Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Determination of extreme floods using a distributed hydrological model

Hydrological models developed for extreme precipitation of PMP type are difficult to calibrate because of the scarcity of available data for these events. This article presents the process and results of calibration for a distributed hydrological model at fine scale developed for the estimation of probable maximal floods in the case of a PMP. This calibration is done on two Swiss catchments for two events of summer storms. The calculation done is concentrated on the estimation of the parameters of the model, divided in two parts. The first is necessary for the computation of flow speeds while the second is required for the determination of the initial and final infiltration capacities for each terrain type. The results, validated with the Nash equation show a good correlation between the simulated and observed flows. We also apply this model on two Romanian catchments, showing the river network and estimated flow.

Adenoid Cystic Carcinoma of the Breast: A Rare Cancer Network Study

Purpose/Objective(s): Mammary adenoid cystic carcinoma (ACC) is a rare breast cancer variant. It accounts for less than 0.1% of all invasive breast malignancies. Typically, it presents as a small breast lump with a low propensity to metastasize to regional lymph nodes or distant sites. The aim of this retrospective multicenter Rare Cancer Network study is to assess prognostic factors and patterns of failure in ACC, as well as the role of radiation therapy (RT) in this rare disease. Materials/Methods: Between January 1980 and December 2007, 61 women with breast ACC were included in this study. Median age was 59 years (range, 28-94 years). The majority of the patients had good performance status (49 patients with WHO 0, 12 patients with WHO 1), and 70% of the patients (n = 42) were premenopausal. Surgery consisted of tumorectomy in 35 patients, mastectomy in 20, or quadrantectomy in 6. Median tumor size was 20 mm (range, 6-170 mm). Surgical margins were clear in 50 (82%) patients. Axillary dissection (n = 41) or sentinel node assessment (n = 10) was realized in the majority of the patients. There were 53 (87%) pN0 and 8 pNx (13%) patients. Estrogen (ER) and progesterone receptor (PR) was negative in 43 (71%) and 42 (69%) patients, respectively. In 16 patients (26%), the receptor status was unknown. Adjuvant chemotherapy or hormonotherapy was administered in 8 (13%) and 7 (12%) patients, respectively. Postoperative RT with a median total dose of 50 Gy (1.8-2.0 Gy/fraction; range, 44-70 Gy) was given in 40 patients. Results: With a median follow-up of 79 months (range, 6-285 months), 5-year overall and disease-free survival (DFS) rates were 94% (95% confidence interval [CI]: 88-100%) and 82% (95% CI: 71-93%), respectively. Five-year locoregional control rate was 95% (95% CI: 89-100%). There were only 4 patients with local relapse who were all salvaged successfully, and 4 other patients developed distant metastases. According to the Common Terminology Criteria for Adverse Events v3.0, late toxicity consisted of grade 2-3 cutaneous fibrosis in 4 (10%) patients, grade 1-2 edema in 2 (5%), and grade 3 lung fibrosis in 2 (5%). In univariate analyses, the outcome was influenced neither by the type of surgery nor the use of postoperative RT. However, positive receptor status had a negative influence on the outcome. Multivariate analysis (Cox model) revealed that negative ER (p = 0.006) or PR (p = 0.04) status was associated with improved DFS. Conclusions: ACC of the breast is a relatively indolent disease with excellent local control and survival. The prognosis of patients with ACC is much better than that for patients with other breast cancers, especially those who are ER and PR negative. The role of postoperative RT is not clear. More aggressive treatments may be warranted for patients with positive receptor status.

Outcome and Prognostic Factors in Adenosquamous Carcinoma of the Head and Neck: A Multicenter Rare Cancer Network Study

Purpose/Objective(s): Adenosquamous carcinoma (AC) of the head and neck is a distinct entity first described in 1968. Its natural history is more aggressive than squamous cell carcinoma but this is based on very small series reported in the literature. The goal of this study was to assess the clinical profile, outcome, patterns of failure and prognostic factors in patients with AC of the head and neck treated by radiation therapy (RT) with or without chemotherapy (CT).Materials/Methods: Data from 18 patients with Stage I (n = 3), II (n = 1), III (n = 4), or IVa (n = 10) AC, treated between 1989 and 2009, were collected in a retrospective multicenter Rare Cancer Network study. Median age was 60 years (range, 48 - 73 years). Fourteen patients were male and 4 female. Risk factors, including perineural invasion, lymphangitis, vascular invasion, positive margins, were present in 83% of the patients. Tumor sites included oral cavity in 4, oropharynx in 4, hypopharynx in2, larynx in 2, salivary glands in 2, nasal vestibule in 2, nasopharynx in 1, and maxillary sinus in 1 patient. Surgery (S) was performed in all but 5 patients. S alone was performed in only 1 patient, and definitive RT alone in 3 patients. Fourteen patients received combined modality treatment (S+RT in 10, RT+CT in 2, and all of the three modalities in 2 patients). Median RT dose to the primary and to the nodes was 66 Gy (range, 50 - 72 Gy) and 53 Gy (range, 44 - 66 Gy), respectively (1.8 - 2.0 Gy/fr., 5 fr./ week). In 4 patients, the planning treatment volume included the primary tumor site only. Seven patients were treated with 2D RT, 7 with 3D conformal RT, and 2 with intensity-modulated RT.Results: After a median follow-up period of 38 months (range, 9 - 62 months), 8 patients developed distant metastases (lung, bone, mediastinum, and liver), 6 presented nodal recurrences, and only 4 had a local relapse at the primary site (all in-field recurrences). At last follow-up, 6 patients were alive without disease, 1 alive with disease, 9 died from progressive disease, and 2 died from intercurrent disease. The 3-year and median overall survival, disease-free survival (DFS) and locoregional control rates were 52% (95% confidence interval [CI]: 28 - 76%) and 39 months, 36% (95% CI: 13 - 49%) and 12 months, and 54% (95% CI: 26 - 82%) and 40 months, respectively. In multivariate analysis (Cox model), DFS was negatively influenced by the presence of extracapsular extension (p = 0.02) and advanced stage (IV versus I-III, p = 0.003).Conclusions: Overall prognosis of locoregionally advanced AC remains poor, and distant metastases and nodal relapse occur in almost half of the cases. However, local control is relatively good, and early stage AC patients had prolonged DFS when treated with combined modality treatment.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Diffusion Spectrum Imaging after stroke shows structural changes in the contra-lateral motor network correlating with functional recovery

There is growing interest in understanding the role of the non-injured contra-lateral hemisphere in stroke recovery. In the experimental field, histological evidence has been reported that structural changes occur in the contra-lateral connectivity and circuits during stroke recovery. In humans, some recent imaging studies indicated that contra-lateral sub-cortical pathways and functional and structural cortical networks are remodeling, after stroke. Structural changes in the contra-lateral networks, however, have never been correlated to clinical recovery in patients. To determine the importance of the contra-lateral structural changes in post-stroke recovery, we selected a population of patients with motor deficits after stroke affecting the motor cortex and/or sub-cortical motor white matter. We explored i) the presence of Generalized Fractional Anisotropy (GFA) changes indicating structural alterations in the motor network of patientsâeuro? contra-lateral hemisphere as well as their longitudinal evolution ii) the correlation of GFA changes with patientsâeuro? clinical scores, stroke size and demographics data iii) and a predictive model.

Monitoring network optimisation for spatial data classification using support vector machines

The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

Bone marrow mesenchymal stem cells stabilize already-formed aortic aneurysms more efficiently than vascular smooth muscle cells in a rat model.

PURPOSE: Abdominal aortic aneurysms (AAAs) expand because of aortic wall destruction. Enrichment in Vascular Smooth Muscle Cells (VSMCs) stabilizes expanding AAAs in rats. Mesenchymal Stem Cells (MSCs) can differentiate into VSMCs. We have tested the hypothesis that bone marrow-derived MSCs (BM-MSCs) stabilizes AAAs in a rat model. MATERIAL AND METHODS: Rat Fischer 344 BM-MSCs were isolated by plastic adhesion and seeded endovascularly in experimental AAAs using xenograft obtained from guinea pig. Culture medium without cells was used as control group. The main criteria was the variation of the aortic diameter at one week and four weeks. We evaluated the impact of cells seeding on inflammatory response by immunohistochemistry combined with RT-PCR on MMP9 and TIMP1 at one week. We evaluated the healing process by immunohistochemistry at 4 weeks. RESULTS: The endovascular seeding of BM-MSCs decreased AAA diameter expansion more powerfully than VSMCs or culture medium infusion (6.5% ± 9.7, 25.5% ± 17.2 and 53.4% ± 14.4; p = .007, respectively). This result was sustained at 4 weeks. BM-MSCs decreased expression of MMP-9 and infiltration by macrophages (4.7 ± 2.3 vs. 14.6 ± 6.4 mm(2) respectively; p = .015), increased Tissue Inhibitor Metallo Proteinase-1 (TIMP-1), compared to culture medium infusion. BM-MSCs induced formation of a neo-aortic tissue rich in SM-alpha active positive cells (22.2 ± 2.7 vs. 115.6 ± 30.4 cells/surface units, p = .007) surrounded by a dense collagen and elastin network covered by luminal endothelial cells. CONCLUSIONS: We have shown in this rat model of AAA that BM-MSCs exert a specialized function in arterial regeneration that transcends that of mature mesenchymal cells. Our observation identifies a population of cells easy to isolate and to expand for therapeutic interventions based on catheter-driven cell therapy.

Small but thick enough-the Arabidopsis hypocotyl as a model to study secondary growth.

The continuous production of vascular tissues through secondary growth results in radial thickening of plant organs and is pivotal for various aspects of plant growth and physiology, such as water transport capacity or resistance to mechanical stress. It is driven by the vascular cambium, which produces inward secondary xylem and outward secondary phloem. In the herbaceous plant Arabidopsis thaliana (Arabidopsis), secondary growth occurs in stems, in roots and in the hypocotyl. In the latter, radial growth is most prominent and not obscured by parallel ongoing elongation growth. Moreover, its progression is reminiscent of the secondary growth mode of tree trunks. Thus, the Arabidopsis hypocotyl is a very good model to study basic molecular mechanisms of secondary growth. Genetic approaches have succeeded in the identification of various factors, including peptides, receptors, transcription factors and hormones, which appear to participate in a complex network that controls radial growth. Many of these players are conserved between herbaceous and woody plants. In this review, we will focus on what is known about molecular mechanisms and regulators of vascular secondary growth in the Arabidopsis hypocotyl.

A qualitative continuous model of cellular auxin and brassinosteroid signaling and their crosstalk.

Motivation: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present.Results: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature.

Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

Problèmes dus aux fistules d'hémodialyse: un réseau régional de prise en charge [Problems related to haemodialysis vascular accesses: a regional network of care]

The number of patients treated by haemodialysis (HD) is continuously increasing. The complications associated with vascular accesses represent the first cause of hospitalisation in these patients. Since 2001 nephrologists, surgeons, angiologists and radiologists at the CHUV are working to develop a multidisciplinary model that includes planning and monitoring of HD accesses. In this setting the echo-Doppler represents an important tool of investigation. Every patient is discussed and decisions are taken during a weekly multidisciplinary meeting. A network has been created with nephrologists of peripheral centres and other specialists. This model allows to centralize investigational information and coordinate patient care while keeping and even developing some investigational activities and treatment in peripheral centres.