Information-centric communication in mobile and wireless networks

Information-centric networking (ICN) is a new communication paradigm that has been proposed to cope with drawbacks of host-based communication protocols, namely scalability and security. In this thesis, we base our work on Named Data Networking (NDN), which is a popular ICN architecture, and investigate NDN in the context of wireless and mobile ad hoc networks. In a first part, we focus on NDN efficiency (and potential improvements) in wireless environments by investigating NDN in wireless one-hop communication, i.e., without any routing protocols. A basic requirement to initiate informationcentric communication is the knowledge of existing and available content names. Therefore, we develop three opportunistic content discovery algorithms and evaluate them in diverse scenarios for different node densities and content distributions. After content names are known, requesters can retrieve content opportunistically from any neighbor node that provides the content. However, in case of short contact times to content sources, content retrieval may be disrupted. Therefore, we develop a requester application that keeps meta information of disrupted content retrievals and enables resume operations when a new content source has been found. Besides message efficiency, we also evaluate power consumption of information-centric broadcast and unicast communication. Based on our findings, we develop two mechanisms to increase efficiency of information-centric wireless one-hop communication. The first approach called Dynamic Unicast (DU) avoids broadcast communication whenever possible since broadcast transmissions result in more duplicate Data transmissions, lower data rates and higher energy consumption on mobile nodes, which are not interested in overheard Data, compared to unicast communication. Hence, DU uses broadcast communication only until a content source has been found and then retrieves content directly via unicast from the same source. The second approach called RC-NDN targets efficiency of wireless broadcast communication by reducing the number of duplicate Data transmissions. In particular, RC-NDN is a Data encoding scheme for content sources that increases diversity in wireless broadcast transmissions such that multiple concurrent requesters can profit from each others’ (overheard) message transmissions. If requesters and content sources are not in one-hop distance to each other, requests need to be forwarded via multi-hop routing. Therefore, in a second part of this thesis, we investigate information-centric wireless multi-hop communication. First, we consider multi-hop broadcast communication in the context of rather static community networks. We introduce the concept of preferred forwarders, which relay Interest messages slightly faster than non-preferred forwarders to reduce redundant duplicate message transmissions. While this approach works well in static networks, the performance may degrade in mobile networks if preferred forwarders may regularly move away. Thus, to enable routing in mobile ad hoc networks, we extend DU for multi-hop communication. Compared to one-hop communication, multi-hop DU requires efficient path update mechanisms (since multi-hop paths may expire quickly) and new forwarding strategies to maintain NDN benefits (request aggregation and caching) such that only a few messages need to be transmitted over the entire end-to-end path even in case of multiple concurrent requesters. To perform quick retransmission in case of collisions or other transmission errors, we implement and evaluate retransmission timers from related work and compare them to CCNTimer, which is a new algorithm that enables shorter content retrieval times in information-centric wireless multi-hop communication. Yet, in case of intermittent connectivity between requesters and content sources, multi-hop routing protocols may not work because they require continuous end-to-end paths. Therefore, we present agent-based content retrieval (ACR) for delay-tolerant networks. In ACR, requester nodes can delegate content retrieval to mobile agent nodes, which move closer to content sources, can retrieve content and return it to requesters. Thus, ACR exploits the mobility of agent nodes to retrieve content from remote locations. To enable delay-tolerant communication via agents, retrieved content needs to be stored persistently such that requesters can verify its authenticity via original publisher signatures. To achieve this, we develop a persistent caching concept that maintains received popular content in repositories and deletes unpopular content if free space is required. Since our persistent caching concept can complement regular short-term caching in the content store, it can also be used for network caching to store popular delay-tolerant content at edge routers (to reduce network traffic and improve network performance) while real-time traffic can still be maintained and served from the content store.

The biologic and signaling effects of Tiam1 overexpression in colorectal carcinoma

Cellular migration is essential to many normal cellular processes. In tumor cells, aberrant activation of the normal pathways regulating migration is one of the critical steps in the development of metastasis. Previously, I demonstrated for the first time that overexpression of Tiam1, a guanine nucleotide exchange factor (GNEF) for small G proteins in the Rho family, could alter migration in colorectal tumor cells. ^ This dissertation focuses on the roles of Tiam1 in promoting cell migration, survival, and metastasis of colorectal carcinoma cells, utilizing the model system I developed. To determine the in vivo phenotype of the migratory cell lines, athymic nude mice were injected with cells into the orthotopic site. Several of the mice injected with cells of increased migratory potential had metastases. Thus, the in vitro selection for increased migration resulted in increased metastatic potential in vivo, and therefore, the Tiam1-overexpressing cells provide a model to examine signal transduction pathways important to this process. ^ To examine effects of Tiam1 signaling on small G proteins critical to cellular functions associated with migration, I examined the activation status of the small G proteins Rac, Rho, and Cdc42. The cells of increased migratory potential have increased GTP-bound Rac and Rho, compared to control SW480 cells. Cells that overexpress Tiam1 are more migratory and are resistant to detachment-induced death, or anoikis. To determine which effects and phenotypes were Tiam1-specific, we utilized siRNA to downregulate Tiam1 expression. These results demonstrate that Tiam1 is sufficient but not required for the migration of colorectal carcinoma cells in our model system, and that the biologically selected cells have additional changes that promote migration besides the increase in Tiam1. I also show that Tiam1 protects colorectal carcinoma cells from detachment-induced death, but is not required for anoikis resistance in the biologically selected migratory cells. ^ In summary, my studies demonstrate a heretofore-unknown regulator of phenotypes critical to the development of colorectal carcinoma metastases, overexpression of Tiam1. Understanding the mechanism by which Tiam1 contributes to cellular migration and metastasis is crucial to developing desperately needed new therapies for colorectal carcinoma. ^

Molecular and biochemical analyses of wounding in mesocarp of peach (Prunus persica L. Batsch) ripe fruits

The physiological and molecular responses of ripe fruit to wounding were evaluated in two peach (Prunus persica) varieties ('Glohaven', GH, melting and 'BigTop', BT, slow melting nectarine) by comparing mesocarp samples from wedges (as in minimal processing) and whole fruit as the control. Slight differences between the two varieties were detected in terms of ethylene production, whereas total phenol and flavonoid concentrations, and PPO and POD enzyme activities showed a general increase in wounded GH but not in BT. This was associated with the better appearance of the BT wedges at the end of the experimental period (72 h). Microarray (genome-wide ?PEACH3.0) analysis revealed that a total number of 2218 genes were differentially expressed (p < 0.01, log2 fold change expression ratio >1 or <-1) in GH 24 h after wounding compared to the control. This number was much lower (1208) in BT. According to the enrichment analysis, cell wall, plasma membrane, response to stress, secondary metabolic processes, oxygen binding were the GO categories over-represented among the GH up-regulated genes, whereas plasma membrane and response to endogenous stimulus were the categories over-represented among the down-regulated genes. Only 32 genes showed a common expression trend in the two varieties 24 h after wounding, whereas a total of 512 genes (with highly represented transcription factors), displayed opposite behavior. Quantitative RT-PCR analysis confirmed the microarray data for 18 out of a total of 20 genes selected. Specific WRKY, AP2/ERF and HSP20 genes were markedly up-regulated in wounded GH, indicating the activation of regulatory and signaling mechanisms probably related to different hormone categories. Compared to BT, the expression of specific genes involved in phenylpropanoid and triterpenoid biosynthetic pathways showed a more pronounced induction in GH, highlighting the difference between the two peach varieties in terms of molecular responses to wounding in the mesocarp tissue.

An export strategy and technology networks in the Republic of Korea

In Korea, trade with Japan has had a deficit since the normalization of Japan-Korea diplomatic relations in 1965. Korea’s trade balance with Japan has remained in deficit since then, although Korean companies have become bigger compared to Japanese companies. My hypothesis is that the problem has been caused because Korea introduced technologies from Japan. However, in recent years Korean companies could not introduce technologies through technical cooperation with Japan like in the 1990s. In addition, the Korean government seemed to encourage domestic production for import substitution. Nevertheless, the deficit has continued. I thought it necessary to check my hypothesis in order to discover whether or not it was persuasive.

PSO and neural networks: Optimal combination to solve non linear complex problems

Swarm colonies reproduce social habits. Working together in a group to reach a predefined goal is a social behaviour occurring in nature. Linear optimization problems have been approached by different techniques based on natural models. In particular, Particles Swarm optimization is a meta-heuristic search technique that has proven to be effective when dealing with complex optimization problems. This paper presents and develops a new method based on different penalties strategies to solve complex problems. It focuses on the training process of the neural networks, the constraints and the election of the parameters to ensure successful results and to avoid the most common obstacles when searching optimal solutions.

Floating car data augmentation based on infrastructure sensors and neural networks

The development of new-generation intelligent vehicle technologies will lead to a better level of road safety and CO2 emission reductions. However, the weak point of all these systems is their need for comprehensive and reliable data. For traffic data acquisition, two sources are currently available: 1) infrastructure sensors and 2) floating vehicles. The former consists of a set of fixed point detectors installed in the roads, and the latter consists of the use of mobile probe vehicles as mobile sensors. However, both systems still have some deficiencies. The infrastructure sensors retrieve information fromstatic points of the road, which are spaced, in some cases, kilometers apart. This means that the picture of the actual traffic situation is not a real one. This deficiency is corrected by floating cars, which retrieve dynamic information on the traffic situation. Unfortunately, the number of floating data vehicles currently available is too small and insufficient to give a complete picture of the road traffic. In this paper, we present a floating car data (FCD) augmentation system that combines information fromfloating data vehicles and infrastructure sensors, and that, by using neural networks, is capable of incrementing the amount of FCD with virtual information. This system has been implemented and tested on actual roads, and the results show little difference between the data supplied by the floating vehicles and the virtual vehicles.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Assortative and modular networks are shaped by adaptive synchronization processes

Modular organization and degree-degree correlations are ubiquitous in the connectivity structure of biological, technological, and social interacting systems. So far most studies have concentrated on unveiling both features in real world networks, but a model that succeeds in generating them simultaneously is needed. We consider a network of interacting phase oscillators, and an adaptation mechanism for the coupling that promotes the connection strengths between those elements that are dynamically correlated. We show that, under these circumstances, the dynamical organization of the oscillators shapes the topology of the graph in such a way that modularity and assortativity features emerge spontaneously and simultaneously. In turn, we prove that such an emergent structure is associated with an asymptotic arrangement of the collective dynamical state of the network into cluster synchronization.

Impact of new technologies and social networks on a secondary education theatre project

This paper describes the potential impact of social media and new technologies in secondary education. The case of study has been designed for the drama and theatre subject. A wide set of tools like social networks, blogs, internet, multimedia content, local press and other promotional tools are promoted to increase students’ motivation. The experiment was developed at the highschool IES Al-Satt located in Algete in the Comunidad de Madrid. The students included in the theatre group present a low academic level, 80% of them had previously repeated at least one grade, half of them come from programs for students with learning difficulties and were at risk of social exclusion. This action is supported by higher and secondary education professors and teachers who look forward to implanting networked media technologies as new tools to improve the academic results and the degree of involvement of students. The results of the experiment have been excellent, based on satisfactory opinions obtained from a survey answered by students at the end of the course, and also revealed by the analytics taken from different social networks. This project is a pioneer in the introduction and usage of new technologies in secondary high-schools in Spain.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

Neuronanatomy, neurology and Bayesian networks

Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related quality of life in Parkinson's disease. Most of these challenging problems posed by neuroscience involve new Bayesian network designs that can cope with multiple class variables, small sample sizes, or labels annotated by several experts.

Impaired CD19 expression and signaling, enhanced antibody response to type II T independent antigen and reduction of B-1 cells in CD81-deficient mice

The tetraspanin CD81 is ubiquitously expressed and associated with CD19 on B lymphocytes and with CD4 and CD8 on T lymphocytes. Analysis of mice with disrupted CD81 gene reveals normal T cells but a distinct abnormality in B cells consisting of decreased expression of CD19 and severe reduction in peritoneal B-1 cells. CD81-deficient B cells responded normally to surface IgM crosslinking, but had severely impaired calcium influx following CD19 engagement. CD81-deficient mice had increased serum IgM and IgA and an exaggerated antibody response to the type II T independent antigen TNP-Ficoll. These results suggest that CD81 is important for CD19 signaling and B cell function.

Protein binding and signaling properties of RIN1 suggest a unique effector function

Human RIN1 was first characterized as a RAS binding protein based on the properties of its carboxyl-terminal domain. We now show that full-length RIN1 interacts with activated RAS in mammalian cells and defines a minimum region of 434 aa required for efficient RAS binding. RIN1 interacts with the “effector domain” of RAS and employs some RAS determinants that are common to, and others that are distinct from, those required for the binding of RAF1, a known RAS effector. The same domain of RIN1 that binds RAS also interacts with 14-3-3 proteins, extending the similarity between RIN1 and other RAS effectors. When expressed in mammalian cells, the RAS binding domain of RIN1 can act as a dominant negative signal transduction blocker. The amino-terminal domain of RIN1 contains a proline-rich sequence similar to consensus Src homology 3 (SH3) binding regions. This RIN1 sequence shows preferential binding to the ABL–SH3 domain in vitro. Moreover, the amino-terminal domain of RIN1 directly associates with, and is tyrosine phosphorylated by, c-ABL. In addition, RIN1 encodes a functional SH2 domain that has the potential to activate downstream signals. These data suggest that RIN1 is able to mediate multiple signals. A differential pattern of expression and alternate splicing indicate several levels of RIN1 regulation.

Embryonic mesoderm cells spread in response to platelet-derived growth factor and signaling by phosphatidylinositol 3-kinase.

Abnormal mesoderm movement, leading to defects in axial organization, is observed in mouse and Xenopus laevis embryos deprived of platelet-derived growth factor (PDGF) AA signaling. However, neither the cellular response to PDGF nor the signaling pathways involved are understood. Herein we describe an in vitro assay to examine the direct effect of PDGF AA on aggregates of Xenopus embryonic mesoderm cells. We find that PDGF AA stimulates aggregates to spread on fibronectin. This behavior is similar to that of migrating mesoderm cells in vivo that spread and form lamellipodia and filipodia on contact with fibronectin-rich extracellular matrix. We go on to show two lines of evidence that implicate phosphatidylinositol 3-kinase (PI3K) as an important component of PDGF-induced mesoderm cell spreading. (i) The fungal metabolite wortmannin, which inhibits signaling by PI3K, blocks mesoderm spreading in response to PDGF AA. (ii) Activation of a series of receptors with specific tyrosine-to-phenylalanine mutations revealed PDGF-induced spreading of mesoderm cells depends on PI3K but not on other signaling molecules that interact with PDGF receptors including phospholipase C gamma, Ras GTPase-activating protein, and phosphotyrosine phosphatase SHPTP2. These results indicate that a PDGF signal, medicated by PI3K, can facilitate embryonic mesoderm cell spreading on fibronectin. We propose that PDGF, produced by the ectoderm, influences the adhesive properties of the adjacent mesoderm cells during gastrulation.

Expression and signaling specificity of the IFNAR chain of the type I interferon receptor complex.

The IFNAR chain of the type I interferon (IFN) receptor (IFNIR) undergoes rapid ligand-dependent tyrosine phosphorylation and acts as a species-specific transducer for type I IFN action. Using the vaccinia/T7 expression system to amplify IFNAR expression, we found that human HeLa-S3 cells transiently express high levels of cell surface IFNAR chains (approximately 250,000 chains per cell). Metabolic labeling and immunoblot analysis of transfected HeLa cells show that the IFNAR chain is initially detected as 65-kDa and 98-kDa precursors, and then as the 130-kDa mature protein. Due to variation in N-glycosylation, the apparent molecular mass of the mature IFNAR chain varies from 105 to 135 kDa in different cells. IFNIR structure was characterized in various human cell lines by analyzing 125I-labeled IFN cross-linked complexes recognized by various antibodies against IFNIR subunits and JAK protein-tyrosine kinases. Precipitation of cross-linked material from Daudi cells with anti-IFNAR antibodies showed that IFNAR was present in a 240-kDa complex. Precipitation of cross-linked material from U937 cells with anti-TYK2 sera revealed a 240-kDa complex, which apparently did not contain IFNAR and was not present in IFN-resistant HEC1B cells. The tyrosine phosphorylation and down-regulation of the IFNAR chain were induced by type I IFN in several human cell lines of diverse origins but not in HEC1B cells. However, of type I IFNs, IFN-beta uniquely induced the tyrosine phosphorylation of a 105-kDa protein associated with the IFNAR chain in two lymphoblastoid cell lines (Daudi and U266), demonstrating the specificity of transmembrane signaling for IFN-beta and IFN-alpha through the IFNAR chain.