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This study explores various approaches to formulating a parallel hybrid model (HM) for Water and Resource Recovery Facilities (WRRFs) merging a mechanistic and a data-driven model. In the study, the HM is constructed by training a neural network (NN) on the residual of the mechanistic model for effluent nitrate. In an initial experiment using the Benchmark Simulation Model no. 1, a parallel HM effectively addressed limitations in the mechanistic model's representation of autotrophic bacteria growth and the data-driven model's incapability to extrapolate. Next, different versions of a parallel HM of a large pilot-scale WRRF are constructed, using different calibration/training datasets and different versions of the mechanistic model to investigate the balance between the calibration effort for the mechanistic model and the compensation by the NN component. The HM can improve predictions compared to the mechanistic model. Training the NN on an independent validation dataset produced better results than on the calibration dataset. Interestingly, the best performance is achieved for the HM based on a mechanistic model using default (uncalibrated) parameters. Both long short-term memory (LSTM) and convolutional neural network (CNN) are tested as data-driven components, with a CNN HM (root-mean-squared error (RMSE) = 1.58 mg NO 3 -N/L) outperforming an LSTM HM (RMSE = 4.17 mg NO 3 -N/L)., Competing Interests: The authors declare there is no conflict., (© 2024 The Authors This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/).)

Digital transformation for the water sector has gained momentum in recent years, and many water resource recovery facilities modelers have already started transitioning from developing traditional models to digital twin (DT) applications. DTs simulate the operation of treatment plants in near real time and provide a powerful tool to the operators and process engineers for real-time scenario analysis and calamity mitigation, online process optimization, predictive maintenance, model-based control, and so forth. So far, only a few mature examples of full-scale DT implementations can be found in the literature, which only address some of the key requirements of a DT. This paper presents the development of a full-scale operational DT for the Eindhoven water resource recovery facility in The Netherlands, which includes a fully automated data-pipeline combined with a detailed mechanistic full-plant process model and a user interface co-created with the plant's operators. The automated data preprocessing pipeline provides continuous access to validated data, an influent generator provides dynamic predictions of influent composition data and allows forecasting 48 h into the future, and an advanced compartmental model of the aeration and anoxic bioreactors ensures high predictive power. The DT runs near real-time simulations every 2 h. Visualization and interaction with the DT is facilitated by the cloud-based TwinPlant technology, which was developed in close interaction with the plant's operators. A set of predefined handles are made available, allowing users to simulate hypothetical scenarios such as process and equipment failures and changes in controller settings. The combination of the advanced data pipeline and process model development used in the Eindhoven DT and the active involvement of the operators/process engineers/managers in the development process makes the twin a valuable asset for decision making with long-term reliability. PRACTITIONER POINTS: A full-scale digital twin (DT) has been developed for the Eindhoven WRRF. The Eindhoven DT includes an automated continuous data preprocessing and reconciliation pipeline. A full-plant mechanistic compartmental process model of the plant has been developed based on hydrodynamic studies. The interactive user interface of the Eindhoven DT allows operators to perform what-if scenarios on various operational settings and process inputs. Plant operators were actively involved in the DT development process to make a reliable and relevant tool with the expected added value., (© 2024 Water Environment Federation.)

An improved 1D reactive settler model is pursued in order to increase the understanding of reactive settling processes and obtain a better prediction of the nitrogen mass balance in wastewater treatment systems. The developed model is based on the 1D Bürger-Diehl settler model with compression function and the Activated Sludge Model No. 1 biological reactions. Specific attention was paid in the model development phase to optimal selection of settling velocity functions and integration of the correct clarifier geometry. A unique measurement campaign was carried out with different operational scenarios to quantify the denitrification in a secondary settling tank. A detailed step-wise calibration effort demonstrated that by choosing an appropriate settling velocity function (power-law structure) and considering the true clarifier geometry allows to accurately capture the biomass concentration profile, total sludge mass, sludge blanket height, and the reaction rates. The resulting model is able to accurately describe total suspended solids (TSS) and nitrate concentration profiles throughout a settling tank under different operational conditions. As such the model can be applied in further scenario analysis and system optimization. PRACTITIONER POINTS: A unique measurement campaign was carried out to obtain detailed data for a reactive settler model development. A 1-D reactive settler model is developed based on the Bürger-Diehl framework including ASM1 biokinetics and the clarifier geometry. An extensive calibration and model selection effort was performed. The model accurately predicts measured concentration profiles in the settling tank. The developed model can be integrated in a plant-wide model to properly calculate the nitrogen mass balance of a WRRF., (© 2022 Water Environment Federation.)

Mathematical modelling is an indispensable tool to support water resource recovery facility (WRRF) operators and engineers with the ambition of creating a truly circular economy and assuring a sustainable future. Despite the successful application of mechanistic models in the water sector, they show some important limitations and do not fully profit from the increasing digitalisation of systems and processes. Recent advances in data-driven methods have provided options for harnessing the power of Industry 4.0, but they are often limited by the lack of interpretability and extrapolation capabilities. Hybrid modelling (HM) combines these two modelling paradigms and aims to leverage both the rapidly increasing volumes of data collected, as well as the continued pursuit of greater process understanding. Despite the potential of HM in a sector that is undergoing a significant digital and cultural transformation, the application of hybrid models remains vague. This article presents an overview of HM methodologies applied to WRRFs and aims to stimulate the wider adoption and development of HM. We also highlight challenges and research needs for HM design and architecture, good modelling practice, data assurance, and software compatibility. HM is a paradigm for WRRF modelling to transition towards a more resource-efficient, resilient, and sustainable future.

Digital Twins (DTs) are on the rise as innovative, powerful technologies to harness the power of digitalisation in the WRRF sector. The lack of consensus and understanding when it comes to the definition, perceived benefits and technological needs of DTs is hampering their widespread development and application. Transitioning from traditional WRRF modelling practice into DT applications raises a number of important questions: When is a model's predictive power acceptable for a DT? Which modelling frameworks are most suited for DT applications? Which data structures are needed to efficiently feed data to a DT? How do we keep the DT up to date and relevant? Who will be the main users of DTs and how to get them involved? How do DTs push the water sector to evolve? This paper provides an overview of the state-of-the-art, challenges, good practices, development needs and transformative capacity of DTs for WRRF applications.

This work gives an overview of the state-of-the-art in modelling of short-cut processes for nitrogen removal in mainstream wastewater treatment and presents future perspectives for directing research efforts in line with the needs of practice. The modelling status for deammonification (i.e., anammox-based) and nitrite-shunt processes is presented with its challenges and limitations. The importance of mathematical models for considering N 2 O emissions in the design and operation of short-cut nitrogen removal processes is considered as well. Modelling goals and potential benefits are presented and the needs for new and more advanced approaches are identified. Overall, this contribution presents how existing and future mathematical models can accelerate successful full-scale mainstream short-cut nitrogen removal applications.

Mathematical modelling is increasingly used to improve the design, understanding, and operation of water systems. Two modelling paradigms, i.e., mechanistic and data-driven modelling, are dominant in the water sector, both with their advantages and drawbacks. Hybrid modelling aims to combine the strengths of both paradigms. Here, we introduce a novel framework that incorporates a data-driven component into an existing activated sludge model of a water resource recovery facility. In contrast to previous efforts, we tightly integrate both models by incorporating a neural differential equation into an existing mechanistic ODE model. This machine learning component fills in the knowledge gaps of the mechanistic model. We show that this approach improves the predictive capabilities of the mechanistic model and is able to extrapolate to unseen conditions, a problematic task for data-driven models. This approach holds tremendous potential for systems that are difficult to model using the mechanistic paradigm only., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Water management in most of the developed world is currently practiced in a highly centralized manner, leading to major infrastructure and energy costs to transport water. To decrease the impacts of water scarcity and climate change, the decentralization of water can increase local robustness. In extremis, decentralization can involve building or house level water supply and treatment. Here, we constructed a MATLAB/Simulink model for two decentralized water management configurations at the household level, assuming the socio-environmental setting of Flanders, Belgium. Independence from the potable water grid and sewer system was pursued through rainwater harvesting, reuse of wastewater streams fit-for-purpose, and discharge via infiltration. The mass balance for water was calculated over the system boundaries showing high potential for independence from the grid with a reasonable treatment train and storage options. Next, the risk of contaminant accumulation within the circular system was assessed, showing a key limitation on decentralized system performance necessitating a system purge. Up to 59% of system rainwater usage was due to the replacement of this purge. Employing treatment units with high (95%) contaminant rejection efficiencies eliminated contaminant accumulation issues. The raw model output was quantitatively assessed by constructing four newly proposed key performance indicators (KPIs), quantifying system independence, circularity, drought tolerance and local water body recharge, which allowed for facilitated system comparison and communication to stakeholders. A sensitivity analysis was performed in which the effect of input parameter variability and uncertainty on system performance was quantified. The sensitivity analysis showed the importance of water recovery and contaminant removal efficiencies of the applied treatment technologies on system performance when contaminant accumulation in the system forms an issue. In systems not severely affected by pollutant accumulation, parameters such as inhabitant number and roof surface had the largest effect. As a whole, this work shows the potential of extreme decentralization of water systems and addresses the obstacle towards implementation formed by the accumulation of contaminants due to system circularity. Additionally, this study provides a framework for operational and technological decision support of decentralized household-scale water systems and, by extension, for future water policy-making., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

We present a compartmental extended SEIQRD metapopulation model for SARS-CoV-2 spread in Belgium. We demonstrate the robustness of the calibration procedure by calibrating the model using incrementally larger datasets and dissect the model results by computing the effective reproduction number at home, in workplaces, in schools, and during leisure activities. We find that schools and home contacts are important transmission pathways for SARS-CoV-2 under lockdown measures. School reopening has the potential to increase the effective reproduction number from R e =0.66±0.04 (95 % CI) to R e =1.09±0.05 (95 % CI) under lockdown measures. The model accounts for the main characteristics of SARS-CoV-2 transmission and COVID-19 disease and features a detailed representation of hospitals with parameters derived from a dataset consisting of 22 136 hospitalized patients. Social contact during the pandemic is modeled by scaling pre-pandemic contact matrices with Google Community Mobility data and with effectivity-of-contact parameters inferred from hospitalization data. The calibrated social contact model with its publically available mobility data, although coarse-grained, is a cheap and readily available alternative to social-epidemiological contact studies under lockdown measures, which were not available at the start of the pandemic., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Antimicrobial and/or preservative ingredients incorporated in wound care products are subjected to certain safety restrictions. However, several of those agents, and paraben preservatives in particular, have been criticised. Conflicting reports on the potential of parabens to induce allergic contact dermatitis, and their assumed oestrogen-like activity, raised public health concerns about their overall safety. Here, we seek to provide a balanced perspective on the most significant purported adverse health effects, and thereby allay the many misconceptions regarding the safety of parabens. Extensive and long-term monitoring of paraben allergy frequencies illustrate that allergic reactions are quite uncommon, especially when compared with other antimicrobial and preservative agents. The estrogenic potential of parabens was illustrated to be far less potent than that of natural oestrogen receptor ligands, and the etiological significance of their presence in human tissue has not been established. The general consensus based on investigations by both the scientific community and regulatory agencies indicates that, with current safety regulations regarding their use in place, this effective and well-documented group of preservatives should not warrant drastic measures to replace them. As such, despite the ongoing concern, it is indicated that, when used at typical concentrations, parabens are unlikely to affect human health., (© 2020 The Authors. International Wound Journal published by Medicalhelplines.com Inc (3M) and John Wiley & Sons Ltd.)

Zinc metalloprotease 1 (Zmp1) is an extracellular enzyme, which has been found essential for the intracellular survival and pathogenesis of Mycobacterium tuberculosis. In this work, we designed and synthesized a series of novel thiazolidinedione-hydroxamates and evaluated in silico their drug-likeness behavior. Then, their inhibitory properties towards a recombinant Zmp1 from Mycobacterium tuberculosis were analyzed by MALDI-TOF MS. Nine of the tested compounds were found to inhibit the enzymatic reaction more effectively than the generic metalloprotease inhibitor phosphoramidon. Furthermore, the synthesized thiazolidinedione-hydroxamate hybrids were evaluated for their in vitro antimycobacterial activity and acute cytotoxicity using whole-cell assays. Results showed that none of the hybrids exhibited acute cytotoxicity against RAW264.7 macrophages. Whereas extracellular antimycobacterial activity was limited, RAW264.7 macrophage infection results showed that a majority of the hybrids inhibited the intracellular growth of Mycobacterium tuberculosis at a concentration of 100 and 10 μM. The thiazolidinedione-hydroxamate compound 2n was considered to be the best candidate of the evaluated library., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Tuberculosis (TB) still has a major impact on public health. In order to efficiently eradicate this life-threatening disease, the exploration of novel anti-TB drugs is of paramount importance. As part of our program to design new 2-azaanthraquinones with anti-mycobacterial activity, various "out-of-plane" tetrahydro- and octahydrobenzo[j]phenanthridinediones were synthesized. In this study, the scaffold of the most promising hits was further optimized in an attempt to improve the bioactivity and to decrease enzymatic degradation. The rudiment bio-evaluation of a small library of fluorinated tetrahydrobenzo[j]phenanthridine-7,12-dione derivatives indicated no significant improvement of the bio-activity against intracellular and extracellular Mycobacterium tuberculosis (Mtb). Though, the derivatives showed an acceptable toxicity against J774A.1 macrophages and early signs of genotoxicity were absent. All derivatives showed to be metabolic stabile in the presence of both phase I and phase II murine or human microsomes. Finally, the onset of reactive oxygen species within Mtb after exposure to the derivatives was measured by electron paramagnetic resonance (EPR). Results showed that the most promising fluorinated derivative is still a possible candidate for the subversive inhibition of mycothione reductase., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

The ever-increasing incidence of drug-resistant Mycobacterium tuberculosis infections has invigorated the focus on the discovery and development of novel treatment options. The discovery and investigation of essential mycobacterial targets is of utmost importance. In addition to the discovery of novel targets, focusing on non-lethal pathways and the use of host-directed therapies has gained interest. These adjunctive treatment options could not only lead to increased antibiotic susceptibility of Mycobacterium tuberculosis , but also have the potential to avoid the emergence of drug resistance. Host-directed therapies, on the other hand, can also reduce the associated lung pathology and improve disease outcome. This review will provide an outline of recent opportunities.

In this study, a small library of twenty benzo[g]isoquinoline-5,10-diones were synthesized in a novel straightforward approach, starting from 2-methyl-1,4-naphthoquinone (vitamin K). An intramolecular Heck reaction of a N-vinylacetamide was a crucial step in the synthetic route, at which the combination of cesium carbonate and a bulky, electron rich trialkylphosphine (tBuCy2P.HBF4) provided high 6-endo-trig selectivity. The anti-tubercular activity against Mycobacterium tuberculosis H37Ra and acute cytotoxicity against J774 A.1 macrophages were studied. From the structure activity relationship, it could be derived that in general the substitution of position 3 yielded analogs with a higher antitubercular potency. Among these, two analogs, 27a and 27b, showed remarkable activity with minimal inhibition concentrations of respectively 28.92 μM and 1.05 μM, and acute cytotoxic concentrations of >128 μM and 34.85 μM. In addition, the analogs and their possible metabolites were evaluated using a Vitotox™ assay to study the possibility of genotoxicity. Results indicated that none of the evaluated analogs and their possible metabolites showed early signs of genotoxicity.

Streptococcus pneumoniae is the leading cause of bacterial pneumonia. Infection is linked to high morbidity and mortality rates and antibiotic resistance within this pathogen is on the rise. Therefore, there is a need for novel antimicrobial therapies. To lower the time and costs of the drug discovery process, alternative in vivo models should be considered. As such, Galleria mellonella larvae can be of great value. The larval immunity consisting of several types of haemocytes is remarkably similar to the human innate immune system. Furthermore, these larvae don't require specific housing, are cheap and are easy to handle. In this study, the use of a G. mellonella infection model to study early pneumococcal infections and treatment is proposed. Firstly, the fitness of this model to study pneumococcal virulence factors is confirmed using streptococcal strains TIGR4, ATCC ® 49619, D39 and its capsule-deficient counterpart R6 at different inoculum sizes. The streptococcal polysaccharide capsule is considered the most important virulence factor without which streptococci are unable to sustain an in vivo infection. Kaplan-Meier survival curves showed indeed a higher larval survival after infection with streptococcal strain R6 compared to strain D39. Then, the infection was characterized by determining the number of haemocytes, production of oxygen free radicals and bacterial burden at several time points during the course of infection. Lastly, treatment of infected larvae with the standard antibiotics amoxicillin and moxifloxacin was evaluated. Treatment has proven to have a positive outcome on the course of infection, depending on the administered dosage. These data imply that G. mellonella larvae can be used to evaluate antimicrobial therapies against S. pneumoniae , apart from using the larval model to study streptococcal properties. The in-depth knowledge acquired regarding this model, makes it more suitable for use in future research.

The wastewater industry is currently facing dramatic changes, shifting away from energy-intensive wastewater treatment towards low-energy, sustainable technologies capable of achieving energy positive operation and resource recovery. The latter will shift the focus of the wastewater industry to how one could manage and extract resources from the wastewater, as opposed to the conventional paradigm of treatment. Debatable questions arise: can the more complex models be calibrated, or will additional unknowns be introduced? After almost 30 years using well-known International Water Association (IWA) models, should the community move to other components, processes, or model structures like 'black box' models, computational fluid dynamics techniques, etc.? Can new data sources - e.g. on-line sensor data, chemical and molecular analyses, new analytical techniques, off-gas analysis - keep up with the increasing process complexity? Are different methods for data management, data reconciliation, and fault detection mature enough for coping with such a large amount of information? Are the available calibration techniques able to cope with such complex models? This paper describes the thoughts and opinions collected during the closing session of the 6th IWA/WEF Water Resource Recovery Modelling Seminar 2018. It presents a concerted and collective effort by individuals from many different sectors of the wastewater industry to offer past and present insights, as well as an outlook into the future of wastewater modelling.

Cellulose, mostly in the form of toilet paper, forms a major component of the particulates in raw municipal wastewater, which could lead to significant consequences due to the potential accumulation of cellulosic fibers and slow biodegradability. Despite the sparse reports on cellulose content and degradation in wastewater and sludge, an accurate and validated method for its quantification in such matrices does not exist. In this paper, four different methods were compared including dilute acid hydrolysis, concentrated acid hydrolysis, enzymatic hydrolysis, and the Schweitzer reagent method. The Schweitzer reagent method, applied to municipal wastewater and sludge, was found to be a very robust and reliable quantification method in light of its reproducibility, accuracy, and ideal (100%) recovery. The determination of cellulose content is critical to understand its fate in wastewater treatment plants as well as improve sludge management and enhance resource recovery.

The presence of micropollutants in the environment and their toxic impacts on the aquatic environment have raised concern about their inefficient removal in wastewater treatment plants. In this study, the fate of micropollutants of four different classes was simulated in a conventional activated sludge plant using a bioreactor micropollutant fate model coupled to a settler model. The latter was based on the Bürger-Diehl model extended for the first time to include micropollutant fate processes. Calibration of model parameters was completed by matching modelling results with full-scale measurements (i.e. including aqueous and particulate phase concentrations of micropollutants) obtained from a 4-day sampling campaign. Modelling results showed that further biodegradation takes place in the sludge blanket of the settler for the highly biodegradable caffeine, underlining the need for a reactive settler model. The adopted Monte Carlo based calibration approach also provided an overview of the model's global sensitivity to the parameters. This analysis showed that for each micropollutant and according to the dominant fate process, a different set of one or more parameters had a significant impact on the model fit, justifying the selection of parameter subsets for model calibration. A dynamic local sensitivity analysis was also performed with the calibrated parameters. This analysis supported the conclusions from the global sensitivity and provided guidance for future sampling campaigns. This study expands the understanding of micropollutant fate models when applied to different micropollutants, in terms of global and local sensitivity to model parameters, as well as the identifiability of the parameters., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In this study, a 50-membered library of substituted 4-hydroxyquinolin-2(1H)-ones and two closely related analogues was designed, scored in-silico for drug likeness and subsequently synthesized. Thirteen derivatives, all sharing a common 3-phenyl substituent showed minimal inhibitory concentrations against Mycobacterium tuberculosis H37Ra below 10 μM and against Mycobacterium bovis AN5A below 15 μM but were inactive against faster growing mycobacterial species. None of these selected derivatives showed significant acute toxicity against MRC-5 cells or early signs of genotoxicity in the Vitotox™ assay at the active concentration range. The structure activity study relation provided some insight in the further favourable substitution pattern at the 4-hydroxyquinolin-2(1H)-one scaffold and finally 6-fluoro-4-hydroxy-3-phenylquinolin-2(1H)-one (38) was selected as the most promising member of the library with a MIC of 3.2 μM and a CC 50 against MRC-5 of 67.4 μM., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Several B. cenocepacia mouse models are available to study the pulmonary infection by this Burkholderia cepacia complex (BCC) species. However, a characterized B. cenocepacia mouse model to evaluate the efficacy of potential new antibacterial therapies is not yet described. Therefore, we optimized and validated the course of infection (i.e. bacterial proliferation in lung, liver and spleen) and the efficacy of a reference antibiotic, tobramycin (TOB), in a mouse lung infection model. Furthermore, the local immune response and histological changes in lung tissue were studied during infection and treatment. A reproducible lung infection was observed when immunosuppressed BALB/c mice were infected with B. cenocepacia LMG 16656. Approximately 50 to 60% of mice infected with this BCC species demonstrated a dissemination to liver and spleen. TOB treatment resulted in a two log reduction in lung burden, prevented dissemination of B. cenocepacia to liver and spleen and significantly reduced levels of proinflammatory cytokines. As this mouse model is characterized by a reproducible course of infection and efficacy of TOB, it can be used as a tool for the in vivo evaluation of new antibacterial therapies., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The presence of micropollutants in the environment has triggered research on quantifying and predicting their fate in wastewater treatment plants (WWTPs). Since the removal of micropollutants is highly related to conventional pollutant removal and affected by hydraulics, aeration, biomass composition and solids concentration, the fate of these conventional pollutants and characteristics must be well predicted before tackling models to predict the fate of micropollutants. In light of this, the current paper presents the dynamic modelling of conventional pollutants undergoing activated sludge treatment using a limited set of additional daily composite data besides the routine data collected at a WWTP over one year. Results showed that as a basis for modelling, the removal of micropollutants, the Bürger-Diehl settler model was found to capture the actual effluent total suspended solids (TSS) concentrations more efficiently than the Takács model by explicitly modelling the overflow boundary. Results also demonstrated that particular attention must be given to characterizing incoming TSS to obtain a representative solids balance in the presence of a chemically enhanced primary treatment, which is key to predict the fate of micropollutants.

Advanced 1-D models for Secondary Settling Tanks (SSTs) explicitly account for several phenomena that influence the settling process (such as hindered settling and compression settling). For each of these phenomena a valid mathematical expression needs to be selected and its parameters calibrated to obtain a model that can be used for operation and control. This is, however, a challenging task as these phenomena may occur simultaneously. Therefore, the presented work evaluates several available expressions for hindered settling based on long-term batch settling data. Specific attention is paid to the behaviour of these hindered settling functions in the compression region in order to evaluate how the modelling of sludge compression is influenced by the choice of a certain hindered settling function. The analysis shows that the exponential hindered settling forms, which are most commonly used in traditional SST models, not only account for hindered settling but partly lump other phenomena (compression) as well. This makes them unsuitable for advanced 1-D models that explicitly include each phenomenon in a modular way. A power-law function is shown to be more appropriate to describe the hindered settling velocity in advanced 1-D SST models., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A new perspective on the modelling of settling behaviour in water resource recovery facilities is introduced. The ultimate goal is to describe in a unified way the processes taking place both in primary settling tanks (PSTs) and secondary settling tanks (SSTs) for a more detailed operation and control. First, experimental evidence is provided, pointing out distributed particle properties (such as size, shape, density, porosity, and flocculation state) as an important common source of distributed settling behaviour in different settling unit processes and throughout different settling regimes (discrete, hindered and compression settling). Subsequently, a unified model framework that considers several particle classes is proposed in order to describe distributions in settling behaviour as well as the effect of variations in particle properties on the settling process. The result is a set of partial differential equations (PDEs) that are valid from dilute concentrations, where they correspond to discrete settling, to concentrated suspensions, where they correspond to compression settling. Consequently, these PDEs model both PSTs and SSTs.

Population balance models (PBMs) represent a powerful modelling framework for the description of the dynamics of properties that are characterised by distributions. This distribution of properties under transient conditions has been demonstrated in many chemical engineering applications. Modelling efforts of several current and future unit processes in wastewater treatment plants could potentially benefit from this framework, especially when distributed dynamics have a significant impact on the overall unit process performance. In these cases, current models that rely on average properties cannot sufficiently capture the true behaviour and even lead to completely wrong conclusions. Examples of distributed properties are bubble size, floc size, crystal size or granule size. In these cases, PBMs can be used to develop new knowledge that can be embedded in our current models to improve their predictive capability. Hence, PBMs should be regarded as a complementary modelling framework to biokinetic models. This paper provides an overview of current applications, future potential and limitations of PBMs in the field of wastewater treatment modelling, thereby looking over the fence to other scientific disciplines.

Patients suffering from advanced melanoma have a very poor prognosis. Despite recent advances in the understanding of oncogenic mechanisms and therapeutic interventions, the median survival of patients with metastatic disease is less than 12 months. Immunotherapy of melanoma has been intensely investigated and holds great promises. Tyrosinase-related protein-1 or gp75 (TYRP-1/gp75) antigen is a melanosomal polypeptide. It is the most abundant glycoprotein synthesized by pigmented melanocytes and melanomas. It is specific for melanocytes and both primary and metastatic melanomas. In mice, administration of the mouse mAb anti-gp75 TA99 prevents outgrowth of B16F10 melanoma metastases. The activity of TA99 is dependent on the presence and activity of the IgG specific, Fc receptors. TA99 cross-reacts with human gp75, and is currently being used for diagnosis of patients. Here, we sequenced mIgG2a TA99 and found that the locus harboring the endogenous light chain of the fusion partner in the TA99 hybridoma cells is not inactivated, resulting in the production of a mixed pool of mAbs that mitigates binding to gp75. Since human IgG1 (hIgG1) is the most frequently used mAb format in clinical studies, we produced a recombinant hIgG1 TA99 molecule. Whereas it is known that hIgG1 can functionally interact with mouse Fc receptors, we found that hIgG1 TA99 did not exhibit in vivo activity against B16F10 melanoma in wild type C57BL/6 mice. However, results obtained in this study demonstrated anti-tumor activity of hIgG1 TA99 in FcγRIIB knockout mice and in human FcγRI transgenic mice. These results emphasize the need for testing hIgG mAb in mice with functional human FcγRs., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The consistent modelling methodology for secondary settling tanks (SSTs) leads to a partial differential equation (PDE) of nonlinear convection-diffusion type as a one-dimensional model for the solids concentration as a function of depth and time. This PDE includes a flux that depends discontinuously on spatial position modelling hindered settling and bulk flows, a singular source term describing the feed mechanism, a degenerating term accounting for sediment compressibility, and a dispersion term for turbulence. In addition, the solution itself is discontinuous. A consistent, reliable and robust numerical method that properly handles these difficulties is presented. Many constitutive relations for hindered settling, compression and dispersion can be used within the model, allowing the user to switch on and off effects of interest depending on the modelling goal as well as investigate the suitability of certain constitutive expressions. Simulations show the effect of the dispersion term on effluent suspended solids and total sludge mass in the SST. The focus is on correct implementation whereas calibration and validation are not pursued.