Cost Implications Research Articles

“How much should public transport services be expanded, and who should pay? Experimental evidence from Switzerland”

The twin challenge of increasing capacity to accommodate growing travel demand while simultaneously decarbonizing the transport sector places enormous pressure on public transport (PT) systems globally. Arguably the most fundamental policy choice and trade-off in designing and operating PT systems in the coming years will be service levels versus cost implications. On the presumption that public (citizen and consumer) opinion is crucial to making such choices, we study this question with a focus on Switzerland by using a factorial experiment (n = 1′634) that considers the frequency and geographic coverage of PT services as well as the cost implications for PT users and taxpayers. We find that support for increased frequency of connections and more services to peripheral regions is high as long as such service expansion is funded mainly by the government, rather than PT users. Preferences are generally consistent across subgroups, except in the case of government funding, where preferences differ by political orientation. This suggests that there is substantial demand across the board for PT services expansion funded primarily by the government, but that the question of funding is also potentially politically the most controversial. While our findings are specific to a country with a highly developed PT system, our research provides a template for similar research in other countries that struggle with a similar challenge.

Biodiesel production from agricultural biomass wastes: Duroc breed fat oil, Citrillus lanatus rind, and Sorghum Bagasse

This research study synthesized a base catalyst from the waste Citrullus lanatus rind (WCLR) for the synthesis of biodiesel from the waste pig fat oil. The high-acid-value oil (high free fatty acid: FFA) was converted to low-acid-value oil through adsorption in sorghum bagasse ash with high particle sizes. The developed base catalyst was obtained from the WCLR and was characterized via thermogravimetric analysis (TGA), Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD-FT), and Brunauer-Emmett-Teller (BET) adsorption analysis. The properties of biodiesel were compared with the recommended standard.Results reflected that the duroc breed pig fat is rich in oil, and the oil is unsaturated. Sorghum bagasse proved to be a good bio-adsorbent for the unsaturated fat FFA reduction. The catalyst produced from WCLR was found to be rich in potassium-calcium-magnesium (K-Ca-Mg) base salts. The predicted yield of 98.69 % (wt./wt.) at 69.96 min, 79.93 °C, 3.15 % (wt.), and 8.57 (vol.) at desirability of 100 % was validated as 98.52 % (wt./wt.). Catalytic strength can be recycled in five cycles. The cost implications indicated that the cost of producing 25 L of biodiesel is $2.61.This study proved to be the most economical way of producing biodiesel that is environmentally friendly, cost-effective, and easy to produce for future energy needs.•Oil was obtained via rendering from duroc breed waste fat oil.•Sorghum bagasse was used as adsorbent for acid reduction of high FFA pig fat oil.•Base catalyst used was obtained from calcined waste Citrullus lanatus rind.

Policy uncertainty, mergers, and acquisitions in the South African business environment

ABSTRACT This study examines policy uncertainty on mergers and acquisitions (M&A) in South Africa, emphasising the extensive regulatory review by the Competition Commission under the ‘public interest consideration’ criterion. It aims to identify the cost implications and uncertainties associated with M&A transactions to propose measures to reduce these uncertainties. Utilising qualitative methodologies, the study gathers empirical evidence through interviews with companies and competition lawyers involved in the M&A processes. The findings reveal significant concerns about economic uncertainty, merger control, and policy and regulation impacting investment decisions. Policy uncertainty, particularly in the context of merger regulation, imposes substantial cost implications and delays on M&A activities, negatively affecting investment, growth, and economic development. It emphasises the necessity for a regulatory framework that minimises disruptions and costs to business participants. The findings suggest that addressing policy uncertainty and streamlining regulatory processes are crucial steps towards enhancing South Africa's attractiveness as an investment destination and fostering economic growth and development.

Social Economic Challenges of Adaptation to Climate Change in Masinga Sub-County, Kenya

Climate in Masinga sub-county has been changing at a momentum which is unprecedented in the recent human history. This area consists mainly small-scale farmers who depend on rain to carry out their farming activities. Coping strategies to the changing climate in the area has faced various challenges ranging from high poverty, low levels of education, age, gender among others. This study investigated how social-economic challenges affecting adaptation strategies on climate change among the households living in Masinga sub-county, in Kenya. The main objectives of the study included; 1) To examine the adaptation strategies employed by households in Masinga sub-county 2) To determine the main factors that affect household in adaptation to climate change in Masinga sub-county 3) To investigate the environmental implications of adaptation to climate change in Masinga sub-county. Essentially, variables such as education levels, age, gender, were assessed. In order to gain an understanding on adaptation strategies used by households in Masinga sub-county, the study was conducted in all six divisions. Various methods of sampling were used in the survey which included stratified random sampling based on the number of households proportionately in the six divisions. In essence, 384 household heads were sampled through stratified random sampling. The study employed specific data collection tools in order acquire data from the six divisions; structured questionnaires, interviews schedules, Focused Group Discussions (FGDs) and direct observation were used. Qualitative data was collected through; interviews, Desk research, Focus Group Discussions comprising six to eight sampled through stratified random sampling and purposive sampling. The households coping strategies, influence of adaptation strategy to climate change and environmental implications of household adaptation was analyzed through both qualitative and quantitative interpretation. Data from survey was organized and analyzed using descriptive and inferential statistics. The results were subjected to statistical package for social sciences (SPSS) to determine their reliability. When applying descriptive statistics, the results were presented in tables, bar graphs, and charts. In this study Chi-squire was used because it was easier to compare the results from a two dimensional perspective. These results after analysis by chi-square test, the p-value was found to be .001, thus, smaller than the significance level (α = .05). Using Chi-square tests, this study established that there is strong evidence of an association between the education level and the implementation of green-house farming (Χ2 (3) = 1.064, p = 0.001). Further analysis by chi-square test indicated that the p-value was found to be .008, thus, less than the significance level (α = .05). This study established that early warning as a strategy to adaptation to climate change was not common amongst households in the area. Further research is suggested on impact of charcoal burning on climate change adaptation and cost implications in semi- arid areas. The study findings will enable the government and other relevant stakeholders to ensure that early warning system information is able to reach the local residents at all times

A comprehensive review of landfill leachate treatment technologies

The management of landfill leachate presents a significant environmental challenge, necessitating a comprehensive and dynamic treatment approach. This comprehensive review delves into the critical issue of landfill leachate treatment, exploring its environmental impact, treatment technologies, regulatory frameworks, and the path towards sustainable management practices. This review explores the complexities of landfill leachate, emphasizing the need for sustainable waste management practices to safeguard environmental health. Our analysis highlights the evolution of conventional and advanced treatment technologies designed to mitigate these risks, focusing on membrane technologies, advanced oxidation processes, and the promising potential of emerging techniques such as adsorption and biological nutrient removal. These technologies are evaluated for their efficiency, cost implications, and sustainability impacts, underscoring the challenges and opportunities within the current landscape of leachate treatment. The review aims to provide insights into designing efficient and effective treatment systems through a detailed analysis of conventional and advanced treatment methods. By examining a case study in Changsha City, the effectiveness of a comprehensive treatment system integrating various technologies is demonstrated. The review underscores the interconnectedness of human activities, environmental health, and waste management, emphasizing the importance of a holistic approach. It stresses the continuous improvement of leachate treatment technologies and the adoption of sustainable practices to reduce the environmental footprint of landfills. Ultimately, it calls for integrating multiple treatment processes, economic considerations, and readiness to address future challenges in landfill leachate treatment, contributing to the advancement of sustainable waste management practices.

Economic Evaluation of Fasting Mimicking Diet vs Standard Care in Diabetic Patients on Dual or Triple Medications at Baseline in the United States: A Cost-Utility Analysis

ObjectivesAccording to most guidelines, dietary interventions are essential in the management of diabetes. Fasting has emerged as potential therapeutic regimes for diabetes. The proof-of-concept study and the fasting in diabetes treatment trial are the first to explore the clinical impact of the Fasting Mimicking Diet (FMD) in patients with type 2 diabetes mellitus. Their results showed that FMD cycles improve glycemic management and can be integrated into usual care complementary to current guidelines. This economic evaluation aims to assess the 10-year quality-of-life effects, cost implications, and cost-effectiveness of adding a 3-year FMD program to diabetes standard care in diabetic population on dual or triple medications at baseline from the perspective of the US payer. MethodsWe constructed a microsimulation model in TreeAge using a published US-specific diabetes model. The model was populated using FMD effectiveness outcomes and publicly available clinical and economic data associated with diabetes complications, use of diabetes medications, hypoglycemia incidence, direct medical costs in 2021 USD, quality of life, and mortality. All benefits were discounted by 3%. ResultsThis cost-utility analysis showed that the FMD program was associated with 11.4% less diabetes complications, 67.2% less overall diabetes medication use, and 45.0% less hypoglycemia events over the 10-year simulation period. The program generated an additional effectiveness benefit of 0.211 quality-adjusted life year and net monetary benefit of 41 613 USD per simulated patient. Thus, the FMD program is cost saving. ConclusionsThese results indicate that the FMD program is a beneficial first-line strategy in T2DM management.

Field efficacy of insecticides for suppressing white mango scale insect (Aulacaspis tubercularis Newstead) (Hemiptera: Diaspididae) in southwest Ethiopia

White mango scale (WMS) Aulacaspis tubercularis Newstead (Hemiptera: Diaspididae) is a polyphagous armored scale insect which is considered one of the key pests of mango (Mangifera indica L.) around the world. Mango is widely grown in Ethiopia whereas its production is challenged by WMS in the last decade. Effective formulations that could help manage the scale as part of IPM practice were sought from field experiments at Seka mango farm, Ethiopia in 2019 and 2020 seasons. The study aimed to evaluate the efficacy of some formulations against WMS on mango trees. Randomized complete block designs with three replications were used for the experiments and each tree served as a plot. Allocation of each treatment within each replication was done randomly. The treatments were applied sequentially three times at 14 days interval using motorized Knapsack sprayer coinciding with peak period of natural infestation. Scale numbers before and after each spray were counted using a microscope with LCD. Sum of live crawler, female and male was registered as WMS count data. Results showed that dimethoate, diazinon, imidacloprid & λ-cyhalothrin sprayed alone; dimethoate rotated with imidacloprid & λ-cyhalothrin, chlorpyrifos-ethyl rotated with paraffin, and diazinon rotated with azadirachtin, caused total mortality of the scales. The results also showed that, chlorpyrifos-ethyl, deltamethrin, paraffin oil and λ-cyhalothrin sprayed alone caused percent reduction with range 83–95 % in both seasons. Hence, the study revealed that dimethoate, diazinon, imidacloprid & λ-cyhalothrin applied individually, dimethoate rotated with imidacloprid & λ-cyhalothrin, chlorpyrifos-ethyl rotated with paraffin and diazinon rotated with azadirachtin fully protect mango trees from WMS and significantly superior to other treatments. Therefore, chemical control of A. tubercularis may consider the use of these materials as foliar application and can be used as components for integrated pest management plans for WMS. However, application in the form of rotation is preferred to the alone spray as the former could substantially reduce the likelihood of inducing pesticide resistance. Cost implications and effects of the products on the natural enemy and residual toxicity in fruits need to be studied.

Optimizing sequential decision-making under risk: Strategic allocation with switching penalties

This paper considers the multiarmed bandit (MAB) problem augmented with a critical real-world consideration: the cost implications of switching decisions. Our work distinguishes itself by addressing the largely unexplored domain of risk-averse MAB problems compounded by switching penalties. Such scenarios are not just theoretical constructs but are reflective of numerous practical applications. Our contribution is threefold: firstly, we explore how switching costs and risk aversion influence decision-making in MAB problems. Secondly, we present novel theoretical results, including the development of the Risk-Averse Switching Index (RASI), which addresses the dual challenges of risk aversion and switching costs, demonstrating its near-optimal efficacy. This heuristic solution method is grounded in dynamic coherent risk measures, enabling a time-consistent evaluation of risk and reward. Lastly, through rigorous numerical experiments, we validate our algorithm’s effectiveness and practical applicability, providing decision-makers with valuable insights and tools for navigating the multifaceted landscape of risk-averse environments with inherent switching costs.

Development of powerpoint-based learning media to improve student learning outcomes on the material of economic science concepts at MA Hamid Rusydi MalangDevelopment of powerpoint-based learning media to improve student learning outcomes on the material of economic science concepts at MA Hamid Rusydi Malang

Introduction: Introduction: Learning resources are an important component of learning. The purpose of this study is to analyze the feasibility, viability, effectiveness, or extent of development of PowerPoint-based learning resources on the topic of conceptual economics in MA Hamid Rasidi Malang. Methods: The research methodology was developed using two types of data, quantitative and qualitative. Finding: The development of this learning tool was adapted from the development model of Borg and Gall (2003), which has 10 phases, but the researchers implemented eight phases due to time, energy, and cost implications. The eight phases are: research and data collection, planning, product format development, initial testing, product revision, intensive field testing, final product revision, implementation, and deployment. The study found that based on feasibility testing by six reviewers, the validity level of the learning media product averaged 96% high feasibility from two subject matter experts, 97% high feasibility from two language experts, 91% high feasibility from two media experts, two social studies teachers. The average feasibility was 96% high from MA. Hamid Rasidi Malang and MA. Said Malang, and 91% high from the students of MA. Hamid Rasidi Malang and MA. Nasional Malang. Conclusion: Malang students indicated that the initial test results before the use of the PowerPoint-based materials were highly effective with an average of 92%, and the results after the use of the PowerPoint-based materials were highly effective with an average of 98%. This indicates that the developed product can be used in social studies and is practical and effective.

Optimizing the moving average trade rule for cryptocurrencies: implications of band size and transaction costs

ABSTRACT In this paper, we apply an adjustable-band moving average algorithm to study technical analysis profitability in cryptocurrency markets. We find three main results. First, adjustable band trade rules act like a leveraged bet: they outperform fixed band rules in years when technical analysis is profitable and under-perform in other years. Second, our algorithm suggests significantly higher than standard 0% and 1% optimal band parameter values. Third, by comparing adjustable band rules with higher fixed band rules, we show that adjustable band rules have value beyond finding high optimal bands. Technical traders should consider higher and adjustable-band rules, especially with above-zero transaction costs.

Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data

In this study, we address critical barriers hindering the widespread adoption of surgical navigation in orthopedic surgeries due to limitations such as time constraints, cost implications, radiation concerns, and integration within the surgical workflow. Recently, our work X23D showed an approach for generating 3D anatomical models of the spine from only a few intraoperative fluoroscopic images. This approach negates the need for conventional registration-based surgical navigation by creating a direct intraoperative 3D reconstruction of the anatomy. Despite these strides, the practical application of X23D has been limited by a significant domain gap between synthetic training data and real intraoperative images.In response, we devised a novel data collection protocol to assemble a paired dataset consisting of synthetic and real fluoroscopic images captured from identical perspectives. Leveraging this unique dataset, we refined our deep learning model through transfer learning, effectively bridging the domain gap between synthetic and real X-ray data. We introduce an innovative approach combining style transfer with the curated paired dataset. This method transforms real X-ray images into the synthetic domain, enabling the in-silico-trained X23D model to achieve high accuracy in real-world settings.Our results demonstrated that the refined model can rapidly generate accurate 3D reconstructions of the entire lumbar spine from as few as three intraoperative fluoroscopic shots. The enhanced model reached a sufficient accuracy, achieving an 84% F1 score, equating to the benchmark set solely by synthetic data in previous research. Moreover, with an impressive computational time of just 81.1 ms, our approach offers real-time capabilities, vital for successful integration into active surgical procedures.By investigating optimal imaging setups and view angle dependencies, we have further validated the practicality and reliability of our system in a clinical environment. Our research represents a promising advancement in intraoperative 3D reconstruction. This innovation has the potential to enhance intraoperative surgical planning, navigation, and surgical robotics.

Determining Payback Period and Comparing Two Small-Scale Vertical Axis Wind Turbines Installed at the Top of Residential Buildings

In recent years, residential buildings have seen a notable increase in energy consumption. To address this, it is crucial for researchers to invest in renewable energy technologies, aiming to develop highly sustainable and nearly-zero energy buildings. Many countries are started to commit to this goal, seeking to phase out fossil fuels due to their harmful environmental effects. Wind energy stands out as a promising renewable resource, especially in areas with strong wind patterns. This study focuses on a case in Karaburun, Izmir province, Türkiye, where annual wind speeds range from 6 to 8 m/s and evaluates the performance of two types of small-scale Vertical Axis Wind Turbines (VAWTs) in reducing energy consumption in a three-story residential building, along with associated costs. Utilizing advanced simulation tools like ANSYS Fluent and DesignBuilder Software, the study examines Ice-Wind VAWTs and Savonius VAWTs. The findings reveal that installing 15 Ice-Wind VAWTs on the building's roof can reduce energy consumption by approximately 22.5%, with each turbine costing about $2000 and a payback period of around 14.57 years. Conversely, using 15 Savonius VAWTs can reduce energy consumption by 36%, with each turbine costing about $2300 and a payback period of around 8.93 years. These results indicate that the Savonius turbine offers a faster return on investment compared to the Ice-Wind turbine under the specified conditions. Overall, this study highlights the significant benefits and cost implications of integrating renewable energy solutions like VAWTs into residential buildings.

Effective green building design assessment support using sequential multidisciplinary design optimization

Green building (GB) represents a leading approach for promoting sustainable development, reducing environmental impact, and ensuring environmental responsibility across its entire life cycle. Many countries have recently developed rating systems and certification programs for GBs. Traditional GB assessment is conducted through manual and iterative procedures that entail numerous meetings and trials. Architects and engineers must thoroughly assess the interdependence of design variables to ensure compliance with assessment standards for feasible solutions in GB projects. This process could be complicated and error-prone, leading to potential cost implications. Therefore, there is a need to develop design support systems to generate feasible solutions for GBs effectively. This paper introduces an integrated assessment system for GB designs, employing a multidisciplinary design optimization (MDO) methodology to efficiently generate solutions across various disciplines, adhering to assessment standards. Practical cases in Taiwan have been employed to assess and confirm the efficiency and effectiveness of the proposed system concerning the design of building envelopes, air-conditioning systems, and artificial lighting systems. The primary advantages of the system include the rapid generation of multiple alternatives and the reduction of iterations in GB assessment by providing conflict-free solutions across various disciplines. The proposed system also offers estimated construction costs for each alternative. Designers can further explore the most cost-effective solutions through value analysis. This information can assist investors in making informed decisions. The proposed design support system shows great potential in accelerating the design process for green buildings by offering conflict-free alternatives and value-added information.

The potential of crematoria as a recoverable waste heat resource for district heating in the UK

Cremation is an energy-intensive process that represents the most popular funeral rite in the United Kingdom. Typically, a cremation lasts for 80 min and furnaces reach temperatures of up to 1000 °C. In order to remove pollutants such as mercury, cremation flue gas must be cooled down to temperatures below 160 °C, offering an opportunity for waste heat to be recovered and reused. Recent case studies have estimated that from 200 to 400 kW of waste heat is released during a typical cremation. Firstly, these reported values are used to determine the heat recovery potential from 314 crematoria across the UK, which varies from 141 to 281 GWh per annum. Secondly, a case study for integrating cremation waste heat into district heating (DH) in England is presented, and heat demand data for an existing network are used to evaluate the carbon and cost implications of exploiting cremation waste heat. Findings suggest that, although a small heat source, cremation heat can be an efficient resource for displacing peak gas usage in larger DH networks. This paper sits within the broader field of heat recovery, and the methods and concepts presented can also be applied to a wider range of heat sources and localities.

Understanding the Activity and Stability Relationship on Metal Oxide Surfaces during the Electrochemical Generation of Reactive Oxygen Species

Inappropriate waste disposal is a significant anthropogenic source of water pollution. This action is responsible for the release of a variety of pollutants into water bodies, including heavy metals, inorganic and organic compounds, which can have severe consequences for aquatic ecosystems and human communities.[1] Particularly, some organic contaminants such as Bisphenol A (BPA) and Per- and Polyfluoroalkyl Substances (PFAS) commonly found in trace concentrations can remain in the environment due to their high resistance to breakdown.[2] Thus, the development of highly effective water remediation technologies is a challenge.Electrochemical methods stand out among the array of tools due to their ability to eliminate pollutants effectively and selectively in an environmentally friendly way. The advantage of the method is tied to the electrochemical advanced oxidation processes (EAOP), which involve the generation of highly reactive oxygen species (ROS), such as hydrogen peroxide (H2O2), ozone(O3), and hydroxyl radicals (•OH). These species can indirectly mineralize organic pollutants to CO2 and H2O. The ROS generation is related to the electrocatalyst's nature, being limited for some classes of materials, such as metal oxides (PbO2, SnO2, TiO2, WO3), and Boron-Doped Diamond (BDD).[2-5] Despite their highly reactive nature, we still know very little about the impact of ROS on the surface stability of metal oxide surfaces that show a high overpotential for the oxygen evolution reaction (OER), and therefore, are believed to generate predominantly ROS at high electrode potentials (e.g., >1.7 V vs reversible hydrogen electrode, RHE). Concerning the electrocatalysts' stability, the eventual deactivation constitutes a pivotal parameter with significant implications for the operational cost to commercialize this water remediation approach.Hence, to understand the trends in surface stability of metal oxides and their correlation to the activity toward ROS formation, we have deployed a combination of in situ electrochemical methods that allow us to directly measure the reaction rates (current) simultaneously with metal dissolution rates using the Stationary Probe Rotating Disk Electrode-ICP-MS method, and selectivity for the formation of O2, H2O2. Ou study framed metal oxides typically considered non-active for oxygen evolution and capable of generating ROS, such as PbO2, SnO2, TiO2, and ZnO.[3] To establish a comparative benchmark, we also utilized IrO2, known as a good OER catalyst due to its high activity-stability factor (ASF).[6-8] Figure 1 shows a set of cyclic voltammetry data obtained from a PbO2 surface in 0.1 mol L-1 NaOH. Although we observe oxidation currents only above 1.9 V vs RHE, monitoring the ring current at two different potentials reveals close to 100% selectivity towards O2 evolution and below 0.2% for H2O2 up to 2.2 V, while the onset of metal dissolution occurs above 2.1V. This result suggests that O2 evolution is still present even on materials that require very high overpotentials, and that metal dissolution might be intrinsically related to the formation of O2 and ROS from the electrolyte’s adsorbed oxygen anions on the metal oxide surface and/or (ionically) bonded oxygen anions in the metal lattice as expected from thermodynamic considerations.[9] Such fundamental comprehension about how the dissolution process impacts the activity of the surface sites for ROS generation can guide the design of not only active but also stable materials for water remediation systems.[10]

(Invited) Achieving Robustness and Economic Viability in CO2 Electrolysis Scale-up: Key Results from RenewCO2

RenewCO2 is commercializing processes to convert carbon emissions from chemical manufacturing, which contributes 274 million metric tons of CO2eq annually in the U.S. alone. Our pioneering electrocatalytic Carbon Utilization Technology (eCUT) is adept at upcycling CO2 from hard-to-decarbonize industrial sources. By synthesizing commodity chemicals from CO2 emissions, eCUT promises high energy efficiency while producing carbon-negative materials. The critical innovation of RenewCO2’s eCUT process is deploying catalysts designed with readily available metals, optimizing the process to reduce CO2 into multi-carbon chemicals selectively with impressive energy efficiency.RenewCO2 has significantly advanced CO2 electrolyzer scale-up, focusing on demonstrating process robustness and economic feasibility. Targeting liquid products such as monomers (glycols), RenewCO2 has demonstrated cost-advantaged process economics compared to the incumbent petrochemical and bio-derived routes. We present detailed findings on the enhanced performance of our proprietary catalysts, which have shown remarkable endurance under prolonged operational conditions (1000 h of operation) in a scaled-up stack containing five 500 cm2 electrodes. The RenewCO2 team has demonstrated consistent electrolyzer performance with minimal degradation over extended periods. We also delve into improvements in energy efficiency, showcasing how these enhancements contribute to the overall process economics.The purification process is crucial in making carbon-negative materials from CO2 that do not require a green premium. In this regard, RenewCO2 has achieved remarkable progress in demonstrating a highly energy-efficient product purification. In collaboration with Argonne National Lab, we have developed an advanced electrochemical separation method that removes ionic species from the products to comply with strict industrial standards and increase their market value. A key development in this area is our innovative approach to electrodeionization, which combines ion-exchange membranes with electrically active media. This method exhibits low energy consumption, robustness, and simple operation. These advancements in the purification process are integral to our system’s overall efficiency and are pivotal in our pursuit of creating economically viable and sustainable electrochemical manufacturing solutions.On the economic front, we provide an in-depth analysis of the cost implications of scaling up. This includes a breakdown of the capital and operational costs, along with a comparative analysis with existing technologies. We discuss the main factors contributing to product cost and strategies to minimize them, such as the integration of low-cost materials and judicious choice of operating conditions.Our aim is to provide a transparent and comprehensive overview of the challenges and the state-of-the-art in scaling up CO2 electrolysis to liquid products, offering valuable insights for the scientific community and stakeholders in the field.

Enhancing Efficiency and Selectivity of Electrochemical Regeneration of NADH By Dynamic Operation

The demand for the reduced nicotinamide adenine dinucleotide (1,4-NADH) and reduced nicotinamide adenine dinucleotide phosphate 1,4-NAD(P)H in industrial processes, particularly in the pharmaceutical sector, necessitates their continuous regeneration to mitigate cost implications [1]. In this respect, direct electrochemical cofactor regeneration is a promising alternative, but challenges in achieving optimal selectivity have hindered its widespread industrial integration.This study focuses on advancing the efficiency and selectivity of electrochemical NADH regeneration through dynamic potential inputs, inspired by recent findings demonstrating improved selectivity using dynamic potential inputs instead of steady-state conditions [2]. Various dynamic, pulsed potential profiles are tested and compared with steady-state conditions, revealing distinct advantages in selectivity. Nicotinamide adenine dinucleotide reduction reaction is then coupled with the enzymatic conversion of a substrate (cyclohexenone) to a product (cyclohexanone). In this electroenzymatic biotransformation, 1,4-NADH formed electrochemically is utilized as a second substrate of enzyme enoate reductase. The success of this coupling is evident in the observed formation of the desired product. This research not only contributes to the fundamental understanding of electrochemical co-factor regeneration but also demonstrates its practical application. By combining the advantages of electrochemical and enzymatic reactions, we pave the way for more sustainable and economically viable industrial processes. The presented results mark a significant step towards harnessing the full potential of electrochemical regeneration in facilitating enzymatic transformations with enhanced efficiency and selectivity through a pulsed dynamic operation.

Patient-related factors drive high rates of reported antibiotic allergies: A qualitative study

BackgroundUnnecessary antibiotic avoidance due to allergy fears has adverse cost and health implications however, the problem is difficult to resolve because patient and provider-related factors leading to avoidance are multifactorial. We use qualitative research methods to explore patient perspectives of antibiotic allergy and testing to reach the heart of the problem. ObjectiveTo reveal factors leading patients to report antibiotic allergy, and determine what education is required to prevent the cycle of erroneous allergy reporting. MethodsThe 29 patients were a sample of convenience recruited from a tertiary public hospital in Western Australia between March 2020 until August 2020; 18 were inpatients and 11 outpatients, with a median age of 64.2 years, and 15 (55%) were female. Semi-structured interviews assessed patients’ understanding and knowledge of three topics: (1) antibiotic allergy, (2) antibiotic allergy testing, and (3) outcomes of testing. Interview transcripts underwent thematic analysis by two researchers, independently. ResultsThree main, overlapping themes emerged as influential across topics: (1) Severity of the Index Reaction, (2) Trust in family and health care providers, and (3) Health literacy. Patients were largely unaware of the benefits of confirmatory testing, and the detrimental health consequences of unnecessary avoidance. Patients displayed trust in health care providers’ expertise and assumed that medical records were accurate to prevent prescribing errors. ConclusionsThe findings provide evidence for an effective patient education strategy and highlight failures among hospital and primary health providers to recognise the potential harm of unverified antibiotic allergy. Healthcare professionals are influential at multiple steps of a patient's healthcare journey and addressing unconfirmed antibiotic allergy should be taken at each opportunity.

Examining breast cancer screening recommendations in Canada: The projected resource impact of screening among women aged 40-49.

To quantify the resource use of revising breast cancer screening guidelines to include average-risk women aged 40-49 years across Canada from 2024 to 2043 using a validated microsimulation model. OncoSim-Breast microsimulation platform was used to simulate the entire Canadian population in 2015-2051. We compared resource use between current screening guidelines (biennial screening ages 50-74) and alternate screening scenarios, which included annual and biennial screening for ages 40-49 and ages 45-49, followed by biennial screening ages 50-74. We estimated absolute and relative differences in number of screens, abnormal screening recalls without cancer, total and negative biopsies, screen-detected cancers, stage of diagnosis, and breast cancer deaths averted. Compared with current guidelines in Canada, the most intensive screening scenario (annual screening ages 40-49) would result in 13.3% increases in the number of screens and abnormal screening recalls without cancer whereas the least intensive scenario (biennial screening ages 45-49) would result in a 3.4% increase in number of screens and 3.8% increase in number of abnormal screening recalls without cancer. More intensive screening would be associated with fewer stage II, III, and IV diagnoses, and more breast cancer deaths averted. Revising breast cancer screening in Canada to include average-risk women aged 40-49 would detect cancers earlier leading to fewer breast cancer deaths. To realize this potential clinical benefit, a considerable increase in screening resources would be required in terms of number of screens and screen follow-ups. Further economic analyses are required to fully understand cost and budget implications.

Output tracking of coupled stochastic strict-feedback higher-order nonlinear systems under pinning control

This paper focuses on the tracking problem for a class of coupled stochastic strict-feedback higher-order nonlinear systems under pinning control. Compared with existing stochastic nonlinear tracking designs, our approach stands out by simultaneously considering coupling and higher-order characteristics for the first time. By utilizing the backstepping technique and designing virtual controllers, we obtain actual controllers that ensure the closed-loop system has an almost surely unique solution and is bounded in probability. Additionally, the fourth-moment of the output tracking error can be rendered arbitrarily small in the long run. Notably, to address the cost implications of imposing a controller on each node, we employ a pinning control strategy to selectively control a portion of the nodes. Moreover, a global Lyapunov function is derived combining Lyapunov method with graph theory. Eventually, a numerical simulation is shown to verify the theoretical results.