267 research outputs found
Efficiency Wages and the Economic Effects of the Minimum Wage: Evidence from a Low-Wage Labour Market
No full textWe exploit a natural experiment provided by the 1990 introduction of the UK National Minimum Wage (NMW) to investigate the relationship between wages and monitoring and to test for Efficiency Wages considerations in a low-wage sector, the UK residential care homes industry. Our findings seem to support the wage-supervision trade-off prediction of the shirking model, and that employers didn't dissipate minimum wage rents by increasing work intensity or effort requirements on the job. Estimation results suggest that higher wage costs were more than offset by lower monitoring costs, and thus the overall evidence imply that the NMW may have operated as an Efficiency Wage. These findings support Efficiency Wage models used to explain a non-negative employment effect of the Minimum Wage and provide an explanation of recent evidence from the care homes sector that although the wage structure was heavily affected by the NMW introduction, there were moderate employment effects.Efficiency Wages, National Minimum Wage, Wage-supervision trade-off
Synthesis and optimization of NGL separation as a complex energy-integrated distillation sequence
No full textThe synthesis of heat-integrated distillation sequences for energy-efficient separation of zeotropic multicomponent mixtures is complex due to the many interconnected design degrees of freedom. This paper explores the basis on which reliable screening can be carried out. To solve this problem, a screening algorithm has been developed using optimization of a superstructure for the sequence synthesis using shortcut models, in conjunction with a transportation algorithm for the synthesis of the heat integration arrangement. Different approaches for the inclusion of heat integration are explored and compared. Then the best few designs from this screening are evaluated using rigorous simulations. A case study for the separation of NGL is used to compare options. It has been found that separation problems of the type explored can be screened reliably using shortcut distillation models in conjunction with the synthesis of heat exchanger network designs. Unintegrated designs using thermally coupled complex columns show much better performance than the corresponding designs using simple columns. However, once heat integration is included the difference between designs using complex columns and simple columns narrows significantly.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Product and Process Engineerin
Paving the way for the integration of synthesis, assessment, and design tools within an ontological framework
No full textThe constant development of new alternatives to treat waste aids in closing material loops towards the circular economy and improving sustainability through the use of new renewable materials and energy. This fact leads to the increasing need for decision-making tools for process synthesis and assessment, which can be addressed with an integrated framework that employs ontologies for knowledge management and optimization tools to perform a hierarchical assessment of alternatives. The systematization of these procedures raises the need for tools to automate techno-economic and life cycle analyses. In this work, such a challenge is addressed through the additional integration of add-on modules such as the CapEx-Opex estimation tools and surrogate modeling within this framework. A case study on plastic waste is proposed with the inclusion of several pyrolysis and gasification alternatives. Results show pyrolysis, followed by the subsequent purification of its products, as the best alternative and helped identify main drivers for technologies feasibility such as feedstock purity and energy consumption.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Product and Process Engineerin
Enhanced hot-liquid water pretreatment of biomass with recovery and valorization of side products
No full textLignocellulosic biomass potentially represents a great feedstock for biofuel production, but its’ pretreatment needs to be enhanced in order to make biorefineries competitive with fossil fuel based alternatives. One way to make biorefineries more economically viable is to recover and valorize all generated by-products during the biomass pretreatment step. The main goal of this original research is to design an optimal process for recovering valuable by-products after hot-liquid water pretreatment of poplar biomass. Rigorous models for all operations included in the recovery process are developed using Aspen Plus as a CAPE tool. An optimal downstream processing sequence, consisting of multiple distillation steps, is designed to recover several valuable components, such as acetic acid, formic acid, furfural and 5-hydroxymethylfurfural (HMF).Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.BT/Bioprocess EngineeringChemE/Product and Process Engineerin
Data augmentation for machine learning of chemical process flowsheets
No full textArtificial intelligence has great potential for accelerating the design and engineering of chemical processes. Recently, we have shown that transformer-based language models can learn to auto-complete chemical process flowsheets using the SFILES 2.0 string notation. Also, we showed that language translation models can be used to translate Process Flow Diagrams (PFDs) into Process and Instrumentation Diagrams (P&IDs). However, artificial intelligence methods require big data and flowsheet data is currently limited. To mitigate this challenge of limited data, we propose a new data augmentation methodology for flowsheet data that is represented in the SFILES 2.0 notation. We show that the proposed data augmentation improves the performance of artificial intelligence-based process design models. In our case study flowsheet data augmentation improved the prediction uncertainty of the flowsheet autocompletion model by 14.7%. In the future, our flowsheet data augmentation can be used for other machine learning algorithms on chemical process flowsheets that are based on SFILES notation.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Product and Process Engineerin
Transfer learning for process design with reinforcement learning
No full textProcess design is a creative task that is currently performed manually by engineers. Artificial intelligence provides new potential to facilitate process design. Specifically, reinforcement learning (RL) has shown some success in automating process design by integrating data-driven models that learn to build process flowsheets with process simulation in an iterative design process. However, one major challenge in the learning process is that the RL agent demands numerous process simulations in rigorous process simulators, thereby requiring long simulation times and expensive computational power. Therefore, typically short-cut simulation methods are employed to accelerate the learning process. Short-cut methods can, however, lead to inaccurate results. We thus propose to utilize transfer learning for process design with RL in combination with rigorous simulation methods. Transfer learning is an established approach from machine learning that stores knowledge gained while solving one problem and reuses this information on a different target domain. We integrate transfer learning in our RL framework for process design and apply it to an illustrative case study comprising equilibrium reactions, azeotropic separation, and recycles, our method can design economically feasible flowsheets with stable interaction with DWSIM. Our results show that transfer learning enables RL to economically design feasible flowsheets with DWSIM, resulting in a flowsheet with an 8% higher revenue. And the learning time can be reduced by a factor of 2.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.ChemE/Product and Process EngineeringChemE/Delft Ingenious Desig
Is there a Wage-Supervision Trade-Off? Efficiency Wages Evidence From the 1990 British Workplace Industrial Relations Survey
No full textEfficiency Wages cannot be ruled out on a priori theoretical grounds and evidence is needed. Direct evidence on the effects of wages on productivity and indirect evidence from the wage structure does not seem persuasive. In this paper we offer an indirect test of the efficiency wage theory, by testing the prediction of the ‘shirking’ and ‘gift-exchange’ models of efficiency wages of a wage-supervision trade-off, using data from the 1990 British Workplace Industrial Relations Survey. We highlight the main empirical problems that hinder the estimation of the wage-supervision relationship, and we offer a novel theoretical explanation of the wagesupervision trade-off in terms of union bargaining power. We find evidence that wages and supervision are substitutes in eliciting effort for unskilled manual workers. This evidence supports principal-agent models, many of which do not have the efficiency wage property. Finally, after we test whether wages are set optimally above the market clearing level we fail to find any evidence that can rule out efficiency wages in favour of incentive contracts.Efficiency Wages, Wage-supervision trade-off, Endogeneity bias, private and Non-Unionised establishments
Private Sector Employment Growth, 1998-2004: A Panel Analysis of British Workplaces
No full textUsing nationally representative panel data for British private sector workplaces this paper points to the importance of distinguishing between workplace and firm size when analysing employment growth, and finds that the factors associated with growth differ markedly between single independent establishments and those belonging to multi-site firms. Results also differ according to whether one adjusts for sample selection arising from workplace survival, and according to whether one distinguishes between growth per se and internal, organic employment growth. We find evidence at the plant level that is consistent with creative job destruction.employment growth, workplace survival, workplace age, workplace size, humancapital, sunk costs
Bioengineering Against Fibrils and Hypoglycemia: Studies on Insulin, Glucagon and the Fusion of Both
No full textIUIInsulin drugs are vital for blood glucose control in type 1 and late-stage type 2 diabetes mellitus. Unfortunately, however, they have two notable problems: (1) an intrinsic propensity to physical degradation (amyloid-like fibrillation), which reduces potency and can lead to occlusion of insulin pumps’ catheters, impairing timely drug administration; and (2) an ever-present risk for iatrogenic hypoglycemia with potential acute (or even fatal) consequences and chronic sequelae. The risk of hypoglycemia, its immediate and long-term complications, and associated anxiety can confound efforts to achieve effective glycemic control. Further, insulin’s physical instability impacts worldwide distribution by imposing a refrigeration requirement—often a barrier to global access. A combined solution to these two problems could benefit patients worldwide. To circumvent these limitations, glucose-responsive technologies have been sought to reduce hypoglycemic risk; diverse strategies have focused on novel devices, delivery modes, or protein engineering. In the present doctoral work, we describe an alternative glucose-responsive approach that exploits an endogenous glucose-dependent switch in hepatic physiology: preferential insulin signaling (under hyperglycemic conditions) versus preferential counter-regulatory glucagon signaling (under hypoglycemic conditions).
Glucagon, traditionally regarded as a counter-regulatory hormone, has been underutilized in routine glucose control due to a marked propensity to fibrillation. Motivated by the pilot success of a counterintuitive strategy—co-infusion of insulin and glucagon—we have bioengineered and tested a fibrillation-resistant insulin-glucagon fusion protein with favorable relative hormonal activities. The N-terminal glucagon moiety was stabilized as a partial α-helix by Lys13-Glu17 lactam bridge and fused to a C-terminal insulin moiety stabilized as a single chain with a foreshortened C domain. Our in vitro studies demonstrated (a) marked resistance to fibrillation on prolonged agitation at 37 °C and (b) unaffected dual hormonal signaling activity. Glucodynamic responses were monitored in rats relative to control fusion proteins lacking one or the other hormonal activity. Results showed that insulin’s efficacy in hyperglycemia was unaffected, but enhanced endogenous glucose production was observed under hypoglycemic conditions. Together, these findings provide proof of principle for the translational application of a novel glucose-responsive insulin formulation with augmented physical stability, addressing two major problems of insulin replacement therapy in a single molecule
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