Novel integrated mechanical biological chemical treatment (MBCT) systems for the production of levulinic acid from fraction of municipal solid waste: A comprehensive techno-economic analysis.

This paper, for the first time, reports integrated conceptual MBCT/biorefinery systems for unlocking the value of organics in municipal solid waste (MSW) through the production of levulinic acid (LA by 5wt%) that increases the economic margin by 110-150%. After mechanical separation recovering recyclables, metals (iron, aluminium, copper) and refuse derived fuel (RDF), lignocelluloses from remaining MSW are extracted by supercritical-water for chemical valorisation, comprising hydrolysis in 2wt% dilute H2SO4 catalyst producing LA, furfural, formic acid (FA), via C5/C6 sugar extraction, in plug flow (210−230°C, 25bar, 12s) and continuous stirred tank (195−215°C, 14bar, 20mins) reactors; char separation and LA extraction/purification by methyl isobutyl ketone solvent; acid/solvent and by-product recovery. The by-product and pulping effluents are anaerobically digested into biogas and fertiliser. Produced biogas(6.4MWh/t), RDF(5.4MWh/t), char(4.5MWh/t) are combusted, heat recovered into steam generation in boiler (efficiency:80%); on-site heat/steam demand is met; balance of steam is expanded into electricity in steam turbines (efficiency:35%)

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators

We consider the problem of Bayesian inference in the family of probabilistic models implicitly defined by stochastic generative models of data. In scientific fields ranging from population biology to cosmology, low-level mechanistic components are composed to create complex generative models. These models lead to intractable likelihoods and are typically non-differentiable, which poses challenges for traditional approaches to inference. We extend previous work in "inference compilation", which combines universal probabilistic programming and deep learning methods, to large-scale scientific simulators, and introduce a C++ based probabilistic programming library called CPProb. We successfully use CPProb to interface with SHERPA, a large code-base used in particle physics. Here we describe the technical innovations realized and planned for this library.Comment: 7 pages, 2 figure

Cardiovascular Disease in Pregnancy: Clinical Outcomes and Cost-Associated Burdens From a National Cohort at Delivery.

BACKGROUND: Cardiovascular disease (CVD) in pregnancy is a leading cause of maternal morbidity and mortality in the United States, with an increasing prevalence. OBJECTIVES: This study aimed to examine risk factors for adverse maternal cardiac, maternal obstetric, and neonatal outcomes as well as costs for pregnant people with CVD at delivery. METHODS: Using the National Inpatient Sample 2010-2019 and the Internal Classification of Diseases diagnosis codes, all pregnant people admitted for their delivery hospitalization were included. CVD diagnoses included congenital heart disease, cardiomyopathy, ischemic heart disease, arrhythmias, and valvular disease. Multivariable regressions were used to analyze major adverse cardiovascular events (MACE), maternal and fetal complications, length of stay, and resource utilization. RESULTS: Of the 33,639,831 birth hospitalizations included, 132,532 (0.39%) had CVD. These patients experienced more frequent MACE (8.5% vs 0.4%, P < 0.001), obstetric (24.1% vs 16.6%, P < 0.001), and neonatal complications (16.1% vs 9.5%, P < 0.001), and maternal mortality (0.16% vs 0.01%, P < 0.001). Factors associated with MACE included cardiomyopathy (adjusted OR [aOR]: 49.9, 95% CI: 45.2-55.1), congenital heart disease (aOR: 13.8, 95% CI: 12.0-15.9), Black race (aOR: 1.04, 95% CI: 1.00-1.08), low income (aOR: 1.06, 95% CI: 1.02-1.11), and governmental insurance (aOR: 1.03, 95% CI: 1.00-1.07). On adjusted analysis, CVD was associated with higher odds of maternal mortality (aOR: 9.28, 95% CI: 6.35-13.56), stillbirth (aOR: 1.66, 95% CI: 1.49-1.85), preterm birth (aOR: 1.33, 1.27-1.39), and congenital anomalies (aOR: 1.84, 95% CI: 1.69-1.99). CVD was also associated with an increase of $2,598 (95$2,419-2,777) per patient during admission for delivery. CONCLUSIONS: CVD in pregnancy is associated with higher rates of adverse outcomes. Our study highlights the association of key clinical and demographic factors with CVD during pregnancy to emphasize those at highest risk for complications

Using topology and neighbor information to overcome adverse vehicle density conditions

Vehicular networks supporting cooperative driving on the road have attracted much attention due to the plethora of new possibilities they offer to modern Intelligent Transportation Systems. However, research works regarding vehicular networks usually obviate assessing their proposals in scenarios including adverse vehicle densities, i.e., density values that significantly differ from the average values, despite such densities can be quite common in real urban environments (e.g. traffic jams). In this paper, we study the effect of these hostile conditions on the performance of different schemes providing warning message dissemination. The goal of these schemes is to maximize message delivery effectiveness, something difficult to achieve in adverse density scenarios. In addition, we propose the Neighbor Store and Forward (NSF) scheme, designed to be used under low density conditions, and the Nearest Junction Located (NJL) scheme, specially developed for high density conditions. Simulation results demonstrate that our proposals are able to outperform existing warning message dissemination schemes in urban environments under adverse vehicle density conditions. In particular, NSF reduces the warning notification time in low vehicle density scenarios, while increasing up to 23.3% the percentage of informed vehicles. As for high vehicle density conditions, NJL is able to inform the same percentage of vehicles than other existing approaches, while reducing the number of messages up to 46.73%This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, by the Fundacion Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragon and the European Social Fund (T91 Research Group).Sanguesa, JA.; Fogue, M.; Garrido, P.; Martinez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM. (2014). Using topology and neighbor information to overcome adverse vehicle density conditions. Transportation Research Part C: Emerging Technologies. 42:1-13. https://doi.org/10.1016/j.trc.2014.02.010S1134

SYNERGORS - A Systems Approach to Synergistic Utilisation of Secondary Organic Streams. Final Project Report.

The SYNERGORS Final Project Report is available at: https://eng.ox.ac.uk/synergors/publications/Executive Summary: The SYNERGORS project (“A systems approach to synergistic utilisation of secondary organic streams”) was funded by the UKRI Natural Environment Research Council (NERC), running from 2018 to 2021. The project aimed to develop new systems approaches for promoting resource recovery from secondary organic waste streams including food waste, residual biomass and municipal solid waste. The project received support from more than 10 UK and international organisations, including academia, industry and policymakers, to provide multidisciplinary expertise to address the global challenges in resources and waste management. The formation of the core team was greatly assisted by the British Council / Newton Fund Researcher Links workshops, with collaboration between the British, Malaysian, Mexican and Brazilian academics. The SYNERGORS project has led to substantial impacts beyond academia, resulting in 9 academic publications, new experimental studies with Anaero Technology, a number of engagement activities and international visits (including case studies in Malaysia, Brazil and Mexico), and the creation of the Society of Circular, Regenerative and Sustainable Systems (CRES) which aims to promote systems thinking and circular economy. SYNERGORS’s research spans three themes: Theme 1: Strategic analysis for sustainable organic resources and waste management to achieve circular economy and net zero Theme. 2: Development of novel resource recovery and valorisation technology concept Theme. 3: Development of innovative biorefinery system design. Key Recommendations from SYNERGORS 1. Waste and recycling industries should move away from a treatment-oriented waste management approach and adopt a more transformative and innovative resource recovery approach to achieve a more circular economy. 2. A systems approach to addressing waste management is needed to promote collaboration among different groups of stakeholders (e.g. government, local authorities, waste and recycling industries, commercial sector, public etc.) 3. Resources embedded in organic waste streams should be exploited for value-added products such 4 as chemicals and hydrogen. This requires significant revamp on existing waste treatment facilities. Further research is needed to improve system efficiency and achieve greater cost reduction.This work was supported by the UKRI Natural Environment Research Council (NE/R012938/1) through the UKRI/NERC Industrial Innovation Fellowship Programme

Two strands of servitization: a thematic analysis of traditional and customer co-created servitization and future research directions

The servitization literature has diverged, some adopting a goods-dominant logic and some a service-dominant logic. While both literature streams deal with servitization, their conceptual underpinnings and use of key terms are fundamentally different and have become confused within literature. This lack of clarity and understanding presents a challenge to both research and practice. The paper asks what the points of convergence and divergence are between the two streams of literature. The extant literature is reviewed to identify and understand where and how the streams converge and diverge. A two-tiered thematic analysis with both semantic and latent theme analysis is employed. Our findings highlight five points of departure, as well as highlighting examples where both logics have been applied. The five points of departure are the differing conceptualisations of: Value-in-Use, Design of the Servitized Offering, Value Co-production and Value Co-creation, Contextual Variety and Complexity, and Business Model of Solutions and Outcomes. We also propose conditions under which one logic may be more appropriate, in particular we find that adoption of a goods-dominant logic and service-dominant logic are better suited to the pursuit of efficiency and effectiveness, respectively. Finally, we identify future research directions, particularly within the domain of the Internet-of-Things