Estimation of denitrification potential with respiration based techniques

Denitrification with its prerequisite process nitrification, is a common practice to remove nitrogen from wastewater in activated sludge systems. Although the key factors detrimental to its performance are well recognised, not all links are implemented for optimal design and operation performance. The relation between detailed wastewater characterisation and denitrification potential (DP) is the most crucial example of information that should be better incorporated in design and optimisation procedures. The lumped parameters COD/N and BOD 5 /N (nowadays used in many design approaches) or empirical values of denitrification rates do not allow to predict precisely the denitrification potential due to a unique character of each activated sludge and wastewater. Advanced activated sludge models require the input of a significant number of parameters. Since the estimation of each parameter is difficult and time consuming, the choice of default values is an option but this can lead to erroneous predictions of reality. Far-simplified models, usually based on on-line measurement of process state variables, describe processes with the simplest kinetics what in turn restricts seriously their implementation.In this thesis a methodology is presented to estimate the DP in relation to wastewater and activated sludge characteristics. Two respiration techniques form the basis for two different approaches: the anoxic nitrate utilisation rate (NUR-) test and the aerobic oxygen utilisation rate (OUR-) test. The approach based on the NUR-test is a direct method for the assessment of the DP. The approach based on the OUR-test is an indirect method because a simplified model is necessary to transform oxygen utilisation rate to nitrate utilisation rate. The NUR-test, except of serving as a tool to estimate directly the DP, enables to acquire simplified denitrification kinetics and a relevant wastewater characterisation, leading consequently to a prediction of the denitrification capacity and nitrate effluent quality. Knowledge about actual activated sludge kinetics and wastewater (or other substrate) characteristics allows to establish relations between sludge loading rate and achievable denitrification rate.The OUR-test was the base to formulate the simplified nitrification-denitrification model, where estimated substrate conversion rates are used without biomass population dynamics. Moreover, the aerobic and anoxic organic biodegradable substrate conversions are modelled with the same relations with the only difference that for anoxic conditions appropriate reduction factors are incorporated in conversion kinetics to reflect a slower activity of activated sludge under denitrifying conditions. A novel methodology based on aerobic and anoxic respiration tests is proposed to estimate the reduction factors. The proposed model approach constitutes an alternative for both complex and far-simplified model approaches. It enables to predict the overall N-removal potential and N-effluent quality of a system, based on an actual detailed wastewater and activated sludge characterisation. Good results from dynamic and static testing of the model implicates its possible implementation in control strategies, like e.g. a feed-back control of the denitrification by a nitrate-rich recycle rate, anoxic volume or the addition of an external carbon source.The effect of a decrease in the biodegradable COD-fraction by pre-treatment (pre-precipitation) on the DP was examined. For an evaluation the developed respiration based methodologies were used to estimate the DP in relation to wastewater and activated sludge characteristics. Implemented optimisation procedures revealed that the original denitrification potential of the wastewater determines the process capacity and efficiency. Optimisation steps by the manipulation of technological parameters in the existing process configuration or control strategies may therefore improve process performance only to small extent.</p

Olfactomedin 4 Serves as a Marker for Disease Severity in Pediatric Respiratory Syncytial Virus (RSV) Infection

Funding: Statement of financial support: The study was financially supported by the VIRGO consortium, an Innovative Cluster approved by the Netherlands Genomics Initiative and partially funded by the Dutch Government (BSIK 03012). The authors have indicated they have no personal financial relationships relevant to this article to disclose. Data Availability Statement: The data is accessible at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE69606.Peer reviewedPublisher PD

Duurzame en robuuste sanitatie door decentralisatie

Kritiek op de huidige centralistische aanpak van sanitatie, transport, behandeling en hergebruik van huishoudelijk afval en afvalwater, en schets van een alternatief: DESAH (Decentrale Sanitatie en Hergebruik), waarbij wordt voldaan aan de criteria duurzaamheid, preventie en robuustheid. Scheiding van afvalstromen, eenvoudige zuiveringssystemen (anaeroob; biologisch), terugwinning van grondstoffen, en hergebruik in huishouden en landbouw spelen een belangrijke ro

Accelerated Sizing of a Power Split Electrified Powertrain

Component sizing generally represents a demanding and time-consuming task in the development process of electrified powertrains. A couple of processes are available in literature for sizing the hybrid electric vehicle (HEV) components. These processes employ either time-consuming global optimization techniques like dynamic programming (DP) or near-optimal techniques that require iterative and uncertain tuning of evaluation parameters like the Pontryagin's minimum principle (PMP). Recently, a novel near-optimal technique has been devised for rapidly predicting the optimal fuel economy benchmark of design options for electrified powertrains. This method, named slope-weighted energy-based rapid control analysis (SERCA), has been demonstrated producing results comparable to DP, while limiting the associated computational time by near two orders of magnitude. In this paper, sizing parameters for a power split electrified powertrain are considered that include the internal combustion engine size, the two electric motor/generator sizes, the transmission ratios, and the final drive ratio. The SERCA approach is adopted to rapidly evaluate the fuel economy capabilities of each sizing option in various driving missions considering both type-approval drive cycles and real-world driving profiles. While screening out for optimal sizing options, the implemented methodology includes drivability criteria along with fuel economy potential. Obtained results will demonstrate the agility of the developed sizing tool in identifying optimal sizing options compared to state-of-the-art sizing tools for electrified powertrains

Behaviour of motor unit action potential rate, estimated from surface EMG, as a measure of muscle activation level

BACKGROUND: Surface electromyography (EMG) parameters such as root-mean-square value (RMS) are commonly used to assess the muscle activation level that is imposed by the central nervous system (CNS). However, RMS is influenced not only by motor control aspects, but also by peripheral properties of the muscle and recording setup. To assess motor control separately, the number of motor unit action potentials (MUAPs) per second, or MUAP Rate (MR) is a potentially useful measure. MR is the sum of the firing rates of the contributing MUs and as such reflects the two parameters that the CNS uses for motor control: number of MUs and firing rate. MR can be estimated from multi-channel surface EMG recordings. The objective of this study was to explore the behaviour of estimated MR (eMR) in relation to number of active MUs and firing rate. Furthermore, the influence of parameters related to peripheral muscle properties and recording setup (number of fibers per MU, fiber diameter, thickness of the subcutaneous layer, signal-to-noise-ratio) on eMR was compared with their influence on RMS. METHODS: Physiological parameters were varied in a simulation model that generated multi-channel EMG signals. The behaviour of eMR in simulated conditions was compared with its behaviour in experimental conditions. Experimental data was obtained from the upper trapezius muscle during a shoulder elevation task (20–100 N). RESULTS: The simulations showed strong, monotonously increasing relations between eMR and number of active MUs and firing rate (r(2 )> 0.95). Because of unrecognized superimpositions of MUAPs, eMR was substantially lower than the actual MUAP Rate (aMR). The percentage of detected MUAPs decreased with aMR, but the relation between eMR and aMR was rather stable in all simulated conditions. In contrast to RMS, eMR was not affected by number of fibers per MU, fiber diameter and thickness of the subcutaneous layer. Experimental data showed a strong relation between eMR and force (individual second order polynomial regression: 0.96 < r(2 )< 0.99). CONCLUSION: Although the actual number of MUAPs in the signal cannot be accurately extracted with the present method, the stability of the relation between eMR and aMR and its independence of muscle properties make eMR a suitable parameter to assess the input from the CNS to the muscle at low contraction levels non-invasively

Advances in surface EMG signal simulation with analytical and numerical descriptions of the volume conductor

Surface electromyographic (EMG) signal modeling is important for signal interpretation, testing of processing algorithms, detection system design, and didactic purposes. Various surface EMG signal models have been proposed in the literature. In this study we focus on 1) the proposal of a method for modeling surface EMG signals by either analytical or numerical descriptions of the volume conductor for space-invariant systems, and 2) the development of advanced models of the volume conductor by numerical approaches, accurately describing not only the volume conductor geometry, as mainly done in the past, but also the conductivity tensor of the muscle tissue. For volume conductors that are space-invariant in the direction of source propagation, the surface potentials generated by any source can be computed by one-dimensional convolutions, once the volume conductor transfer function is derived (analytically or numerically). Conversely, more complex volume conductors require a complete numerical approach. In a numerical approach, the conductivity tensor of the muscle tissue should be matched with the fiber orientation. In some cases (e.g., multi-pinnate muscles) accurate description of the conductivity tensor may be very complex. A method for relating the conductivity tensor of the muscle tissue, to be used in a numerical approach, to the curve describing the muscle fibers is presented and applied to representatively investigate a bi-pinnate muscle with rectilinear and curvilinear fibers. The study thus propose an approach for surface EMG signal simulation in space invariant systems as well as new models of the volume conductor using numerical methods

Olfactomedin 4 serves as a marker for disease severity in pediatric respiratory syncytial virus (RSV) infection

Background: Respiratory viral infections follow an unpredictable clinical course in young children ranging from a common cold to respiratory failure. The transition from mild to severe disease occurs rapidly and is difficult to predict. The pathophysiology underlying disease severity has remained elusive. There is an urgent need to better understand the immune response in this disease to come up with biomarkers that may aid clinical decision making. Methods: In a prospective study, flow cytometric and genome-wide gene expression analyses were performed on blood samples of 26 children with a diagnosis of severe, moderate or mild Respiratory Syncytial Virus (RSV) infection. Differentially expressed genes were validated using Q-PCR in a second