Topology and Link quality-aware Geographical opportunistic routing in wireless ad-hoc networks

Opportunistic routing (OR) takes advantage of the broadcast nature and spatial diversity of wireless transmission to improve the performance of wireless ad-hoc networks. Instead of using a predetermined path to send packets, OR postpones the choice of the next-hop to the receiver side, and lets the multiple receivers of a packet to coordinate and decide which one will be the forwarder. Existing OR protocols choose the next-hop forwarder based on a predefined candidate list, which is calculated using single network metrics. In this paper, we propose TLG - Topology and Link quality-aware Geographical opportunistic routing protocol. TLG uses multiple network metrics such as network topology, link quality, and geographic location to implement the coordination mechanism of OR. We compare TLG with well-known existing solutions and simulation results show that TLG outperforms others in terms of both QoS and QoE metrics.

Potentials and constraints of modeling for transdisciplinary co-producing strategies for sustainable water governance

Both climate change and socio-economic development will significantly modify the supply and consumption of water in future. Consequently, regional development has to face aggravation of existing or emergence of new conflicts of interest. In this context, transdisciplinary co-production of knowledge is considered as an important means for coping with these challenges. Accordingly, the MontanAqua project aims at developing strategies for more sustainable water management in the study area Crans-Montana-Sierre (Switzerland) in a transdisciplinary way. It strives for co-producing system, target and transformation knowledge among researchers, policy makers, public administration and civil society organizations. The research process basically consisted of the following steps: First, the current water situation in the study region was investigated. How much water is available? How much water is being used? How are decisions on water distribution and use taken? Second, participatory scenario workshops were conducted in order to identify the stakeholders’ visions of regional development. Third, the water situation in 2050 was simulated by modeling the evolution of water resources and water use and by reflecting on the institutional aspects. These steps laid ground for jointly assessing the consequences of the stakeholders’ visions of development in view of scientific data regarding governance, availability and use of water in the region as well as developing necessary transformation knowledge. During all of these steps researchers have collaborated with stakeholders in the support group RegiEau. The RegiEau group consists of key representatives of owners, managers, users, and pressure groups related to water and landscape: representatives of the communes (mostly the presidents), the canton (administration and parliament), water management associations, agriculture, viticulture, hydropower, tourism, and landscape protection. The aim of the talk is to explore potentials and constraints of scientific modeling of water availability and use within the process of transdisciplinary co-producing strategies for more sustainable water governance.

MODELING SPORADIC TUMOR FORMATION DRIVEN BY TELOMERE DYSFUNCTION IN THE GASTROINTESTINAL TRACT

Colorectal cancer is a complex disease that is thought to arise when cells accumulate mutations that allow for uncontrolled growth. There are several recognized mechanisms for generating such mutations in sporadic colon cancer; one of which is chromosomal instability (CIN). One hypothesized driver of CIN in cancer is the improper repair of dysfunctional telomeres. Telomeres comprise the linear ends of chromosomes and play a dual role in cancer. Its length is maintained by the ribonucleoprotein, telomerase, which is not a normally expressed in somatic cells and as cells divide, telomeres continuously shorten. Critically shortened telomeres are considered dysfunctional as they are recognized as sites of DNA damage and cells respond by entering into replicative senescence or apoptosis, a process that is p53-dependent and the mechanism for telomere-induced tumor suppression. Loss of this checkpoint and improper repair of dysfunctional telomeres can initiate a cycle of fusion, bridge and breakage that can lead to chromosomal changes and genomic instability, a process that can lead to transformation of normal cells to cancer cells. Mouse models of telomere dysfunction are currently based on knocking out the telomerase protein or RNA component; however, the naturally long telomeres of mice require multiple generational crosses of telomerase null mice to achieve critically short telomeres. Shelterin is a complex of six core proteins that bind to telomeres specifically. Pot1a is a highly conserved member of this complex that specifically binds to the telomeric single-stranded 3’ G-rich overhang. Previous work in our lab has shown that Pot1a is essential for chromosomal end protection as deletion of Pot1a in murine embryonic fibroblasts (MEFs) leads to open telomere ends that initiate a DNA damage response mediated by ATR, resulting in p53-dependent cellular senescence. Loss of Pot1a in the background of p53 deficiency results in increased aberrant homologous recombination at telomeres and elevated genomic instability, which allows Pot1a-/-, p53-/- MEFs to form tumors when injected into SCID mice. These phenotypes are similar to those seen in cells with critically shortened telomeres. In this work, we created a mouse model of telomere ysfunction in the gastrointestinal tract through the conditional deletion of Pot1a that recapitulates the microscopic features seen in severe telomere attrition. Combined intestinal loss of Pot1a and p53 lead to formation of invasive adenocarcinomas in the small and large intestines. The tumors formed with long latency, low multiplicity and had complex genomes due to chromosomal instability, features similar to those seen in sporadic human colorectal cancers. Taken together, we have developed a novel mouse model of intestinal tumorigenesis based on genomic instability driven by telomere dysfunction.

CAOR: Context-aware Adaptive Opportunistic Routing in Mobile Ad-hoc Networks

Opportunistic routing (OR) employs a list of candidates to improve wireless transmission reliability. However, conventional list-based OR restricts the freedom of opportunism, since only the listed nodes are allowed to compete for packet forwarding. Additionally, the list is generated statically based on a single network metric prior to data transmission, which is not appropriate for mobile ad-hoc networks (MANETs). In this paper, we propose a novel OR protocol - Context-aware Adaptive Opportunistic Routing (CAOR) for MANETs. CAOR abandons the idea of candidate list and it allows all qualified nodes to participate in packet transmission. CAOR forwards packets by simultaneously exploiting multiple cross-layer context information, such as link quality, geographic progress, energy, and mobility.With the help of the Analytic Hierarchy Process theory, CAOR adjusts the weights of context information based on their instantaneous values to adapt the protocol behavior at run-time. Moreover, CAOR uses an active suppression mechanism to reduce packet duplication. Simulation results show that CAOR can provide efficient routing in highly mobile environments. The adaptivity feature of CAOR is also validated.

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

Dispersal Modeling of Fish Early Life Stages: Sensitivity with Application to Atlantic Cod in the Western Gulf of Maine

As an initial step in establishing mechanistic relationships between environmental variability and recruitment in Atlantic cod Gadhus morhua along the coast of the western Gulf of Maine, we assessed transport success of larvae from major spawning grounds to nursery areas with particle tracking using the unstructured grid model FVCOM (finite volume coastal ocean model). In coastal areas, dispersal of early planktonic life stages of fish and invertebrate species is highly dependent on the regional dynamics and its variability, which has to be captured by our models. With state-of-the-art forcing for the year 1995, we evaluate the sensitivity of particle dispersal to the timing and location of spawning, the spatial and temporal resolution of the model, and the vertical mixing scheme. A 3 d frequency for the release of particles is necessary to capture the effect of the circulation variability into an averaged dispersal pattern of the spawning season. The analysis of sensitivity to model setup showed that a higher resolution mesh, tidal forcing, and current variability do not change the general pattern of connectivity, but do tend to increase within-site retention. Our results indicate strong downstream connectivity among spawning grounds and higher chances for successful transport from spawning areas closer to the coast. The model run for January egg release indicates 1 to 19 % within-spawning ground retention of initial particles, which may be sufficient to sustain local populations. A systematic sensitivity analysis still needs to be conducted to determine the minimum mesh and forcing resolution that adequately resolves the complex dynamics of the western Gulf of Maine. Other sources of variability, i.e. large-scale upstream forcing and the biological environment, also need to be considered in future studies of the interannual variability in transport and survival of the early life stages of cod.

Simulating Cortical Development as a Self Constructing Process: A Novel Multi-Scale Approach Combining Molecular and Physical Aspects

Current models of embryological development focus on intracellular processes such as gene expression and protein networks, rather than on the complex relationship between subcellular processes and the collective cellular organization these processes support. We have explored this collective behavior in the context of neocortical development, by modeling the expansion of a small number of progenitor cells into a laminated cortex with layer and cell type specific projections. The developmental process is steered by a formal language analogous to genomic instructions, and takes place in a physically realistic three-dimensional environment. A common genome inserted into individual cells control their individual behaviors, and thereby gives rise to collective developmental sequences in a biologically plausible manner. The simulation begins with a single progenitor cell containing the artificial genome. This progenitor then gives rise through a lineage of offspring to distinct populations of neuronal precursors that migrate to form the cortical laminae. The precursors differentiate by extending dendrites and axons, which reproduce the experimentally determined branching patterns of a number of different neuronal cell types observed in the cat visual cortex. This result is the first comprehensive demonstration of the principles of self-construction whereby the cortical architecture develops. In addition, our model makes several testable predictions concerning cell migration and branching mechanisms.

Modeling episodic fluid-release events in the ductile carbonates of the Glarus thrust

The exposed Glarus thrust displays midcrustal deformation with tens of kilometers of displacement on an ultrathin layer, the principal slip zone (PSZ). Geological observations indicate that this structure resulted from repeated stick-slip events in the presence of highly overpressured fluids. Here we show that the major characteristics of the Glarus thrust movement (localization, periodicity, and evidence of pressurized fluids) can be reconciled by the coupling of two processes, namely, shear heating and fluid release by carbonate decomposition. During this coupling, slow ductile creep deformation raises the temperature through shear heating and ultimately activates the chemical decomposition of carbonates. The subsequent release of highly overpressurized fluids forms and lubricates the PSZ, allowing a ductile fault to move tens of kilometers on millimeter-thick bands in episodic stick-slip events. This model identifies carbonate decomposition as a key process for motion on the Glarus thrust and explains the source of overpressured fluids accessing the PSZ.

Benchmark problems for reactive transport modeling of the generation and attenuation of acid rock drainage

Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions.

The Process-Outcome Mindfulness Effects in Trainees (PrOMET) study: protocol of a pragmatic randomized controlled trial

Background Mindfulness has its origins in an Eastern Buddhist tradition that is over 2500 years old and can be defined as a specific form of attention that is non-judgmental, purposeful, and focused on the present moment. It has been well established in cognitive-behavior therapy in the last decades, while it has been investigated in manualized group settings such as mindfulness-based stress reduction and mindfulness-based cognitive therapy. However, there is scarce research evidence on the effects of mindfulness as a treatment element in individual therapy. Consequently, the demand to investigate mindfulness under effectiveness conditions in trainee therapists has been highlighted. Methods/Design To fill in this research gap, we designed the PrOMET Study. In our study, we will investigate the effects of brief, audiotape-presented, session-introducing interventions with mindfulness elements conducted by trainee therapists and their patients at the beginning of individual therapy sessions in a prospective, randomized, controlled design under naturalistic conditions with a total of 30 trainee therapists and 150 patients with depression and anxiety disorders in a large outpatient training center. We hypothesize that the primary outcomes of the session-introducing intervention with mindfulness elements will be positive effects on therapeutic alliance (Working Alliance Inventory) and general clinical symptomatology (Brief Symptom Checklist) in contrast to the session-introducing progressive muscle relaxation and treatment-as-usual control conditions. Treatment duration is 25 therapy sessions. Therapeutic alliance will be assessed on a session-to-session basis. Clinical symptomatology will be assessed at baseline, session 5, 15 and 25. We will conduct multilevel modeling to address the nested data structure. The secondary outcome measures include depression, anxiety, interpersonal functioning, mindful awareness, and mindfulness during the sessions. Discussion The study results could provide important practical implications because they could inform ideas on how to improve the clinical training of psychotherapists that could be implemented very easily; this is because there is no need for complex infrastructures or additional time concerning these brief session-introducing interventions with mindfulness elements that are directly implemented in the treatment sessions.

Modeling immune functions of the mouse blood-cerebrospinal fluid barrier in vitro: primary rather than immortalized mouse choroid plexus epithelial cells are suited to study immune cell migration across this brain barrier.

BACKGROUND The blood-cerebrospinal fluid barrier (BCSFB) established by the choroid plexus (CP) epithelium has been recognized as a potential entry site of immune cells into the central nervous system during immunosurveillance and neuroinflammation. The location of the choroid plexus impedes in vivo analysis of immune cell trafficking across the BCSFB. Thus, research on cellular and molecular mechanisms of immune cell migration across the BCSFB is largely limited to in vitro models. In addition to forming contact-inhibited epithelial monolayers that express adhesion molecules, the optimal in vitro model must establish a tight permeability barrier as this influences immune cell diapedesis. METHODS We compared cell line models of the mouse BCSFB derived from the Immortomouse(®) and the ECPC4 line to primary mouse choroid plexus epithelial cell (pmCPEC) cultures for their ability to establish differentiated and tight in vitro models of the BCSFB. RESULTS We found that inducible cell line models established from the Immortomouse(®) or the ECPC4 tumor cell line did not express characteristic epithelial proteins such as cytokeratin and E-cadherin and failed to reproducibly establish contact-inhibited epithelial monolayers that formed a tight permeability barrier. In contrast, cultures of highly-purified pmCPECs expressed cytokeratin and displayed mature BCSFB characteristic junctional complexes as visualized by the junctional localization of E-cadherin, β-catenin and claudins-1, -2, -3 and -11. pmCPECs formed a tight barrier with low permeability and high electrical resistance. When grown in inverted filter cultures, pmCPECs were suitable to study T cell migration from the basolateral to the apical side of the BCSFB, thus correctly modelling in vivo migration of immune cells from the blood to the CSF. CONCLUSIONS Our study excludes inducible and tumor cell line mouse models as suitable to study immune functions of the BCSFB in vitro. Rather, we introduce here an in vitro inverted filter model of the primary mouse BCSFB suited to study the cellular and molecular mechanisms mediating immune cell migration across the BCSFB during immunosurveillance and neuroinflammation.

Revealing Assembly of a Pore-Forming Complex Using Single-Cell Kinetic Analysis and Modeling

Many biological processes depend on the sequential assembly of protein complexes. However, studying the kinetics of such processes by direct methods is often not feasible. As an important class of such protein complexes, pore-forming toxins start their journey as soluble monomeric proteins, and oligomerize into transmembrane complexes to eventually form pores in the target cell membrane. Here, we monitored pore formation kinetics for the well-characterized bacterial pore-forming toxin aerolysin in single cells in real time to determine the lag times leading to the formation of the first functional pores per cell. Probabilistic modeling of these lag times revealed that one slow and seven equally fast rate-limiting reactions best explain the overall pore formation kinetics. The model predicted that monomer activation is the rate-limiting step for the entire pore formation process. We hypothesized that this could be through release of a propeptide and indeed found that peptide removal abolished these steps. This study illustrates how stochasticity in the kinetics of a complex process can be exploited to identify rate-limiting mechanisms underlying multistep biomolecular assembly pathways.

Effects of Surface Forcing on Interannual Variability of the Fall Phytoplankton Bloom in the Gulf of Maine Revealed Using a Process-Oriented Model

SeaWiFS (Sea-viewing Wide Field-of-view Sensor) chlorophyll data revealed strong interannual variability in fall phytoplankton dynamics in the Gulf of Maine, with 3 general features in any one year: (1) rapid chlorophyll increases in response to storm events in fall; (2) gradual chlorophyll increases in response to seasonal wind-and cooling-induced mixing that gradually deepens the mixed layer; and (3) the absence of any observable fall bloom. We applied a mixed-layer box model and a 1-dimensional physical-biological numerical model to examine the influence of physical forcing (surface wind, heat flux, and freshening) on the mixed-layer dynamics and its impact on the entrainment of deep-water nutrients and thus on the appearance of fall bloom. The model results suggest that during early fall, the surface mixed-layer depth is controlled by both wind-and cooling-induced mixing. Strong interannual variability in mixed-layer depth has a direct impact on short-and long-term vertical nutrient fluxes and thus the fall bloom. Phytoplankton concentrations over time are sensitive to initial pre-bloom profiles of nutrients. The strength of the initial stratification can affect the modeled phytoplankton concentration, while the timing of intermittent freshening events is related to the significant interannual variability of fall blooms.

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Modeling the survival of T-cell lymphocytes using compound branching processes

Radiotherapy has been a method of choice in cancer treatment for a number of years. Mathematical modeling is an important tool in studying the survival behavior of any cell as well as its radiosensitivity. One particular cell under investigation is the normal T-cell, the radiosensitivity of which may be indicative to the patient's tolerance to radiation doses.^ The model derived is a compound branching process with a random initial population of T-cells that is assumed to have compound distribution. T-cells in any generation are assumed to double or die at random lengths of time. This population is assumed to undergo a random number of generations within a period of time. The model is then used to obtain an estimate for the survival probability of T-cells for the data under investigation. This estimate is derived iteratively by applying the likelihood principle. Further assessment of the validity of the model is performed by simulating a number of subjects under this model.^ This study shows that there is a great deal of variation in T-cells survival from one individual to another. These variations can be observed under normal conditions as well as under radiotherapy. The findings are in agreement with a recent study and show that genetic diversity plays a role in determining the survival of T-cells. ^