Existence and wandering of bumps in a spiking neural network model

We study spatially localized states of a spiking neuronal network populated by a pulse coupled phase oscillator known as the lighthouse model. We show that in the limit of slow synaptic interactions in the continuum limit the dynamics reduce to those of the standard Amari model. For non-slow synaptic connections we are able to go beyond the standard firing rate analysis of localized solutions allowing us to explicitly construct a family of co-existing one-bump solutions, and then track bump width and firing pattern as a function of system parameters. We also present an analysis of the model on a discrete lattice. We show that multiple width bump states can co-exist and uncover a mechanism for bump wandering linked to the speed of synaptic processing. Moreover, beyond a wandering transition point we show that the bump undergoes an effective random walk with a diffusion coefficient that scales exponentially with the rate of synaptic processing and linearly with the lattice spacing.

Dendritic Cells for SYN Scan Detection

Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and key to the activation of the human immune system, behaviour which has been abstracted to form the Dendritic Cell Algorithm (DCA). In algorithmic terms, individual DCs perform multi-sensor data fusion, asynchronously correlating the fused data signals with a secondary data stream. Aggregate output of a population of cells is analysed and forms the basis of an anomaly detection system. In this paper the DCA is applied to the detection of outgoing port scans using TCP SYN packets. Results show that detection can be achieved with the DCA, yet some false positives can be encountered when simultaneously scanning and using other network services. Suggestions are made for using adaptive signals to alleviate this uncovered problem.

TRIB2 in human AML: a biological and clinical investigation

Acute myeloid leukemia (AML) involves the proliferation, abnormal survival and arrest of cells at a very early stage of myeloid cell differentiation. The biological and clinical heterogeneity of this disease complicates treatment and highlights the significance of understanding the underlying causes of AML, which may constitute potential therapeutic targets, as well as offer prognostic information. Tribbles homolog 2 (Trib2) is a potent murine oncogene capable of inducing transplantable AML with complete penetrance. The pathogenicity of Trib2 is attributed to its ability to induce proteasomal degradation of the full length isoform of the transcription factor CCAAT/enhancer-binding protein alpha (C/EBPα p42). The role of TRIB2 in human AML cells, however, has not been systematically investigated or targeted. Across human cancers, TRIB2 oncogenic activity was found to be associated with its elevated expression. In the context of AML, TRIB2 overexpression was suggested to be associated with the large and heterogeneous subset of cytogenetically normal AML patients. Based upon the observation that overexpression of TRIB2 has a role in cellular transformation, the effect of modulating its expression in human AML was examined in a human AML cell line that expresses high levels of TRIB2, U937 cells. Specific suppression of TRIB2 led to impaired cell growth, as a consequence of both an increase in apoptosis and a decrease in cell proliferation. Consistent with these in vitro results, TRIB2 silencing strongly reduced progression of the U937 in vivo xenografts, accompanied by detection of a lower spleen weight when compared with mice transplanted with TRIB2- expressing control cells. Gene expression analysis suggested that TRIB2 modulates apoptosis and cell-cycle sensitivity by influencing the expression of a subset of genes known to have implications on these phenotypes. Furthermore, TRIB2 was found to be expressed in a significant subset of AML patient samples analysed. To investigate whether increased expression of this gene could be afforded prognostic significance, primary AML cells with dichotomized levels of TRIB2 transcripts were evaluated in terms of their xenoengraftment potential, an assay reported to correlate with disease aggressiveness observed in humans. A small cohort of analysed samples with higher TRIB2 expression did not associate with preferential leukaemic cell engraftment in highly immune-deficient mice, hence, not predicting for an adverse prognosis. However, further experiments including a larger cohort of well characterized AML patients would be needed to clarify TRIB2 significance in the diagnostic setting. Collectively, these data support a functional role for TRIB2 in the maintenance of the oncogenic properties of human AML cells and suggest TRIB2 can be considered a rational therapeutic target. Proteasome inhibition has emerged as an attractive target for the development of novel anti-cancer therapies and results from translational research and clinical trials support the idea that proteasome inhibitors should be considered in the treatment of AML. The present study argued that proteasome inhibition would effectively inhibit the function of TRIB2 by abrogating C/EBPα p42 protein degradation and that it would be an effective pharmacological targeting strategy in TRIB2-positive AMLs. Here, a number of cell models expressing high levels of TRIB2 were successfully targeted by treatment with proteasome inhibitors, as demonstrated by multiple measurements that included increased cytotoxicity, inhibition of clonogenic growth and anti-AML activity in vivo. Mechanistically, it was shown that block of the TRIB2 degradative function led to an increase of C/EBPα p42 and that response was specific to the TRIB2-C/EBPα axis. Specificity was addressed by a panel of experiments showing that U937 cells (express detectable levels of endogenous TRIB2 and C/EBPα) treated with the proteasome inhibitor bortezomib (Brtz) displayed a higher cytotoxic response upon TRIB2 overexpression and that ectopic expression of C/EBPα rescued cell death. Additionally, in C/EBPα-negative leukaemia cells, K562 and Kasumi 1, Brtz-induced toxicity was not increased following TRIB2 overexpression supporting the specificity of the compound on the TRIB2-C/EBPα axis. Together these findings provide pre-clinical evidence that TRIB2- expressing AML cells can be pharmacologically targeted with proteasome inhibition due, in part, to blockage of the TRIB2 proteolytic function on C/EBPα p42. A large body of evidence indicates that AML arises through the stepwise acquisition of genetic and epigenetic changes. Mass spectrometry data has identified an interaction between TRIB2 and the epigenetic regulator Protein Arginine Methyltransferase 5 (PRMT5). Following assessment of TRIB2‟s role in AML cell survival and effective targeting of the TRIB2-C/EBPα degradation pathway, a putative TRIB2/PRMT5 cooperation was investigated in order to gain a deeper understanding of the molecular network in which TRIB2 acts as a potent myeloid oncogene. First, a microarray data set was interrogated for PRMT5 expression levels and the primary enzyme responsible for symmetric dimethylation was found to be transcribed at significantly higher levels in AML patients when compared to healthy controls. Next, depletion of PRMT5 in the U937 cell line was shown to reduce the transformative phenotype in the high expressing TRIB2 AML cells, which suggests that PRMT5 and TRIB2 may cooperate to maintain the leukaemogenic potential. Importantly, PRMT5 was identified as a TRIB2-interacting protein by means of a protein tagging approach to purify TRIB2 complexes from 293T cells. These findings trigger further research aimed at understanding the underlying mechanism and the functional significance of this interplay. In summary, the present study provides experimental evidence that TRIB2 has an important oncogenic role in human AML maintenance and, importantly in such a molecularly heterogeneous disease, provides the rational basis to consider proteasome inhibition as an effective targeting strategy for AML patients with high TRIB2 expression. Finally, the identification of PRMT5 as a TRIB2-interacting protein opens a new level of regulation to consider in AML. This work may contribute to our further understanding and therapeutic strategies in acute leukaemias.

Pattern and function of woody features on the grazing itineraries of Terra Fria, Trás–os–Montes – Portugal

The trees, hedgerows and woods are current configuration of the tree network in several ecological regions of the world. In Trás–os–Montes region, Northeast of Portugal, they are a traditional component of Terra fria landscape and they could be seen in several forms: scatter trees, fencerows, small woodlots, riparian buffer strips, among others. The extensive livestock systems in this region are based on a set of circuits across the landscape. In this practice, flocks interacts with these structures using them for different functions inducing an influence on the itineraries. Our purpose will be focused on the woody features of landscape regarding their configurations, abundance and spacial distribution; in order to examine how the grazing systems depends on the currency of these formations; particularly how species flocks behaviors are related on. Depending on spatial data, The investigation attain to compare the tree network within the agriculture matrix, to the grazed territory crossed by flocks. From the other side, the importance of spatial data on interpreting the issue by suggesting different parameter that may influence the circuits. The recognition of the pressure exerciced by the occurence of the woody structures on the grazed circuits is possible. We believe that the role of these woody structures features in supporting the tradicional silvopastoral systems has been sufficiently strong for change their distribution pattern.

Neuronal networks with gap junctions: A study of piece-wise linear planar neuron models

The presence of gap junction coupling among neurons of the central nervous systems has been appreciated for some time now. In recent years there has been an upsurge of interest from the mathematical community in understanding the contribution of these direct electrical connections between cells to large-scale brain rhythms. Here we analyze a class of exactly soluble single neuron models, capable of producing realistic action potential shapes, that can be used as the basis for understanding dynamics at the network level. This work focuses on planar piece-wise linear models that can mimic the firing response of several different cell types. Under constant current injection the periodic response and phase response curve (PRC) is calculated in closed form. A simple formula for the stability of a periodic orbit is found using Floquet theory. From the calculated PRC and the periodic orbit a phase interaction function is constructed that allows the investigation of phase-locked network states using the theory of weakly coupled oscillators. For large networks with global gap junction connectivity we develop a theory of strong coupling instabilities of the homogeneous, synchronous and splay state. For a piece-wise linear caricature of the Morris-Lecar model, with oscillations arising from a homoclinic bifurcation, we show that large amplitude oscillations in the mean membrane potential are organized around such unstable orbits.

Effect of the cation on the interactions between alkyl methyl imidazolium chloride ionic liquids and water

A systematic study of the interactions between water and alkyl methyl imidazolium chloride ionic liquids at 298.2 K, based on activity coefficients estimated from water activity measurements in the entire solubility range, is presented. The results show that the activity coefficients of water in the studied ILs are controlled by the hydrophilicity of the cation and the cation-anion interaction. To achieve a deeper understanding on the interactions between water and the ILs, COSMO-RS and FTIR spectroscopy were also applied. COSMO-RS was used to predict the activity coefficient of water in the studied ionic liquids along with the excess enthalpies, suggesting the formation of complexes between three molecules of water and one IL molecule. On the basis of quantum-chemical calculations, it is found that cation-anion interaction plays an important role upon the ability of the IL anion to interact with water. The changes in the peak positions/band areas of OH vibrational modes of water as a function of IL concentration were investigated, and the impact of the cation on the hydrogen-bonding network of water is identified and discussed.

A new method for conditioning stochastic groundwater flow models in fractured media

Many geological formations consist of crystalline rocks that have very low matrix permeability but allow flow through an interconnected network of fractures. Understanding the flow of groundwater through such rocks is important in considering disposal of radioactive waste in underground repositories. A specific area of interest is the conditioning of fracture transmissivities on measured values of pressure in these formations. This is the process where the values of fracture transmissivities in a model are adjusted to obtain a good fit of the calculated pressures to measured pressure values. While there are existing methods to condition transmissivity fields on transmissivity, pressure and flow measurements for a continuous porous medium there is little literature on conditioning fracture networks. Conditioning fracture transmissivities on pressure or flow values is a complex problem because the measurements are not linearly related to the fracture transmissivities and they are also dependent on all the fracture transmissivities in the network. We present a new method for conditioning fracture transmissivities on measured pressure values based on the calculation of certain basis vectors; each basis vector represents the change to the log transmissivity of the fractures in the network that results in a unit increase in the pressure at one measurement point whilst keeping the pressure at the remaining measurement points constant. The fracture transmissivities are updated by adding a linear combination of basis vectors and coefficients, where the coefficients are obtained by minimizing an error function. A mathematical summary of the method is given. This algorithm is implemented in the existing finite element code ConnectFlow developed and marketed by Serco Technical Services, which models groundwater flow in a fracture network. Results of the conditioning are shown for a number of simple test problems as well as for a realistic large scale test case.

Financial Statement Analysis for Enterprise Network Design

Part 8: Business Strategies Alignment

COMPUTATIONAL PREDICTION OF THE SPORULATION NETWORK IN CLOSTRIDIUM THERMOCELLUM

Sporulation is a process in which some bacteria divide asymmetrically to form tough protective endospores, which help them to survive in a hazardous environment for a quite long time. The factors which can trigger this process are diverse. Heat, radiation, chemicals and lacking of nutrition can all lead to the formation of endospores. This phenomenon will lead to low productivity during industrial production. However, the sporulation mechanism in a spore-forming bacterium, Clostridium theromcellum, is still unclear. Therefore, if a regulation network of sporulation can be built, we may figure out ways to inhibit this process. In this study, a computational method is applied to predict the sporulation network in Clostridium theromcellum. A working sporulation network model with 40 new predicted genes and 4 function groups is built by using a network construction program, CINPER. 5 sets of microarray expression data in Clostridium theromcellum under different conditions have been collected. The analysis shows the predicted result is reasonable.

Progress in understanding of the molecular basis underlying functional diversification of cyclic di-nucleotide turnover proteins

Cyclic di-GMP was the first cyclic di-nucleotide second messenger described, presaging the discovery of additional cyclic di-nucleotide messengers in bacteria and eukaryotes. The GGDEF diguanylate cyclase (DGC) and EAL and HD-GYP phosphodiesterase (PDE) domains conduct the turnover of cyclic di-GMP. These three unrelated domains belong to superfamilies that exhibit significant variations in function, to include both enzymatically active and inactive members with a subset involved in synthesis and degradation of other cyclic di-nucleotides. Here we summarize current knowledge of sequence and structural varitions that underpin the functional diversification of cyclic di-GMP turnover proteins. Moreover, we highlight that superfamily diversification is not restricted to cyclic di-GMP signaling domains, as particular DHH/DHHA1 domain and HD domain proteins have been shown to act as cyclic di-AMP phosphodiesterases. We conclude with a consideration of the current limitations that such diversity of action places on bioinformatic prediction of the roles of GGDEF, EAL and HD-GYP domain proteins.

Characterization of DNA sequence properties through network and statistical approaches

In this thesis we will see that the DNA sequence is constantly shaped by the interactions with its environment at multiple levels, showing footprints of DNA methylation, of its 3D organization and, in the case of bacteria, of the interaction with the host organisms. In the first chapter, we will see that analyzing the distribution of distances between consecutive dinucleotides of the same type along the sequence, we can detect epigenetic and structural footprints. In particular, we will see that CG distance distribution allows to distinguish among organisms of different biological complexity, depending on how much CG sites are involved in DNA methylation. Moreover, we will see that CG and TA can be described by the same fitting function, suggesting a relationship between the two. We will also provide an interpretation of the observed trend, simulating a positioning process guided by the presence and absence of memory. In the end, we will focus on TA distance distribution, characterizing deviations from the trend predicted by the best fitting function, and identifying specific patterns that might be related to peculiar mechanical properties of the DNA and also to epigenetic and structural processes. In the second chapter, we will see how we can map the 3D structure of the DNA onto its sequence. In particular, we devised a network-based algorithm that produces a genome assembly starting from its 3D configuration, using as inputs Hi-C contact maps. Specifically, we will see how we can identify the different chromosomes and reconstruct their sequences by exploiting the spectral properties of the Laplacian operator of a network. In the third chapter, we will see a novel method for source clustering and source attribution, based on a network approach, that allows to identify host-bacteria interaction starting from the detection of Single-Nucleotide Polymorphisms along the sequence of bacterial genomes.

Automated service provisioning in programmable network infrastructures

Modern networks are undergoing a fast and drastic evolution, with software taking a more predominant role. Virtualization and cloud-like approaches are replacing physical network appliances, reducing the management burden of the operators. Furthermore, networks now expose programmable interfaces for fast and dynamic control over traffic forwarding. This evolution is backed by standard organizations such as ETSI, 3GPP, and IETF. This thesis will describe which are the main trends in this evolution. Then, it will present solutions developed during the three years of Ph.D. to exploit the capabilities these new technologies offer and to study their possible limitations to push further the state-of-the-art. Namely, it will deal with programmable network infrastructure, introducing the concept of Service Function Chaining (SFC) and presenting two possible solutions, one with Openstack and OpenFlow and the other using Segment Routing and IPv6. Then, it will continue with network service provisioning, presenting concepts from Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). These concepts will be applied to network slicing for mission-critical communications and Industrial IoT (IIoT). Finally, it will deal with network abstraction, with a focus on Intent Based Networking (IBN). To summarize, the thesis will include solutions for data plane programming with evaluation on well-known platforms, performance metrics on virtual resource allocations, novel practical application of network slicing on mission-critical communications, an architectural proposal and its implementation for edge technologies in Industrial IoT scenarios, and a formal definition of intent using a category theory approach.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.

Convolutional Neural Network Architectures for Template Matching

The Neural Networks customized and tested in this thesis (WaldoNet, FlowNet and PatchNet) are a first exploration and approach to the Template Matching task. The possibilities of extension are therefore many and some are proposed below. During my thesis, I have analyzed the functioning of the classical algorithms and adapted with deep learning algorithms. The features extracted from both the template and the query images resemble the keypoints of the SIFT algorithm. Then, instead of similarity function or keypoints matching, WaldoNet and PatchNet use the convolutional layer to compare the features, while FlowNet uses the correlational layer. In addition, I have identified the major challenges of the Template Matching task (affine/non-affine transformations, intensity changes...) and solved them with a careful design of the dataset.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.