Dynamic Modeling and Intermittent Operation of a Flow-Through Microbial Electrolysis Cell

La pile microbienne électrolytique (MEC) représente une nouvelle technologie qui peut être appliquée pour le traitement des eaux usées combiné avec la production d'hydrogène ou de biogaz. La MEC est un dispositif bioélectrochimique, qui contient une anode et une cathode connectées à une alimentation externe. La modélisation dynamique et l'optimisation de réacteurs basés sur une MEC représentent plusieurs défis. Cette thèse commence par la présentation de la MEC de type « circuit équivalent électrique » (EEC), qui fournit un outil pour la surveillance en temps réel et permet l'estimation des paramètres de la MEC. Lors du traitement des eaux usées, une surveillance en continue des MEC est essentielle pour assurer des performances adéquates, et à cet égard, le modèle EEC le permet. Le modèle EEC de base implique deux résistances (R0 décrivant les pertes ohmiques et R1 les pertes d'activation) connectées en série avec la force électromotrice interne (FEI). De plus, la croissance du biofilm est représentée par la capacitance (C) connectée en parallèle avec R1. Ses paramètres électriques internes peuvent être estimés numériquement en minimisant la différence entre le courant théorique et mesuré de la MEC. De plus, les mêmes paramètres peuvent être estimés en utilisant une solution analytique du modèle EEC. Dans ce cas, la MEC doit être utilisée pendant une courte période (par exemple 1 à 2 minutes) avec une connexion intermittente de l'alimentation électrique. Une telle connexion est effectuée à des fréquences hautes et basses pour estimer R0 (à haute fréquence) et R1 et C (à basse fréquence). De plus, la FEI est estimée par la MEC dans des conditions de circuit ouvert. Pour démontrer l'approche proposée, des expériences ont été effectuées avec plusieurs concentrations de sources de carbone entrantes. Les paramètres électriques internes de la MEC ont été estimés à des intervalles de 6h. Le modèle EEC a permis de décrire avec succès la dynamique électrique de la MEC et de suivre les changements des paramètres électriques. Grâce à la simplicité du modèle, il peut être utilisé pour développer un système de surveillance et de diagnostic des MEC en temps réel. Un tel système de suivi en continu pourrait être essentiel au bon fonctionnement des systèmes de traitement des eaux usées à grande échelle basés sur les MEC. Les paramètres du modèle EEC fournissent un aperçu des performances des MEC soumises à diverses perturbations en temps réel. Cette thèse présente des résultats pour la surveillance en temps réel de MEC avec différentes concentrations influentes. Avec l'augmentation de la concentration de l'influent, il y a une diminution subséquente de la résistance interne de la MEC et une augmentation de la C interne. La thèse explique également en détail les performances à long terme de MEC sous connexion intermittente de l'alimentation électrique (mode marche/arrêt). Cette étude décrit une nouvelle approche pour atteindre une performance stable à long terme et maximiser l'élimination de la demande chimique en oxygène (DCO) dans une MEC. Dans l'approche proposée, la tension appliquée sur la MEC est périodiquement déconnectée, par exemple à une fréquence de 0,1 à 0,5 Hz et un rapport cyclique de 90 à 95%. Pour évaluer l'impact d'une telle intermittence de tension sur les performances de la MEC, des expériences ont été réalisées avec deux MEC à écoulement continu avec des électrodes de charbon activé granulaire. La stratégie d'exploitation d’une connexion intermittente a été appliquée à une MEC, tandis que l'autre a fonctionné à une tension fixe (MEC de contrôle). Un fonctionnement intermittent à long terme a entraîné une augmentation progressive de l'efficacité d'élimination de la DCO et du courant de la MEC avec le temps, tandis que la MEC de contrôle a montré des performances inférieures. De plus, en changeant la stratégie d'exploitation et en appliquant une connexion intermittente à la MEC de contrôle, ses performances ont été considérablement améliorées. L'amélioration des performances pendant la phase intermittente a été confirmée par la surveillance en continu de la résistance interne et de la C des MEC. Le mode de fonctionnement intermittent proposé peut être utilisé pour développer un système de traitement des eaux usées à haut débit basé sur les MEC. Un modèle bioélectrochimique dynamique d’une MEC, dont les compartiments anodiques et cathodiques sont connectés en série, est également présenté dans cette thèse. Le modèle peut être utilisé pour estimer le courant circulant dans la MEC et la concentration du substrat de l'effluent. Les paramètres du modèle sont obtenus par une procédure d'estimation des paramètres numériques. Les résultats de la simulation correspondent assez bien aux données expérimentales. La thèse comprend également un modèle de biofilm une dimension (1D), qui décrit les changements de distribution de la source de carbone dans le biofilm électrochimiquement actif à l'anode. Le modèle est capable de prédire le courant obtenu dans une MEC ayant une tension intermittente. ---------- ABSTRACT Microbial electrolysis cell (MEC) represents a novel technology that can be applied for wastewater treatment combined with hydrogen or biogas production. MEC is a bioelectrochemical device, which houses anode and cathode connected to an external power supply. Dynamic modeling and optimization of a MEC-based reactor faces several challenges. This thesis starts from presenting an equivalent electrical circuit (EEC) model of MEC, which provides a tool for online monitoring and parameter estimation of MEC. When treating wastewaters, continuous MEC monitoring is essential to ensure adequate performance, with this regard, the electrical equivalent circuit (EEC) model enables on-line parameter estimation and monitoring of a continuous flow MEC. Such simple EEC model involves two resistances (describing ohmic losses, R0, and activation losses, R1) connected in series with internal electromotive force (EMF). Also, biofilm growth is represented by capacitance (C) connected in parallel with R1. These internal electrical parameters can be estimated numerically by minimizing the difference between the measured and predicted MEC current. Also, the same parameters can be estimated using an analytical solution of the EEC model. In this case, the MEC needs to be operated for a short time (e.g. 1-2 min) with intermittent connection to the power supply. Such intermittent connection is performed at high and low frequencies to estimate R0 (at high frequency) and R1 and C (at low frequency). Also, EMF is estimated by MEC under open circuit conditions. To demonstrate the proposed approach, experiments were carried out at several influent carbon source concentrations. MEC internal electrical parameters were estimated at 6h intervals. The EEC model successfully described electrical dynamics of the MEC and tracked changes in electrical parameters. Owing to the model simplicity, it can be used to develop a real-time MEC monitoring and diagnostics system. Such an on-line tracking system might be essential for successful operation of large scale MEC-based wastewater treatment systems. EEC model parameters provide an insight of MEC performance subjected to various perturbations in real time. This thesis presents results for online monitoring of MEC with different strength of influent concentrations. With the increase in influent concentration there is a subsequent decrease in internal resistance of MEC and increase in internal capacitance. Furthermore, the thesis also explains in detail long term performance of MEC under intermittent connection/disconnection of power supply. This study describes a new approach for achieving stable long-term performance and maximizing removal of chemical oxygen demand (COD) in a Microbial Electrolysis Cell (MEC). In the proposed approach, the MEC applied voltage is periodically disconnected, e.g. at a frequency of 0.1 – 0.5 Hz and a duty cycle of 90-95%. To evaluate the impact of such periodic voltage disconnection (on/off mode) on MEC performance, experiments were carried out in two flow-through MECs with activated granular carbon electrodes. The on/off operating strategy was applied to one MEC, while the other one was operated at a fixed voltage (control MEC). Long-term on/off operation resulted in progressive increase in COD removal efficiency and MEC current over time, while the control MEC showed inferior performance. Furthermore, by changing the operating strategies and applying the on/off strategy to the control MEC, its performance was significantly improved. Performance improvement during on/off operation was confirmed by on-line monitoring of MFC internal resistance and capacitance. The proposed on/off mode of operation can be used to develop a high-rate MEC-based wastewater treatment system. Dynamic bioelectrochemical model of MEC, which considers anodic and cathodic compartments connected in series, is also presented in this thesis. The model can be used to estimate current flowing through the MEC and effluent substrate concentration. Model parameters are estimated by numerical parameter estimation procedure. The simulation results provide a fairly good fit with the experimental data. Thesis also includes 1D biofilm model, which describes changes in carbon source distribution in the electrochemically active biofilm at anode under on/off operation of power supply. The model is able to predict current flowing through the MEC with periodic applied voltage

Long-term performance of a microbial electrolysis cell operated with periodic disconnection of power supply

This study describes a new approach for achieving stable long-term performance and maximizing the removal of chemical oxygen demand (COD) in a Microbial Electrolysis Cell (MEC). In the proposed approach, the MEC power supply is periodically disconnected, e.g. at a frequency of 0.1–0.5 Hz and a duty cycle of 90–95%. To evaluate the impact of such periodic power supply disconnection (on/off mode) on MEC performance, experiments were carried out in two flow-through MECs with activated granular carbon electrodes. The on/off operating strategy was applied to one MEC, while the other one was operated at a fixed voltage (control MEC). Long-term on/off operation resulted in progressive increase in COD removal efficiency (from 80% to 90%) and MEC current over time, while the control MEC showed stable but inferior performance. Furthermore, by changing the operating strategies and applying the on/off approach to the control MEC, its COD removal was increased from 78% to 83% and internal resistance decreased. The proposed on/off mode of operation can be used to develop a high-rate MEC-based wastewater treatment system

CODIE: Controlled Data and Interest Evaluation in Vehicular Named Data Networks

[EN] Recently, named data networking (NDN) has been proposed as a promising architecture for future Internet technologies. NDN is an extension to the content-centric network (CCN) and is expected to support various applications in vehicular communications [ vehicular NDN (VNDN)]. VNDN basically relies on naming the content rather than using end-to-end device names. In VNDN, a vehicle broadcasts an "Interest" packet for the required "content," regardless of end-to-end connectivity with servers or other vehicles and known as a "consumer." In response, a vehicle with the content replies to the Interest packet with a "Data" packet and named as a "provider." However, the simple VNDN architecture faces several challenges such as consumer/provider mobility and Interest/Data packet(s) forwarding. In VNDN, for the most part, the Data packet is sent along the reverse path of the related Interest packet. However, there is no extensive simulated reference available in the literature to support this argument. In this paper, therefore, we first analyze the propagation behavior of Interest and Data packets in the vehicular ad hoc network (VANET) environment through extensive simulations. Second, we propose the "CODIE" scheme to control the Data flooding/broadcast storm in the naive VNDN. The main idea is to allow the consumer vehicle to start hop counter in Interest packet. Upon receiving this Interest by any potential provider, a data dissemination limit (DDL) value stores the number of hops and a data packet needs to travel back. Simulation results show that CODIE forwards fewer copies of data packets processed (CDPP) while achieving similar interest satisfaction rate (ISR), as compared with the naive VNDN. In addition, we also found that CODIE also minimizes the overall interest satisfaction delay (ISD), respectively.This work was supported by the Ministry of Science, ICT and Future Planning, South Korea, under Grant IITP-2015-H8601-15-1002 of the Convergence Information Technology Research Center supervised by the Institute for Information and Communications Technology Promotion. The review of this paper was coordinated by Editors of CVS. (Corresponding author: Dongkyun Kim.)Ahmed, SH.; Bouk, SH.; Yaqub, MA.; Kim, D.; Song, H.; Lloret, J. (2016). CODIE: Controlled Data and Interest Evaluation in Vehicular Named Data Networks. IEEE Transactions on Vehicular Technology. 65(6):3954-3963. https://doi.org/10.1109/TVT.2016.2558650S3954396365

Pro-Environmental Behaviors and Ecological Responsibilities: An Evaluation of Pakistani University Students’ Behavioral Intentions Towards Climate Change

Rapid and devastating changes in climate and environment have affected individuals from all around the globe to indulge in climate change mitigation and adaptation. The aim of this research is to evaluate the role of students in climate change mitigation and adaptation by analyzing their behavioral intentions. We incorporated the theory of planned behavior in evaluating the environmental knowledge among university students in Pakistan. The results implicated that the attitudes, societal norms and perceived behavioral control contributes significantly in an individual’s pro-environmental behavioral intentions. Additionally, education was found to be contributing merely in building attitudes towards pro-environmental behaviors. However the societal norms and individual’s perceived behavioral control were found to be less influenced by the educational background of individuals.This research provides strategic policy suggestions in face of formulating encouraging engagement in deliberative discussions, interaction with scientists, and formulation of community projects to induce education, resources and opportunities which can be beneficial in changing behaviors of individuals on a larger scale in society

How should HIV resources be allocated? Lessons learnt from applying Optima HIV in 23 countries.

INTRODUCTION: With limited funds available, meeting global health targets requires countries to both mobilize and prioritize their health spending. Within this context, countries have recognized the importance of allocating funds for HIV as efficiently as possible to maximize impact. Over the past six years, the governments of 23 countries in Africa, Asia, Eastern Europe and Latin America have used the Optima HIV tool to estimate the optimal allocation of HIV resources. METHODS: Each study commenced with a request by the national government for technical assistance in conducting an HIV allocative efficiency study using Optima HIV. Each study team validated the required data, calibrated the Optima HIV epidemic model to produce HIV epidemic projections, agreed on cost functions for interventions, and used the model to calculate the optimal allocation of available funds to best address national strategic plan targets. From a review and analysis of these 23 country studies, we extract common themes around the optimal allocation of HIV funding in different epidemiological contexts. RESULTS AND DISCUSSION: The optimal distribution of HIV resources depends on the amount of funding available and the characteristics of each country's epidemic, response and targets. Universally, the modelling results indicated that scaling up treatment coverage is an efficient use of resources. There is scope for efficiency gains by targeting the HIV response towards the populations and geographical regions where HIV incidence is highest. Across a range of countries, the model results indicate that a more efficient allocation of HIV resources could reduce cumulative new HIV infections by an average of 18% over the years to 2020 and 25% over the years to 2030, along with an approximately 25% reduction in deaths for both timelines. However, in most countries this would still not be sufficient to meet the targets of the national strategic plan, with modelling results indicating that budget increases of up to 185% would be required. CONCLUSIONS: Greater epidemiological impact would be possible through better targeting of existing resources, but additional resources would still be required to meet targets. Allocative efficiency models have proven valuable in improving the HIV planning and budgeting process

Observation of Exclusive Gamma Gamma Production in p pbar Collisions at sqrt{s}=1.96 TeV

We have observed exclusive \gamma\gamma production in proton-antiproton collisions at \sqrt{s}=1.96 TeV, using data from 1.11 \pm 0.07 fb^{-1} integrated luminosity taken by the Run II Collider Detector at Fermilab. We selected events with two electromagnetic showers, each with transverse energy E_T > 2.5 GeV and pseudorapidity |\eta| < 1.0, with no other particles detected in -7.4 < \eta < +7.4. The two showers have similar E_T and azimuthal angle separation \Delta\phi \sim \pi; 34 events have two charged particle tracks, consistent with the QED process p \bar{p} to p + e^+e^- + \bar{p} by two-photon exchange, while 43 events have no charged tracks. The number of these events that are exclusive \pi^0\pi^0 is consistent with zero and is < 15 at 95% C.L. The cross section for p\bar{p} to p+\gamma\gamma+\bar{p} with |\eta(\gamma)| < 1.0 and E_T(\gamma) > 2.5$ GeV is 2.48^{+0.40}_{-0.35}(stat)^{+0.40}_{-0.51}(syst) pb.Comment: 7 pages, 4 figure

Combined search for the standard model Higgs boson decaying to a bb pair using the full CDF data set

We combine the results of searches for the standard model Higgs boson based on the full CDF Run II data set obtained from sqrt(s) = 1.96 TeV p-pbar collisions at the Fermilab Tevatron corresponding to an integrated luminosity of 9.45/fb. The searches are conducted for Higgs bosons that are produced in association with a W or Z boson, have masses in the range 90-150 GeV/c^2, and decay into bb pairs. An excess of data is present that is inconsistent with the background prediction at the level of 2.5 standard deviations (the most significant local excess is 2.7 standard deviations).Comment: To be published in Phys. Rev. Lett (v2 contains minor updates based on comments from PRL

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Evidence for t\bar{t}\gamma Production and Measurement of \sigma_t\bar{t}\gamma / \sigma_t\bar{t}

Using data corresponding to 6.0/fb of ppbar collisions at sqrt(s) = 1.96 TeV collected by the CDF II detector, we present a cross section measurement of top-quark pair production with an additional radiated photon. The events are selected by looking for a lepton, a photon, significant transverse momentum imbalance, large total transverse energy, and three or more jets, with at least one identified as containing a b quark. The ttbar+photon sample requires the photon to have 10 GeV or more of transverse energy, and to be in the central region. Using an event selection optimized for the ttbar+photon candidate sample we measure the production cross section of, and the ratio of cross sections of the two samples. Control samples in the dilepton+photon and lepton+photon+\met, channels are constructed to aid in decay product identification and background measurements. We observe 30 ttbar+photon candidate events compared to the standard model expectation of 26.9 +/- 3.4 events. We measure the ttbar+photon cross section to be 0.18+0.08 pb, and the ratio of the cross section of ttbar+photon to ttbar to be 0.024 +/- 0.009. Assuming no ttbar+photon production, we observe a probability of 0.0015 of the background events alone producing 30 events or more, corresponding to 3.0 standard deviations.Comment: 9 pages, 3 figure