The impact of global change on the hydropower potential of Europe: a model-based analysis

Biotrickling filters are one of the most widely used biological technologies to perform biogas desulfurization. Their industrial application has been hampered due to the difficulty to achieve a robust and reliable operation of this bioreactor. Specifically, biotrickling filters process performance is affected mostly by fluctuations in the hydrogen sulfide (H2S) loading rate due to changes in the gas inlet concentration or in the volumetric gas flowrate. The process can be controlled by means of the regulation of the air flowrate (AFR) to control the oxygen (O2) gas outlet concentration ([O2]out) and the trickling liquid velocity (TLV) to control the H2S gas outlet concentration ([H2S]out). In this work, efforts were placed towards the understanding and development of control strategies in biological H2S removal in a biotrickling filter under aerobic conditions. Classical proportional and proportional-integral feedback controllers were applied in a model of an aerobic biotrickling filter for biogas desulfurization. Two different control loops were studied: (i) AFR Closed-Loop based on AFR regulation to control the [O2]out, and (ii) TLV Closed-Loop based on TLV regulation to control the [H2S]out. AFR regulation span was limited to values so that corresponds to biogas dilution factors that would give a biogas mixture with a minimum methane content in air, far from those values required to obtain an explosive mixture. A minimum TLV of 5.9 m h−1 was applied to provide the nutrients and moisture to the packed bed and a maximum TLV of 28.3 m h−1 was set to prevent biotrickling filter (BTF) flooding. Control loops were evaluated with a stepwise increase from 2000 ppmv until 6000 ppmv and with changes in the biogas flowrate using stepwise increments from 61.5 L h−1 (EBRT = 118 s) to 184.5 L h−1 (EBRT = 48.4 s). Controller parameters were determined based on time-integral criteria and simple criteria such as stability and oscillatory controller response. Before implementing the control strategies, two different mass transfer correlations were evaluated to study the effect of the manipulable variables. Open-loop behavior was also studied to determine the impact of control strategies on process performance variables such as removal efficiency, sulfate and sulfur selectivity, and oxygen consumption. AFR regulation efficiently controlled [O2]out; however, the impact on process performance parameters was not as great as when TLV was regulated to control [H2S]out. This model-based analysis provided valuable information about the controllability limits of each strategy and the impact that each strategy can have on the process performance.

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Estimation of the economic burden of COVID-19 using disability-adjusted life years (DALYs) and productivity losses in Kerala, India: a model-based analysis

BMJ Open ◽

10.1136/bmjopen-2021-049619 ◽

2021 ◽

Vol 11 (8) ◽

pp. e049619

Author(s):

Denny John ◽

M S Narassima ◽

Jaideep Menon ◽

Jammy Guru Rajesh ◽

Amitava Banerjee

Keyword(s):

Economic Burden ◽

Premature Mortality ◽

Secondary Outcome ◽

Years Of Life Lost ◽

Disability Adjusted Life Years ◽

Model Based ◽

Disability Adjusted Life ◽

Life Years ◽

The Impact ◽

Model Based Analysis

ObjectivesFrom the beginning of the COVID-19 pandemic, clinical practice and research globally have centred on the prevention of transmission and treatment of the disease. The pandemic has had a huge impact on the economy and stressed healthcare systems worldwide. The present study estimates disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL) and cost of productivity lost (CPL) due to premature mortality and absenteeism secondary to COVID-19 in the state of Kerala, India.SettingDetails on sociodemographics, incidence, death, quarantine, recovery time, etc were derived from public sources and the Collective for Open Data Distribution-Keralam. The working proportion for 5-year age–gender cohorts and the corresponding life expectancy were obtained from the 2011 Census of India.Primary and secondary outcome measuresThe impact of the disease was computed through model-based analysis on various age–gender cohorts. Sensitivity analysis was conducted by adjusting six variables across 21 scenarios. We present two estimates, one until 15 November 2020 and later updated to 10 June 2021.ResultsSeverity of infection and mortality were higher among the older cohorts, with men being more susceptible than women in most subgroups. DALYs for males and females were 15 954.5 and 8638.4 until 15 November 2020, and 83 853.0 and 56 628.3 until 10 June 2021. The corresponding YPPLL were 1323.57 and 612.31 until 15 November 2020, and 6993.04 and 3811.57 until 10 June 2021, and the CPL (premature mortality) were 263 780 579.94 and 41 836 001.82 until 15 November 2020, and 1 419 557 903.76 and 278 275 495.29 until 10 June 2021.ConclusionsMost of the COVID-19 burden was contributed by years of life lost. Losses due to YPPLL were reduced as the impact of COVID-19 infection was lesser among the productive cohorts. The CPL values for individuals aged 40–49 years old were the highest. These estimates provide the data necessary for policymakers to work on reducing the economic burden of COVID-19 in Kerala.

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Simulating the impact of policy, energy prices and technological progress on the passenger car fleet in Austria—A model based analysis 2010–2050

Energy Policy ◽

10.1016/j.enpol.2011.06.008 ◽

2011 ◽

Vol 39 (9) ◽

pp. 5045-5062 ◽

Cited By ~ 48

Author(s):

Maximilian Kloess ◽

Andreas Müller

Keyword(s):

Technological Progress ◽

Energy Prices ◽

Passenger Car ◽

Model Based ◽

The Impact ◽

Model Based Analysis

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The impact of differential uptake of HPV vaccine by sexual risks on health inequalities: A model-based analysis

Vaccine ◽

10.1016/j.vaccine.2013.01.026 ◽

2013 ◽

Vol 31 (13) ◽

pp. 1740-1747 ◽

Cited By ~ 15

Author(s):

Talía Malagón ◽

Véronique Joumier ◽

Marie-Claude Boily ◽

Nicolas Van de Velde ◽

Mélanie Drolet ◽

...

Keyword(s):

Health Inequalities ◽

Hpv Vaccine ◽

Sexual Risks ◽

Model Based ◽

The Impact ◽

Model Based Analysis

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Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics

Journal of The Royal Society Interface ◽

10.1098/rsif.2016.0167 ◽

2016 ◽

Vol 13 (117) ◽

pp. 20160167 ◽

Cited By ~ 13

Author(s):

Maria Herberg ◽

Ingmar Glauche ◽

Thomas Zerjatke ◽

Maria Winzi ◽

Frank Buchholz ◽

...

Keyword(s):

Stem Cells ◽

Embryonic Stem Cells ◽

Embryonic Stem ◽

Mouse Embryonic Stem Cells ◽

State Transitions ◽

Self Renewal ◽

Model Based ◽

Heterogeneous Expression ◽

The Impact ◽

Model Based Analysis

Pluripotent mouse embryonic stem cells (mESCs) show heterogeneous expression levels of transcription factors (TFs) involved in pluripotency regulation, among them Nanog and Rex1. The expression of both TFs can change dynamically between states of high and low activity, correlating with the cells' capacity for self-renewal. Stochastic fluctuations as well as sustained oscillations in gene expression are possible mechanisms to explain this behaviour, but the lack of suitable data hampered their clear distinction. Here, we present a systems biology approach in which novel experimental data on TF heterogeneity is complemented by an agent-based model of mESC self-renewal. Because the model accounts for intracellular interactions, cell divisions and heredity structures, it allows for evaluating the consistency of the proposed mechanisms with data on population growth and on TF dynamics after cell sorting. Our model-based analysis revealed that a bistable, noise-driven network model fulfils the minimal requirements to consistently explain Nanog and Rex1 expression dynamics in heterogeneous and sorted mESC populations. Moreover, we studied the impact of TF-related proliferation capacities on the frequency of state transitions and demonstrate that cellular genealogies can provide insights into the heredity structures of mESCs.

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