Technical Uncertainties Research Articles

Project Capital Rationing using Discounted Cash Flow Method, Sensitivity Analysis and Monte Carlo Simulation: Case Study Tambura Oil Development

This paper will analyze capital rationing on Tambura Insert PCP, which is currently in preparation. To prolong field production time, the company needs to find a most profitable method to produce oil in gas field which currently has no artificial list infrastructure installed. One of possible options is using Progressive Cavity Pump or PCP in the well to lift oil from down hole to surface. PCP is driven by a surface motor installed at the wellhead, above the x-mas tree. Electrical power is required to run the motor. With no electricity source available, three strategy options must be chosen to commence the project. First is the “cable laying” option which has high capital upfront with very low operating costs. Second is “in situ genset installation” option which has lower capital with higher operating costs. And third is “rental basis” option which has very low upfront capital but much higher operating cost. A business situation analysis situation is first conducted to determine why this project is needed. It consisted of internal analysis using a resource-based view framework, external analysis using PESTEL and Porter Five Forces, and PSC context. The method used to evaluate the project is quantitative by calculating project economic and financial parameters using discounted cashflow analysis to compare which options are most profitable. The second consideration is sensitivity analysis to determine what parameter most affects each option. And the third consideration is risks analysis using Monte Carlo simulation to define which option has the most robust parameters. Discounted cash flow analysis shows Net Present Value of Tambura insert PCP Project valuation is positive at range 1.32-1.44 Million USD, which indicates as base case all options are feasible economically. Scenario analysis shows the lowest project net present value or NPV is negative as low as 1.09 MUSD, and the maximum NPV is 2.62 million USD. The sensitivity analysis of several parameters shows that this project is very sensitive to changes in oil price and oil production volume. And finally, Monte Carlo simulation shows that probability of failure or having negative NPV is ranging from 10% to 30%, which means the project has different risks based on options. In conclusion, comparing parameters from all the analysis, it is recommended to commence the project with Option-3, the rental basis option. Although not the highest, Option-3 provided the second best NPV with a very small difference with the first. It gives the best result for other economic and financial parameters. And in terms of risk, it has the lowest risks among other options. Despite the risk that already low, there still some mitigations that need to be implemented to further reduce potential risk, such as conducting a more thorough valuation analysis, reduce technical uncertainty from reserves and reservoir properties, and accuracy of oil production rate. The company also needs to conduct more research is required to forecast the future price fluctuations, considering the oil price is one of the highest risk parameters and the most sensitive aspect in this project.

Whose energy sovereignty? Competing imaginaries of Mexico's energy future

Mexico started down a path toward renewable energy in 2013 when the central government set ambitious targets for clean energy and carbon emissions through long-term electricity auctions and clean energy licenses. In 2018, these efforts came to a drastic halt when President López Obrador was elected. Since then, efforts to transition to renewable have been stalled, and even reversed to some extent. At this moment of fundamental political, societal, and technical uncertainty, different futures are being debated. On the basis of 24 narrative interviews conducted with experts in the Mexican energy sector and extensive document analysis, we discuss how energy futures are imagined in different assemblages of institutions, technologies, and political power. Notions of energy sovereignty take central stage in discourses employed by actors seeking to materialize their imaginaries. Using the sociotechnical imaginaries framework, we identify and discuss both the dominant imaginaries and three counter-imaginaries, as well as their expression within notions of energy sovereignty. We conclude that this politicization may present an opportunity to include broader notions of energy sovereignty in imaginaries of energy futures.

The jurisdiction of the subjective expected utility (SEU) approach to risk-taking in science – A response to Franzoni and Stephan (2023), ‘uncertainty and risk-taking in science’

This paper discusses the SEU approach with regard to its “jurisdiction”; i.e. where it should and where it should not be applied. It is argued that the SEU approach must address the fundamental tension between exploration and exploitation; that it should be applied only to disciplines or fields that have low degrees of both technical and strategic uncertainties; and that funders need to prevent the SEU approach from spilling over to evaluations of exploratory projects, for which it is clearly not suited. In addition, the paper argues that the SEU approach needs to respond to the “fund people, not projects” argument. Finally, it calls for many more empirical and preferably experimental studies with the aim of shedding light on how the SEU approach works in practice. In this regard, novel techniques should be used more frequently than today, such as specification curve analysis that encompasses all reasonable explanatory specifications that are both theoretically consistent and statistically valid and non-redundant.

Sensitivity Analysis Using One-Factor-at-a-Time and Response Surface Method in Liquid-Dominated Geothermal Reservoir

In addition to extensive information that has been obtained from pre-feasibility, exploration, and drilling phase, we can improve our knowledge of reservoir behavior related to thermal extraction using sensitivity analysis. Such analysis is commonly applied to address technical uncertainty and risks in economic evaluation. The purpose of this study is to determine the parameters that have the most influence on thermal power generation using two different approaches named one-factor-at-a-time or OFAT and response surface method or RSM. Moreover, RSM analysis allowed us to make a predictive model for thermal power extracted in liquid-dominated geothermal reservoir. Literature study is conducted to understand various properties commonly encountered in a liquid-dominated geothermal reservoir including porosity, conductivity, reservoir temperature, and permeability. This information is then used to construct reservoir model in CMG STARS simulator with a single producer and injector. Two different sampling method, named OFAT and Box-Behnken are used to construct dataset, each contains different combination of levels of reservoir porosity, conductivity, temperature, permeability, and re-injection temperature. A total of 31 models using OFAT method with 7-level for each parameter are simulated to understand individual effect of each parameter. Meanwhile, 47 models are constructed using RSM method with 3-level for each parameter to evaluate the effect of interaction between parameters on thermal generation potential as well as constructing predictive model. Sensitivity analysis using both OFAT and RSM agree that the reservoir temperature is the most significant characteristic of geothermal reservoir to affect its thermal power potential. Meanwhile, re-injection temperature that initially expected to strongly effect the lifetime and sustainability of a liquid-dominated geothermal utilization is insignificant. This finding suggest that optimization re-injection temperature is solely for the purpose of maintaining sustainability of geothermal reservoir or cater the concern of environmental issue on wastewater management, and not for maximizing the thermal extraction.

Knowledge management and project uncertainty in ppen innovation context

Goal: We aims to map the literature that correlates uncertainty management and Open Innovation at project level, identifying the main contributions of knowledge management. Design/Methodology/Approach: We applied the Systematic Literature Review - SLR approach associated with Bibliometric analysis. To sample compose we use the Scopus and Web of Science databases. We also use the Bibliometrix R package to managed the sample process compose and bibliometric analysis and content analysis to identify the main topics. Results: The contributions mainly discuss the performance of OI projects to generate competitive advantage for organizations. The sample are categorized in technical, market, organizational and resource uncertainties. There is a greater focus on market and organizational uncertainties justified by the propagation of uncertainty. Limitations of the investigation: Even with transparency in the analysis and sample composition, the discussions may be subject to subjective interpretations by the authors. Practical Implications: This study has managerial implications. Our study helps managers identify core KM mechanisms in OI projects that enable sharing, integration, and knowledge flow between the network partners. Our findings show that the main challenge lies in organizational culture and the change of mindset, which influences the opening to new partnerships, knowledge sharing, and internal and external partners' trust to leverage innovation. For that, managers have to be aware of the KM barriers such as lack of trust or information asymmetry. Originality/ Value: We correlate uncertainties management in the OI projects, considering the influence of KM. We present conceptual maps. We identified emerging topics and we suggest a theoretical model of the research.

Alternative futures for crewed space cooperation after the international space station

The International Space Station (ISS) has been the largest and most visible international space cooperation project for decades. The program began in the 1980s during the Cold War, incorporated Russia after the end of the Cold War, and has sustained permanent human occupancy in low Earth orbit for over 20 years. Although political support among the partners appears solid, it is uncertain how many more years the Station will be able to operate technically. The operating costs of the Station for the United States and international partners are considerable and have been increasing as the facility ages. These costs impose a constraint on the willingness and ability of international partners to participate in new human exploration efforts, such as Artemis, the European Space Agency (ESA) Lunar Village concept, and the International Lunar Research Station (ILRS) plans of China and Russia. Given the central importance of the ISS to international human spaceflight cooperation today, what are the possible alternative futures for crewed space missions in a post-ISS world? States and private sector actors could work to extend the ISS, participate in the Chinese Space Station, create multiple, smaller government and private human-tended platforms, focus on human missions to the Moon and Mars, or even cease participation in human space exploration altogether. This paper examines these alternatives futures, assesses the attractiveness and practicality of the alternatives to spacefaring states, and seeks to identify the key areas of technical, economic, and policy uncertainty that will shape the post-ISS era of human space exploration.

Sensitivity Analysis of Capital Cost of European DEMO Design

Conceptual designs for a European demonstration (EU-DEMO) power plant are based on extrapolations of physics scaling laws and current understanding of engineering limits based on available technologies. It is imperative to quantify the impact of uncertainties in physics and engineering parameters on the ability to produce an economically attractive future fusion power plant that meets key design outcomes. In this work, the sensitivity of the expected capital cost of an EU-DEMO power plant has been studied using the systems code PROCESS. A systems code aims to model interactions between subsystems of a fusion power plant and provide consistent solution across a large parameter space. The PROCESS system code allows for user-defined initial conditions and constraints and then optimizes using a given figure of merit to find optimal design parameters. We present a sensitivity analysis on optimizations around the 2018 pulsed EU-DEMO baseline, and this allows for the identification of the most consequential model parameters and the magnitude of the nonlinear interactions between them. We consider the pulsed EU-DEMO baseline, and while fixing the major radius and optimizing for fusion gain <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> , we present a sensitivity analysis of the role of the physics and engineering parameters and constraints in determining the capital cost of such a device. We identify the dominant physics parameter as the power threshold necessary to enter H-mode, which accounts for 45% of the sensitivity and find high interactions between plasma shaping parameters and other power plant subsystems. This analysis allows for the identification of areas of additional technical focus and uncertainty propagation.

Bioplastics innovation: commercialization strategies for polyethylene furanoate (PEF) and polyhydroxy alkanoates (PHA)

AbstractPlastics have become ubiquitous materials essential for modern life and sustaining the global economy. On the other hand, their dependence on dwindling fossil fuel sources and their durability has raised concerns about their sustainability. Biobased plastics, which include biodegradable plastics, appear to be an appealing solution, yet their uptake has been slow. This paper specifically looks at the commercialization challenges for two bioplastics: polyethylene furanoate (PEF) and polyhydroxy alkanoate (PHA), that have been claimed by the industry as potentially disruptive. The superior barrier, mechanical and thermal properties of PEF present a suitable competition to polyethylene terephthalate (PET). The versatility and marine biodegradability of PHAs have attracted interest from several potential adopters. However, the high production costs of both pose a serious commercialization challenge when considering the established production, supply chain and recycling infrastructure for fossil‐based plastics. This study illustrates how firms are mitigating technical and market uncertainties by strategies such as adding value to other products, utilizing existing industrial assets, balancing exploration of more efficient and sustainable production pathways with commercial exploitation, lowering transaction costs by utilizing existing knowledge base, by developing formulation capabilities and forward integrating into end consumer products, or by entering collaborative alliances. These strategies could inevitably overcome inertia posed by the current market structure for fossil‐based plastics. © 2022 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley &amp; Sons Ltd.

Examining the effect of interoperability factors on building information modelling (BIM) adoption in Malaysia

PurposeBuilding information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.Design/methodology/approachThe theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.FindingsThe study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.Practical implicationsFinally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.Originality/valueTo the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

Multicentre Evaluation of the EUCAST Rapid Antimicrobial Susceptibility Testing (RAST) Extending Analysis to 16-20 Hours Reading Time.

The aim of the study was to evaluate the EUCAST RAST method by extending analysis to 16–20 h reading time and performance with new β-lactam/β-lactamase inhibitor combinations. A total of 676 positive blood cultures (BCs) were enrolled. Results at 4 h, 6 h, 8 h and 16–20 h were interpreted according to bacterial species using EUCAST RAST breakpoints (version 5.1). For species for which no breakpoints were available, tentative breakpoints were used. Categorical agreement with the Microscan microdilution system was analysed. Among the 676 BCs enrolled, 641 were monomicrobial and were included in the analysis. Categorical agreement ranged from 98.9% at 4 h to 99.4% at 16–20 h. The rates of very major errors were 3.3%, 3.7% and 3.4% at 4 h, 6 h and 8 h, respectively, and decreased to 1% at 16–20 h (p < 0.001). The number of major errors was low for each reading time (0.2% and 0.4% at 4 h and 6 h, respectively, and 0.3% at both 8 h and 16–20 h). The proportions of results in the area of technical uncertainty were 9.9%, 5.9%, 5% and 5.2% for readings at 4 h, 6 h, 8 h and 16–20 h, respectively. Tentative breakpoints proposed for Enterobacterales other than E.coli/K.pneumoniae and coagulase-negative staphylococci showed overall performances comparable to those observed for E. coli/K. pneumoniae and S. aureus. In conclusion, EUCAST RAST has been shown to be reliable to determine microbial susceptibility to main antimicrobials, including ceftazidime/avibactam and ceftolozane/tazobactam. A poorer performance was observed for certain species/antimicrobial agent combinations. The better performance observed at 16–20 h compared to the early readings may confer to the method greater potential for antimicrobial de-escalation interventions.

Immersive educational curriculum on intracoronary optical coherence tomography image analysis among naïve readers

BackgroundOptical coherence tomography (OCT) is an intravascular imaging modality for analysing coronary vessels. Image interpretation remains an obstacle for novice readers due to technical artefacts and uncertainty in tissue characterization. Despite an expanding clinical and research role for OCT, few training efforts exist, and there is an absence of a national standardized educational curriculum. We sought to determine whether an interactive, feedback-based OCT curriculum improved image interpretation among naive readers.MethodsNaive OCT readers completed both a Standard curriculum, comprised of self-directed didactics and consensus statements, and an Augmented curriculum, which provided real-time digital feedback of feature identification and measurements. Modules were separated by a minimum one-week washout period. After each module, and blinded to the exam answers, subjects completed an identical expert-designed 413-item exam to assess technical knowledge and ability to identify and measure vessel features. Performances were compared using Exact Wilcoxon signed-rank tests.ResultsAmong the 7 included subjects were 3 medical students, 3 internal medicine residents, and 1 cardiovascular medicine fellow with no prior OCT experience. The technical knowledge score (maximum 13) was significantly higher with the Augmented compared with the Standard curriculum (median 11 vs. 7, p = 0.03). After undergoing the Augmented curriculum, all 7 subjects were able to identify features of plaque rupture (Standard curriculum: 5/7 subjects, p = 0.5) and macrophages (Standard curriculum: 6/7 subjects, p = 0.99), differentiate the components between red and white thrombus (Standard curriculum: 6/7 subjects, p = 0.99), and characterize lipid plaque by attenuation, signal, homogeneity, and borders (Standard curriculum: 5/7 subjects, p = 0.5). Performances on the remaining exam portions did not differ between curricula.ConclusionsThe need for standardized, effective training in OCT image interpretation is increasingly essential as the intravascular imaging modality becomes widely utilized among interventional cardiologists and trainees. A novel interactive OCT curriculum enhanced naive readers’ technical knowledge and may supplement traditional self-learning in refining analytic skills.

Impact of EUCAST rapid antimicrobial susceptibility testing (RAST) on management of Gram-negative bloodstream infection

ObjectivesDuring bloodstream infections, reducing the time to antimicrobial susceptibility testing is crucial to initiation of early appropriate antibiotic therapy. For Gram-negative infections, a phenotypic approach remains necessary. Rapid antimicrobial testing (RAST) is a recently developed phenotypic EUCAST method. The goal of this study was to evaluate the accuracy and clinical impact of RAST. Patients and methodsFrom September 2020 to August 2021, Gram-negative episodes with positive blood culture detected in the morning were included in the RAST group. Categorical agreement of RAST with conventional antimicrobial testing on strains was determined. To assess antibiotic management and patient outcomes, the RAST group was compared with a control group (CG) with positive blood culture detected in the afternoon for which overnight antimicrobial testing was performed. ResultsThe RAST group included 61 episodes from 61 patients, while the CG group included 49 episodes from 48 patients. While RAST performed on 41 E. coli, 11 K. pneumoniae and 9 P. aeruginosa strains highlighted 99.3 % of categorical agreement, 7.4 % of unreadable zones and 9.4 % of technical uncertainty area at 4 h incubation were also reported.For the RAST group, effective antibiotic therapy was prescribed in 100 % of patients on the day of positive blood culture (day 1) vs 88 % in CG (p = 0,007). As for beta-lactams on day 1, RAST led to 9 escalations and 6 de-escalations. Mortality and length of hospital stay did not significantly differ between the two groups. ConclusionRAST improves management of antibiotic therapy in patients with Gram-negative sepsis.

Empirical analysis of the depreciation of electric vehicles compared to gasoline vehicles

The depreciation pattern of passenger vehicles is an important input parameter for economic considerations of buyers and other stakeholders such as financial insti-tutions. Due to their technical specifications and uncertainties in their degradation and life expectancy, it seems plausible that electric vehicles depreciate differently to conventional vehicles. This paper contributes to existing research in the economics of electric vehicles by analyzing the depreciation of electric vehicles along several countries and segments and compares it to gasoline vehicles by empirical analysis of public available data of 24,000 used vehicle sales. The results show that vehicles have a degressive depreciation relationship over the age of the vehicle, but that elec-tric vehicles have a substantially higher depreciation of 1.16% per month (13.9% per annum) compared to gasoline vehicles with 0.87% per month (10.4% per annum). Consequently, research into the economics of vehicles and budgeting considerations should apply a different depreciation rate for electric vehicles than for conventional vehicles. The resulting difference in depreciation to gasoline vehicles imply adapta-tion in economic models of insurance and leasing companies and gives governments the opportunity to adapt subsidies for electric vehicles to become more efficient.

Differential Perspectives: Epistemic Disconnects Surrounding the U.S. Census Bureau’s Use of Differential Privacy

When the U.S. Census Bureau announced its intention to modernize its disclosure avoidance procedures for the 2020 Census, it sparked a controversy that is still underway. The move to differential privacy introduced technical and procedural uncertainties, leaving stakeholders unable to evaluate the quality of the data. More importantly, this transformation exposed the statistical illusions and limitations of census data, weakening stakeholders’ trust in the data and in the Census Bureau itself. This essay examines the epistemic currents of this controversy. Drawing on theories from Science and Technology Studies (STS) and ethnographic fieldwork, we analyze the current controversy over differential privacy as a battle over uncertainty, trust, and legitimacy of the census. We argue that rebuilding trust will require more than technical repairs or improved communication; it will require reconstructing what we identify as a ‘statistical imaginary.’

Digital Droplet-PCR for Quantification of Viable Campylobacter jejuni and Campylobacter coli in Chicken Meat Rinses

The EU commission established Regulation (2017/1495) in 2017 to reduce Campylobacter on chicken skin and to decrease the number of human cases of campylobacteriosis attributable to the consumption of poultry meat. A Process Hygiene Criterion based on colony-forming unit data was set to a maximum of 1000 CFU Campylobacter spp. per gram chicken neck skin at slaughterhouses. Confronted with stressors, including cold, oxidative stress or antibiotic treatment, live cells may enter into a viable but non-cultivable state (VBNC) and lose the ability to grow, in reference to the plate count ISO 10272-2:2017 method, but still possess the potential to recover and cause infections under favorable conditions. In this study, a droplet digital PCR combined with the intercalating dye propidium monoazide (PMA) was established for quantification of C. coli and C. jejuni in chicken meat rinses. The PMA was used to inactivate DNA from dead cells in this technique. This method was successfully validated against the reference method according to ISO 16140-2:2016 for accuracy and relative trueness. Additionally, it presented a 100% selectivity for Campylobacter jejuni and C. coli. Moreover, the technical measurement uncertainty was determined according to ISO 19036:2019, and the applicability of ddPCR for quantifying C. coli and C. jejuni in chicken meat rinses was investigated on naturally contaminated samples from slaughterhouses and supermarkets. Results obtained from this study demonstrated a strong correlation to qPCR as well as the classical microbiological reference method.

A climate club to decarbonize the global steel industry

Decarbonizing global steel production requires a fundamental transformation. A sectoral climate club, which goes beyond tariffs and involves deep transnational cooperation, can facilitate this transformation by addressing technical, economic and political uncertainties.

Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review

Over the past decade, escalating trends toward renewable energy resources, electrified transportation, magnifying load demand, erratic energy reserve capacities, dynamic demand response programs, and fast ubiquitous connectivity models have amplified the complexity of energy predicaments owing to the acute intensification of operational and technical uncertainties in the energy grid’s evolutionary phases, one of the pressing challenges that need to be properly addressed. For risk hedging and circumventing the impact of ambiguous parameters, several experts and decision-makers have developed uncertainty modeling approaches for optimization problems under uncertainty. This article first offers a generic overview of traditional uncertainty modeling techniques (such as probabilistic techniques, possibilistic techniques, hybrid probabilistic–possibilistic methods, information gap decision theory, and interval-based analysis) to highlight the significance of robust optimization (RO) method, a state-of-the-art deterministic set-based uncertainty methodology used to optimize a system having uncertain inputs. For this reason – a most popular and pertinent uncertainty modeling technique, the RO approach is precisely introduced to study and recapitulate its remarkable features, decisive modules, and shortcomings. Next, the preceding research on the RO’s contributions in the domain of the power grid is reviewed over three key enablers: Decentralization, Decarbonization, and Digitalization. More specifically, the literature on microgrid, virtual power plant, co/trigeneration, renewable energy with storage units, electric mobility, demand response, and security threats are covered in this survey. Finally, a rigorous discussion on foremost prospects, research gaps, and future directions is quantified. This strategic study can be utilized by researchers, engineers, and power industrialists to anticipate open research areas and unprecedented opportunities related to the application of the RO uncertainty handling method in the futuristic power grid.

Comparison of disk diffusion, MIC test strip and broth microdilution methods for cefiderocol susceptibility testing on carbapenem-resistant enterobacterales

ObjectivesCefiderocol is a catechol-substituted cephalosporin dedicated to the treatment of infections caused by multidrug resistant gram-negative rods. Cefiderocol susceptibility testing might be complex. We compared cefiderocol susceptibility testing methods on a relevant collection of carbapenem-resistant Enterobacterales. MethodsCE-IVD (European CE marking required for all in vitro diagnostic (IVD)) broth microdilution (BMD) plate (ThermoFisher, Waltham, MA, USA) using regular Mueller-Hinton broth, MIC test strip (Liofilchem, Teramo, Italy), and disk diffusion (Liofilchem) were compared to a frozen BMD plate prepared with iron depleted Mueller-Hinton broth. First, a collection of 100 entirely sequenced carbapenem-resistant Enterobacterales was used to compare these methods. Then, a prospective comparison of disk diffusion and CE-IVD BMD was performed on 827 consecutive carbapenem non-susceptible Enterobacterales including 634 carbapenemase-producers. ResultsCompared to reference method, CE-IVD BMD plate gave 95.0% (95% CI, 88.8–97.9) categorisation agreement (CA), 2.8% (95% CI, 0.4–14.2) very major errors (VME), and 1.6% (95% CI, 0.3–8.7) major errors (ME) with high reproducibility. MIC strip gave only 63% (95% CI, 53.2–71.8) of CA and 94.9% (95% CI, 83.1–98.6) of VME due to critical underestimation of the MICs. Disk diffusion gave 77% (95% CI, 67.9–84.2) CA with additional 8% of the isolates within the area of technical uncertainty of 18–22 mm.Prospectively, disk diffusion gave 81.7% (95% CI, 79.0–84.2) CA, 23.3% (95% CI, 15.1–34.2%)VME, and 4.9% (95% CI, 3.6–6.7) ME. Additionally, 21.3% (95% CI, 18.6–24.2) of CRE were within the area of technical uncertainty. DiscussionCommercial CE-IVD BMD (ThermoFisher) is accurate for cefiderocol MIC determination in difficult-to-treat Enterobacterales whereas MIC test strip (Liofilchem), that was formulated for Pseudomonas aeruginosa only, should be avoided. Disk diffusion might be useful for screening, but many of these CRE have to be re-tested using BMD to assess definitive categorization.

Simulating competition among heavy-duty zero-emissions vehicles under different infrastructure conditions

• We simulate competition among ZEV drivetrains in the heavy-duty trucking sector. • In the short-haul market, battery electric and hydrogen fuel cell drivetrains tend to dominate. • In the long-haul market, plug-in hybrid diesel and hydrogen fuel-cell drivetrains tend to dominate. • ZEV drivetrain success is largely driven by the fueling infrastructure that is prioritized. It is highly uncertain which zero-emissions vehicle (ZEV) drivetrains are most suitable for heavy-duty trucks and there is little exploration of how these technologies might compete in the long-term. We used a dynamic model representing technology, cost, and behavioral parameters to simulate adoption of various drivetrains, including battery electric vehicles (BEVs) and fuel cell vehicles (FCVs), in the short- and long-haul sectors using the case study of British Columbia, Canada. Scenarios included a ZEV mandate, various levels of refueling infrastructure deployment, and representation of social and technical uncertainty through Monte Carlo. For short-haul trucks, BEVs and FCVs tend to dominate, depending on supported infrastructure. For long-haul trucks, plug-in hybrid diesel and FCVs are more likely to dominate sales. Results indicate substantial uncertainty in the suitability of different ZEV drivetrains, potential for multiple options to capture the majority of market share, and potential for the prioritized infrastructure to strongly influence adoption.

Computer-aided identification and evaluation of technologies for sustainable carbon capture and utilization using a superstructure approach

Carbon capture and utilization (CCU) offer ways to reduce carbon emissions of fossil-fuel-based industries with lower economic penalties. There has been increasing social demand to invest in CCU technologies but their evaluations for further R&D and commercialization are complicated by the lack of consistent standards for data and methodologies, as well as their varying levels of technical maturity and uncertainty. As numerous combinations of capture and conversion technologies are possible in a commercial implementation, it is essential to perform systematic evaluations in terms of their economics and CO2 reduction potential, both quickly and fairly. This work introduces a computer-aided tool called ArKaTAC3 which can be used for such purposes. The latest version of the software includes features for constructing a superstructure network to model various CCU pathway alternatives from given sources to products and identifying optimal ones. Many difficult issues faced in evaluating CCU technologies, including the collection of reliable life cycle inventory data, system boundary specification, multi-objective specification, and consideration of uncertainty can be managed with the tool and its embedded CCU database, thus lowering the barrier to systematic and quantitative analyses by policymakers and practitioners. Two case studies are performed: (i) identification of sustainable CCU pathways from a superstructure comprising various CO2 utilization technologies and (ii) optimization of a CCU supply chain network in the Middle East. These case studies demonstrate the efficacy and flexibility of the newly-developed tool in making policy- and investment-related decisions for CCU.