciences.

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.

Self-Organizing Mechanisms for Task Allocation in a Knowledge-Based Economy

A prevalent claim is that we are in knowledge economy. When we talk about knowledge economy, we generally mean the concept of “Knowledge-based economy” indicating the use of knowledge and technologies to produce economic benefits. Hence knowledge is both tool and raw material (people’s skill) for producing some kind of product or service. In this kind of environment economic organization is undergoing several changes. For example authority relations are less important, legal and ownership-based definitions of the boundaries of the firm are becoming irrelevant and there are only few constraints on the set of coordination mechanisms. Hence what characterises a knowledge economy is the growing importance of human capital in productive processes (Foss, 2005) and the increasing knowledge intensity of jobs (Hodgson, 1999). Economic processes are also highly intertwined with social processes: they are likely to be informal and reciprocal rather than formal and negotiated. Another important point is also the problem of the division of labor: as economic activity becomes mainly intellectual and requires the integration of specific and idiosyncratic skills, the task of dividing the job and assigning it to the most appropriate individuals becomes arduous, a “supervisory problem” (Hogdson, 1999) emerges and traditional hierarchical control may result increasingly ineffective. Not only specificity of know how makes it awkward to monitor the execution of tasks, more importantly, top-down integration of skills may be difficult because ‘the nominal supervisors will not know the best way of doing the job – or even the precise purpose of the specialist job itself – and the worker will know better’ (Hogdson,1999). We, therefore, expect that the organization of the economic activity of specialists should be, at least partially, self-organized. The aim of this thesis is to bridge studies from computer science and in particular from Peer-to-Peer Networks (P2P) to organization theories. We think that the P2P paradigm well fits with organization problems related to all those situation in which a central authority is not possible. We believe that P2P Networks show a number of characteristics similar to firms working in a knowledge-based economy and hence that the methodology used for studying P2P Networks can be applied to organization studies. Three are the main characteristics we think P2P have in common with firms involved in knowledge economy: - Decentralization: in a pure P2P system every peer is an equal participant, there is no central authority governing the actions of the single peers; - Cost of ownership: P2P computing implies shared ownership reducing the cost of owing the systems and the content, and the cost of maintaining them; - Self-Organization: it refers to the process in a system leading to the emergence of global order within the system without the presence of another system dictating this order. These characteristics are present also in the kind of firm that we try to address and that’ why we have shifted the techniques we adopted for studies in computer science (Marcozzi et al., 2005; Hales et al., 2007 [39]) to management science.

Light harvesting and orbital tuning : perylene monoimides and diimides for photovoltaic purposes

Die vorliegende Dissertation beschaftigt sich mit der Steuerung der Absorption und Orbitalenergien von Perylenmonoimiden und Perylendiimiden fur die Anwendung in organischer Photovoltaik (OPV). Eine breite Absorption spielt hier eine wichtige Rolle, um moglichst viel Licht zu ernten, das dann in elektrische Energie umgewandelt wird. Um sicher zu stellen, dass die Zelle ezient arbeiten kann, ist die Abstimmung von Orbitalenergien eine zweite wichtige Voraussetzung. Es werden drei neue Design-Konzepte fur Perylenmonoimid-Sensibilatoren fur Festk orper-Farbstosolarzellen (solid-state dye-sensitised solar cells - sDSSCs) untersucht. Die Synthese, die optischen und elektronischen Eigenschaften der neuen Sensibilisator- Verbindungen sowie ihre Leistungsdaten in sDSSCs werden beschrieben und diskutiert. Die in dieser Arbeit vorgestellten Konzepte reichen von der Einfuhrung von - Abstandhaltern uber neue Funktionalisierungen bis hin zur Erweiterung der Perylenmonimid Grundkorper. Der Push-Pull-Charakter der Systeme variiert von starker Kopplung bis zu kompletter Entkopplung des Donors vom Akzeptor. Dies hat einen starken Ein uss sowohl auf die Absorptionseigenschaften, als auch auf die HOMO/LUMO Energie-Niveaus der Verbindungen. Einige der Konzepte konnen auf Perylendiimide ubertragen werden. Ein Beispiel von Perylendiimid (PDI)-Farbsteuerung wird an einer Reihe von drei Terthiophen-PDIs gezeigt

Is Acute Fibrinous and Organizing Pneumonia the Expression of Immune Dysregulation?

INTRODUCTION: Acute fibrinous and organizing pneumonia (AFOP) is a recently described histologic pattern of diffuse pulmonary disease. In children, all cases reported to date have been fatal. In this study, we describe the first nonfatal AFOP in a child and review the literature. DESCRIPTION: A 10-year-old boy developed very severe aplastic anemia (VSAA) after being admitted to our hospital with a fulminant hepatic failure of unknown origin. A chest computed tomography scan revealed multiple lung nodules and a biopsy of a pulmonary lesion showed all the signs of AFOP. Infectious workup remained negative. We started immunosuppressive therapy with antithymocyte globulin and cyclosporine to treat VSAA. Subsequent chest computed tomography scans showed a considerable diminution of the lung lesions but the VSAA did not improve until we performed hematopoietic stem cell transplantation 5 months later. CONCLUSIONS: Aplastic anemia is associated with a variety of autoimmune syndromes. The sequence of events in our patient suggests that the hepatic failure, AFOP, and the VSAA may all have been part of an autoimmune syndrome. AFOP could be the result of immune dysregulation in this pediatric case with favorable outcome after immunosuppressive therapy and hematopoietic stem cell transplantation.

High interstitial fluid pressure is associated with low tumour penetration of diagnostic monoclonal antibodies applied for molecular imaging purposes

The human epithelial cell adhesion molecule (EpCAM) is highly expressed in a variety of clinical tumour entities. Although an antibody against EpCAM has successfully been used as an adjuvant therapy in colon cancer, this therapy has never gained wide-spread use. We have therefore investigated the possibilities and limitations for EpCAM as possible molecular imaging target using a panel of preclinical cancer models. Twelve human cancer cell lines representing six tumour entities were tested for their EpCAM expression by qPCR, flow cytometry analysis and immunocytochemistry. In addition, EpCAM expression was analyzed in vivo in xenograft models for tumours derived from these cells. Except for melanoma, all cell lines expressed EpCAM mRNA and protein when grown in vitro. Although they exhibited different mRNA levels, all cell lines showed similar EpCAM protein levels upon detection with monoclonal antibodies. When grown in vivo, the EpCAM expression was unaffected compared to in vitro except for the pancreatic carcinoma cell line 5072 which lost its EpCAM expression in vivo. Intravenously applied radio-labelled anti EpCAM MOC31 antibody was enriched in HT29 primary tumour xenografts indicating that EpCAM binding sites are accessible in vivo. However, bound antibody could only be immunohistochemically detected in the vicinity of perfused blood vessels. Investigation of the fine structure of the HT29 tumour blood vessels showed that they were immature and prone for higher fluid flux into the interstitial space. Consistent with this hypothesis, a higher interstitial fluid pressure of about 12 mbar was measured in the HT29 primary tumour via "wick-in-needle" technique which could explain the limited diffusion of the antibody into the tumour observed by immunohistochemistry.

A multilingual audiometer simulator software for training purposes

A set of algorithms, which allows a computer to determine the answers of simulated patients during pure tone and speech audiometry, is presented. Based on these algorithms, a computer program for training in audiometry was written and found to be useful for teaching purposes.