Net Reduction Research Articles

Pilot study to measure the energy and carbon impacts of teleworking

Teleworking offers various socio-economic benefits to the workforce, especially during major disasters. However, the holistic net energy and greenhouse gas (GHG) emissions impacts of telework remain poorly understood. This paper develops and tests a longitudinal mixed-methods approach to estimate energy and emissions in three domains: home office, transportation, and information and communications technology (ICT). A pilot study of 11 participants from Ottawa, Canada, is used to evaluate the method, while generating a rich dataset and new insights. The results show transportation, home heating and cooling account for > 94% of telework-related energy, while home office equipment, lighting and ICT account for the remaining 6% (and < 2% of GHG emissions). Not including employer offices, teleworking will likely yield a net reduction in energy and GHG emissions compared with conventional working arrangements, but this result is dependent on personal choices, routines, purchasing decisions and household structure. The paper concludes with a discussion and future recommendations for the developed method based on the lessons learned. Practice relevance A new mixed-methods approach was developed and piloted to study the holistic energy impacts of teleworking. This demonstrates measurement tools, data analysis measures and scenario modelling. It provides lessons learned and acknowledges limitations. It is a major step forward in setting the stage for larger scale studies. The specific results showed that compared with conventional working arrangements, nine of the 11 participants are likely to consume less energy and produce fewer GHG emissions when teleworking based on a scenario-based analytical approach. However, if workers use sustainable transportation, teleworking may not yield any energy savings as increases in the home domain are expected. Future studies should include the employer offices.

Particle- and Light-Mediated Processes Control Seasonal Manganese Oxide Cycling in a Meromictic Pond

Manganese (Mn) oxides are strong oxidants and sorbents of nutrients and contaminants, thus their formation mechanisms impact multiple biogeochemical cycles. Manganese in oxic surface waters is often found as dissolved Mn species, such as Mn(II) and Mn(III)-ligand complexes, rather than Mn oxides. This is believed to be a result of Mn oxide reduction by hydrogen peroxide associated with photolysis of organic matter and direct organic matter-mediated reduction within sunlit waters. Nevertheless, Mn oxides can persist in some surface environments, which indicates an incomplete understanding of controls on Mn oxide distributions. Here, we couple field- and lab-based analyses to explore Mn oxide distributions, Mn oxidation rates, and underlying controls on Mn oxide formation within Siders Pond, a brackish and meromictic pond on Cape Cod (Massachusetts, USA) during the summer and fall of 2020. Manganese oxides were observed consistently in sunlit surface waters with concentrations declining to undetectable at the base of the chemocline. Surface Mn oxide concentrations were highest in late summer, reaching concentrations of ∼1 μM, and lowest in late fall, reaching only ∼50 nM. Minerals identified using synchrotron-based absorbance measurements were structurally similar to δ-MnO2 and feitknechtite. Substantial light-mediated Mn oxidation only took place in live incubations of Siders Pond water while net Mn reduction proceeded in killed incubations. Thus, total particle-mediated oxidation by microbes and minerals combined outpaced photoreduction, leading to net accumulation of Mn oxides within Siders Pond. Our results identify important roles for microbial- and mineral-mediated oxidation in determining Mn oxide distributions within surface waters of a natural setting, a finding that may help explain comparable distributions in other locations.

Effects of climate change on the potential distribution of a dominant, widely distributed oak species, Quercus candicans, in Mexico

Mexican temperate forests are among the most biodiverse in the world. At present, they face anthropogenic pressures and climatic changes. Quercus candicans is a canopy-dominant, widely distributed species common in the moist habitats of these ecosystems. Its ecological importance, habitat vulnerability, and wide distribution make it a useful model of the vulnerability of Mexican tree forest species to climate change. We used ecological niche modeling to estimate future climatic suitability for this species and its potential range shifts under two emissions scenarios and three-time frames. We also identified areas where novel climates could arise and where predictions should be interpreted cautiously. Additionally, we analyzed how climatic suitability could change across the national protected areas system. In both emissions scenarios, areas with suitable climatic conditions were predicted to experience a net reduction of more than 40% by 2070. This corresponds to more than 100 000 km2 becoming climatically unsuitable. In the national protected areas, we forecast a contraction of approximately 30%. Climatic novelty increased considerably in the higher emissions scenario (RCP 8.5), accounting for 10% of the Mexican temperate mountains, compared to 1% on RCP 4.5. Areas of expansion of suitability not intersected by novel climates occur in areas highly affected by land-use change and other anthropogenic pressures. Effective protection of temperate forests’ tree species such as Q. candicans would need to allow migrations across altitudinal gradients, as areas of stability and expansion of climatic suitability are forecasted to occur at higher altitude sections of mountain ranges.

Metabolic engineering for the production of acetoin and 2,3-butanediol at elevated temperature in Parageobacillus thermoglucosidasius NCIMB 11955.

The current climate crisis has emphasised the need to achieve global net-zero by 2050, with countries being urged to set considerable emission reduction targets by 2030. Exploitation of a fermentative process that uses a thermophilic chassis can represent a way to manufacture chemicals and fuels through more environmentally friendly routes with a net reduction in greenhouse gas emissions. In this study, the industrially relevant thermophile Parageobacillus thermoglucosidasius NCIMB 11955 was engineered to produce 3-hydroxybutanone (acetoin) and 2,3-butanediol (2,3-BDO), organic compounds with commercial applications. Using heterologous acetolactate synthase (ALS) and acetolactate decarboxylase (ALD) enzymes, a functional 2,3-BDO biosynthetic pathway was constructed. The formation of by-products was minimized by the deletion of competing pathways surrounding the pyruvate node. Redox imbalance was addressed through autonomous overexpression of the butanediol dehydrogenase and by investigating appropriate aeration levels. Through this, we were able to produce 2,3-BDO as the predominant fermentation metabolite, with up to 6.6g/L 2,3-BDO (0.33g/g glucose) representing 66% of the theoretical maximum at 50°C. In addition, the identification and subsequent deletion of a previously unreported thermophilic acetoin degradation gene (acoB1) resulted in enhanced acetoin production under aerobic conditions, producing 7.6g/L (0.38g/g glucose) representing 78% of the theoretical maximum. Furthermore, through the generation of a ΔacoB1 mutant and by testing the effect of glucose concentration on 2,3-BDO production, we were able to produce 15.6g/L of 2,3-BDO in media supplemented with 5% glucose, the highest titre of 2,3-BDO produced in Parageobacillus and Geobacillus species to date.

Cooperative coordination between port microgrid and berthed ships with emission limitation and peak awareness

Due to growing concerns on energy efficiency and environmental issues, most ports are increasingly being equipped with cold ironing (CI) facilities, i.e., shoreside power supply facilities, which provide energy to ships at berth from the shoreside grid. The emergence of CI has coupled the energy connection between port microgrid and berthed ships. However, simply treating CI demands from berthed ships as passive loads, without considering the energy coordination, will increase the operational burden of the port. In this paper, an incentive-based cooperative coordination framework between port microgrid and berthed ships is proposed, where the flexibility of CI power is used as a demand response tool. With the aim of minimizing the net cost comprising energy cost and potential demand charge, the port will differentially coordinate berthed ships to adjust their CI demand requests, to alleviate peak burden. The social cost minimization as well as net cost reduction of each participant will be achieved in this cooperative coordination framework. Asymmetric Nash bargaining is adopted to design incentive mechanism, where a novel index, termed as contribution rate is proposed to evaluate the participants’ contributions to the coordination. Distributed solution is proposed to solve the optimization problem, to guarantee the autonomy and information privacy of participants. Simulation results demonstrate the validity of the proposed method in achieving benefits for both port and berthed ships.

Economic and operational investigation of CO2 sequestration through enhanced oil recovery in unconventional reservoirs in Colorado, USA

The ongoing CCUS commercial projects are highly relied on the support of government incentives due to massive capital investment. This study analyzes the economics of carbon capture utilization and sequestration (CCUS) projects, shows a state-wide CCUS deployment exercise, followed by simulation results of enhanced oil recovery (EOR) based CO2 storage in unconventional reservoirs. The comprehensive economic analysis of capture, transportation, sequestration costs, enhanced 45Q tax credits, and EOR revenue implies the practicality of CO2-EOR to offset the high CCUS costs. With the economics understanding, we study the top CO2 sources, existing CO2 pipelines, and sequestration sinks in the state of Colorado, USA. This paper next presents results from EOR simulation in one section of the unconventional Denver-Julesburg (DJ) Basin Niobrara and Codell reservoirs. The simulation model is based on a geological static model, incorporated with hydraulic fracture stimulation, history matched to production, and calibrated to the microseismic and time-lapse surface seismic data. The CO2-EOR simulation results show that oil production can be increased and more CO2 stored with: a longer primary production period; the presence of a shut-in period; higher injection rates; and multi-well injectors. The modeling results show that about 7–10 Mscf of CO2 will be stored when recovering 1 stb of EOR oil. By adding the enhanced oil revenue and the carbon credits together, it is estimated that the most economic case can generate $13 MM when oil price is assumed to be $80/stb, and the EOR oil revenue is 3.4 times greater than that generated from 45Q incentives. It corresponds to the scenario that a five-year primary production is followed by CO2 injection into four wells with the sequence of injection (4 MMscf/day for 6 months), shut-in (6 months) and production (12 months). The best practices in this study will provide valuable insights for similar CCUS projects in other unconventional fields. Furthermore, this study defines a term named “Carbon Neutrality Index (CNI)” by comparing the amount of CO2 stored with that burned by EOR oil. The CNI value of 0 indicates the enhanced oil is carbon neutral; a negative CNI value implies there is a net reduction in carbon emission. The 4-year huff-n-puff (HnP) simulation leads to a positive CNI value, indicating that the EOR oil generated in this process is not carbon neutral yet.

Property Preservation of Object-Oriented Petri Reduction Net Based Representation for Embedded Systems

Embedded systems are widely used in automotive electronics, smart home, smart medical, aerospace and other fields. Aiming at the problem of formal modeling and verification analysis of embedded systems, a solution is proposed using extended Petri net reduction operations. Petri net based representation for embedded system (PRES+) and the object-oriented technology are combined to obtain the object-oriented PRES+ (OOPRES+). Two kinds of subnet reduction rules of OOPRES+ are presented. The preservation of boundedness and liveness of the reduction net system has been investigated to alleviate the problem of state space explosion of OOPRES+. The modeling and analysis of the embedded control system of a smart restaurant is used as an example to verify the effectiveness of the subnet reduction rules. Results obtained can provide an effective way to examine the reduction property of Petri net systems, and present a powerful means to model and verify the large-scale complex embedded systems.

Electrified hydrocarbon-to-oxygenates coupled to hydrogen evolution for efficient greenhouse gas mitigation

Chemicals manufacture is among the top greenhouse gas contributors. More than half of the associated emissions are attributable to the sum of ammonia plus oxygenates such as methanol, ethylene glycol and terephthalic acid. Here we explore the impact of electrolyzer systems that couple electrically-powered anodic hydrocarbon-to-oxygenate conversion with cathodic H2 evolution reaction from water. We find that, once anodic hydrocarbon-to-oxygenate conversion is developed with high selectivities, greenhouse gas emissions associated with fossil-based NH3 and oxygenates manufacture can be reduced by up to 88%. We report that low-carbon electricity is not mandatory to enable a net reduction in greenhouse gas emissions: global chemical industry emissions can be reduced by up to 39% even with electricity having the carbon footprint per MWh available in the United States or China today. We conclude with considerations and recommendations for researchers who wish to embark on this research direction.

The carbon budget induced by water-level fluctuation in a typical shallow lake

Shallow lakes are characterized by strong water-level fluctuations, which control shifts in carbon (C) sources and sinks. However, there remains uncertainty in elucidating the alteration in the carbon budget with water-level changes. Here, carbon budget variation with water level was estimated by between carbon sequestration (Cs) and carbon emission (Ce) (including carbon dioxide, methane) using an improved logistic model and the DeNitrification-DeComposition (DNDC) model in Baiyangdian Lake (BYD), a typical shallow lake. According to the results, the Cs and Ce were 5.33 Tg/a and 1.72 Tg/a, respectively, which indicated that BYD acted as a carbon source (3.60 Tg/a net carbon emission). The spatial pattern and high value areas (HVA) of the carbon budget showed significant change with water depth variation under water level fluctuation. The HVA of Cs, Ce and Cnet in the BYD was distributed at water depths of -0.24±0.77 m, 2.41±0.50 m and 2.53±0.26 m, respectively. At the lake scale, increasing water level will increase the unevenness of the water depth contribution of Cs, with a higher variation coefficient of the contribution structure, while the impact on the Ce contribution is not significant. Furthermore, elevating the water level increases the contribution of Cs in HVA to the whole lake, while the effect of water level on Ce is characterized by segmentation. In combination with the goal of increasing sinks and reducing emissions and the feasibility of management operation, the water level threshold based on the net carbon emissions reduction can be more accurately identified with vegetation coverage demand.

Oxygen Dependent Temperature Regulation of Benthic Fluxes in Reservoirs

AbstractTemperature and dissolved oxygen concentration are critical factors affecting the exchange of solutes between sediment and water; both factors will be affected by warming of lakes and thereby influence water quality. Temperature and oxygen responses of single solute fluxes are well known; however, not much is known about the interaction of temperature and oxygen in regulating the balance of different fluxes in the benthic environment. We analyzed benthic flux (mobilization and immobilization) data of various solutes (dissolved organic carbon (DOC), CH4, NO3−‐N, NH4+‐N, SRP, SO4−, Fe, Mn, and O2) collected from laboratory incubations of 142 sediment cores from 5 different reservoirs incubated under varying in situ temperature and oxygen conditions. Oxygen was the primary driver of benthic fluxes, while temperature and total organic content were secondary. Temperature effects on benthic fluxes were stronger under anoxic conditions which imply that warming will substantially increase the benthic fluxes if the sediment surface becomes anoxic. The varying temperature response of processes underlying the studied fluxes will result in a shift of their relative importance in the benthic environment, especially in shallow lakes that are more vulnerable to warming. For example, more anoxic conditions will shift the equilibrium between net sulfate reduction and methane release toward the latter. We also predict that physical effects of warming leading to hypolimnetic oxygen depletion, that is, stronger stratification and longer hypolimnetic confinement will increase the benthic mobilization of phosphorus, DOC, and methane into water and immobilization of sulfate by the sediments even in deep lakes.

PD38-08 AVOIDING UNNECESSARY TARGETED PROSTATE BIOPSIES USING MACHINE LEARNING

You have accessJournal of UrologyCME1 Apr 2023PD38-08 AVOIDING UNNECESSARY TARGETED PROSTATE BIOPSIES USING MACHINE LEARNING Roxana Esmaili, Ghazal Khajir, Michael Leapman, Preston Sprenkle, Darryl Martin, and John Onofrey Roxana EsmailiRoxana Esmaili More articles by this author , Ghazal KhajirGhazal Khajir More articles by this author , Michael LeapmanMichael Leapman More articles by this author , Preston SprenklePreston Sprenkle More articles by this author , Darryl MartinDarryl Martin More articles by this author , and John OnofreyJohn Onofrey More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003336.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Magnetic resonance imaging (MRI)-targeted transrectal ultrasound (TRUS) guided needle biopsy is the current gold standard for diagnosing prostate cancer in patients with suspicion for prostate cancer. This leads to a frequent needle biopsy to determine the presence of clinically significant prostate cancer (csPCa) with a high rate of invasive overdiagnosis in patients with non-aggressive cancer. Supervised machine learning (ML) algorithms provide a mathematical framework to make predictions about csPCa in order to make personalized decisions to perform a biopsy or not and avoid unnecessary targeted needle biopsies. METHODS: From January 2016 to February 2020, 1099 patients underwent multiparametric MRI before TRUS fusion biopsy. We included PI-RADS score (version 2), gland volume, lesion region of interest volume before biopsy, PSA value, PSA density, and patient age at the time of biopsy as input variables to calculate the probability of csPCa for each lesion for each patient before biopsy using different ML classification algorithms: logistic regression (LR); random forest (RF); naïve Bayes (NB); and nearest neighbor (NN). Gleason Grade Group ≥2 was used as a reference for the presence of csPCa. Ten-fold cross-validation stratified over patients validated the ML approaches and compared to univariate models. RESULTS: Area under the receiver operating characteristic curves (AUC) and net reduction curves show that multivariate LR (AUC 81.3%) outperformed RF (AUC 79.2%), NN (AUC 71.8%) and NB (AUC 78.3%) and outperformed standard univariate LR using PSA density (AUC 71.4%) and PI-RADS (AUC 73.9%). The algorithms were evaluated at a point on the ROC curve for high sensitivity. Using the multivariate LR model, 636 (41.38%) targeted biopsies could have been avoided while missing only 90 (5.86%) csPCa, which is reasonable with a threshold probability of 25% and a net benefit of 0.21. CONCLUSIONS: Our findings suggest that multivariate ML models using clinical data can be used to avoid unnecessary targeted biopsy cores among patients with suspicion of prostate cancer undergoing prostate biopsy. Source of Funding: JAO supported by NIH R42 CA224888. DTM supported by DoD W81XWH-19-PCRP-IDA. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e996 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Roxana Esmaili More articles by this author Ghazal Khajir More articles by this author Michael Leapman More articles by this author Preston Sprenkle More articles by this author Darryl Martin More articles by this author John Onofrey More articles by this author Expand All Advertisement PDF downloadLoading ...

Performance of Residential Micro-CHP Operating in a District Energy Network

To resolve the problem of the imbalance between micro-Combined Heat and Power (m-CHP) supply and demand, a district energy network has been established based on residential m-CHP units powered by natural gas-fueled internal combustion engine. The electric and thermal loads of a Harbin residential building in a typical winter heating week are calculated. The performance of the m-CHP systems operating in two operation strategies, i.e., Following the Electric Load (FEL) and Following the Thermal Load (FTL), are analyzed and evaluated from both energy and economic aspects. The result shows that the energy cost of the m-CHP is reduced by 10% when operating in FTL mode, and the income from selling excess energy is 2.7 times more than that in FEL mode, indicating lower operation costs in FEL mode. Moreover, compared with the traditional separate production of electricity and heat, the net cost reduction rate of the system in FEL and FTL mode is 13.68% and 38.83%, respectively. Micro-CHP operating in a district energy network is more profitable than traditional separate electricity and heat production.

Reduced Tropical Climate Land Area Under Global Warming

AbstractRegions along the edges of the tropics host vast populations and ecosystems which are sensitive to climate change. Here we examine the extent of tropical land areas in the ERA5 and MERRA‐2 reanalyses and in high‐emission scenarios of 45 models participating in phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6). Based on the definition of tropical climate land areas as regions where the diurnal temperature range exceeds the seasonal temperature range, we find a net reduction of tropical land area with global warming. This change is primarily due to an increased seasonal temperature range driven by enhanced summer warming, which in turn is largely driven by reduced evaporative cooling. The reduction of tropical climate area is consistent with a narrowing of the tropical rain belt and with an equatorward and poleward expansion of the subtropical dry zones. Understanding the links between these trends requires further study.

Effects of casing cooling slot purge on heat transfer in turbine blade tip and casing

In recent years, heat transfer in turbine tips and casings has received extensive attention. To further improve heat transfer in the casing region, casing cooling slot purge is proposed as a strategy to effectively control the high heat load. In this study, the effects of different cooling groove geometries and aerodynamic parameters on the heat transfer coefficient and net heat load reduction of the blade tip and casing cooling efficiency are compared numerically when the outlet isentropic Ma is 0.96. The results show that the casing cooling slot purge can realize cooling of the casing, tip groove surface, and tip area of the suction surface. A better cooling effect could be obtained by reducing the coolant slot angle at the same flow rate. By increasing the coolant injection angle, the cooling efficiency of the casing and the inner surface of the groove is improved.

Towards the development of energy sharing methodology between different buildings for high efficient neighborhood design

Devising methods to recover waste heat and to share it within a neighborhood can lower the energy footprint of this neighborhood and reduce its dependence on the utility grids. This paper presents a novel methodology for capturing waste energy from individual buildings and sharing the recovered energy with an entire neighborhood. A survey of the current state of research on energy sharing is presented. A mixed-use neighborhood consisting of retail, residential, and greenhouse buildings is modeled to develop a holistic design of energy sharing strategy. Neighborhood-level waste heat recovery and distribution network is modeled in the EnergyPlus-DesignBuilder co-simulation platform. The energy sharing methodology is applied to different neighborhood configurations and neighborhood densities. The results show that with the application of energy sharing methodology integrated with energy efficient design and on-site solar energy, a net reduction of 74% energy in the mixed-use neighborhood is achieved compared to a design complying with the minimum requirement of the applicable energy codes. Similarly, a net 90.46% reduction in greenhouse gas (GHG) emissions is realized by energy sharing and on-site carbon capturing using neighborhood greenhouse.

Performance and ANN-based optimization of an advanced process for wet CO2-to-Methanol using a catalytic fluidized bed reactor integrated with separators

Large-scale green processes to produce methanol from massive industrial sources of CO2 with a certain amount of water are increasingly attractive for carbon neutralization. In this study, an advanced CO2-to-Methanol (CTM) process, consisting of a turbulent fluidized bed (TFB) reactor, separators, and other units, was developed, analyzed from start-up to steady state, and optimized for high-purity methanol production (98.5–99.9 wt%) from a wet CO2 source (1.3 MtCO2/year with 1.35 mol% H2O). A two-stage flash drum with direct feeding of wet CO2 into a flash drum was applied to the developed CTM process to remove water and enhance unconverted gas recovery. At a methanol purity of 99.9 wt%, the advanced CTM process increased the methanol yield (0.15–0.31%), production capacity (5700–10100 tMeOH/year), and net CO2 reduction (0.0009–0.0033 kgCO2/kgMeOH) but decreased production cost (3.7–7.4 $/tMeOH) compared to the conventional CTM process under various of reactor temperatures (478–538 K) and pressures (40–90 bar). During the start-up process, the CTM process indicated the peaks in the methanol molar fraction and flow rate as the TFB reactor performed the stable profile of solid temperature (548–553.75 K) and volume fraction (∼0.249). In the performance assessment, the main units (compressor, TFB reactor, and distillation column) accounted for 96, 95, and 82.5% of capital expenditure (CAPEX), operating expenditure (OPEX), and energy consumption, respectively. Meanwhile, lowering the price of the annual CO2 and H2 increased CAPEX and OPEX contributions from 10.92 (present) to 28.64% (in 2050). To optimize the process using an artificial neural network (ANN) model, three main objectives and four main operating variables were selected as features through data analysis. The ANN model precisely predicted process performances (>99% accuracy) could reduce the computational cost by 900-fold compared to the process simulation. For methanol purity of 98.5–99.9 wt%, the CTM process should be operated in the optimum domain with a reactor pressure of 57.18–75.74 bar, reactor temperature of 493.62–506.32 K, reflux ratio of 1.02–1.08, and reboiler ratio of 1.32–1.38. The results are useful for designing, operating, and decision-making processes for producing various grades of green methanol from wet CO2 sources.

Economic costs and environmental benefits of deploying CCUS supply chains at scale: Insights from the source–sink matching LCA–MILP approach

Carbon capture utilization and storage technology has been identified as a key solution for limiting the global temperature increase to 2 °C from preindustrial levels. In this study, we develop a source–sink matching mixed-integer linear programming model to obtain an optimal cost for the Carbon capture utilization and storage supply chain and evaluate the environmental benefits using life cycle assessment. Guangdong Province, China, with annual CO2 emissions of 585 Mt, is chosen as the case study for this paper. The results show that the deployment of the carbon capture utilization and storage supply chain follows a pattern of spreading from coastal to inland regions as the CO2 net reduction rate increases. Moreover, the unit cost of CO2 reduction increases with the CO2 reduction rate, specifically, from 237.81 Yuan per ton to 253.51 Yuan per ton as the CO2 reduction rate increases from 10% to 60%. The CO2-derived methanol is not economically viable, while having low implied carbon emissions, it has approximately 2.5 times the unit cost of traditional methanol. We recommend promoting carbon trading due to its effectiveness in reducing the unit abatement cost. Additionally, the carbon price level of 220 Yuan/t can achieve a profitable supply chain at various reduction rates. However, carbon labeling subsidies have little effect on reducing methanol production costs. The 95% confidence intervals for unit abatement costs obtained from Monte Carlo simulations can provide robust support for policymakers.

Abstract P6-01-39: The impact of the 21-gene Recurrence Score® assay upon physician treatment recommendations in the neoadjuvant setting in lymph node-negative breast cancer patients in a multicenter prospective study in Quebec

Abstract Background: Although the role of the 21-gene Breast Recurrence Score® assay is well established to predict response to adjuvant chemotherapy in the setting of node-negative hormone receptor (HR)-positive, HER2-negative breast cancers (BC), fewer studies have evaluated the assay in the neoadjuvant setting. Due to the correlation between a high Recurrence Score® (RS) result and pathological complete response (pCR), the Breast Recurrence Score assay has been used to aid in selecting between chemotherapy (CT) or endocrine therapy. We wanted to further understand the impact of the assay upon physician treatment recommendations and the use of chemotherapy in this patient cohort. Methods: We conducted a multicenter, prospective, observational study in patients with clinically node-negative HR-positive, HER2-negative BC with T2-T3 disease being considered for neoadjuvant therapy. Physicians were required to complete two questionnaires indicating treatment choice, including CT, endocrine therapy, or surgery, prior to and post availability of RS result. Patients were followed up for 6 months after commencement of neoadjuvant therapy. The primary objective was to evaluate the change in the physician’s recommendation for neoadjuvant CT prior to and post assay results. As a secondary objective, we also evaluated the impact of the RS result on physician’s expressed level of confidence. Results: A total of 70 patients were enrolled between April 2018 and November 2021 at five hospital centers, as part of the McPeak Sirois Group of Quebec. The median age of the cohort was 60 years (range, 30 to 79 years). 24.3 % (n=17) of the cohort consisted of patients aged < 50 years, and 75.7% (n=53) were ≥ to 50 years. 29.0% (n=20) of the patients had a RS < 16, 39.1% (n=27) had a RS between 16-25, and 31.9% (n=22) had a RS > 25. For the entire cohort, the RS result led to a net reduction in chemotherapy recommendation by 33.3% (OR (odds of having CT post-RS recommendation versus pre-RS recommendation) = 0.23 [95% CI: 0.12-0.44]; P< 0.0001), and 39.2% net reduction in the use of chemotherapy at 6-month follow-up (OR = 0.18 [95% CI: 0.09-0.35]; P< 0.0001). Furthermore, the RS result led to a 35.3% net reduction in physician recommendation of CT for patients < 50 years (OR = 0.19 [95% CI: 0.04-0.83]; P=0.027) and a 32.7% net reduction for patients ≥ 50 years (OR = 0.24 [95% CI: 0.11-0.50]; P=0.0001). For patients with a RS < 16, there was a reduction in CT recommendation by 75.0%, and by 44.4% for patients with a RS between 16 - 25 (OR = 0.15 [95% CI: 0.06-0.38]; P< 0.0001). Moreover, RS results led to an increase in confidence in physician treatment decisions for 59.4% of patients (OR = 12.53 [95% CI: 5.46-28.78]; P< 0.0001). Conclusion: We determined that the 21-gene Breast Recurrence Score assay altered neoadjuvant treatment decisions, leading to a reduction in the use of chemotherapy by about one-third, regardless of age. Additionally, the assay increased physician confidence in their treatment recommendation for about 60% of patients. This demonstrates the potential clinical utility of the assay to decrease the use of CT in the neoadjuvant setting amongst HR-positive, node-negative BC patients in Quebec. Citation Format: Mariya Yordanova, Lucas Sideris, Pierre Dubé, Jean-Francois Boileau, Julie Lemieux, Catalin Mihalcioiu, Sylvie Levesque, Marie-Claude Guertin, Erica Patocskai, Rami Younan, André Robidoux, Saima Hassan. The impact of the 21-gene Recurrence Score® assay upon physician treatment recommendations in the neoadjuvant setting in lymph node-negative breast cancer patients in a multicenter prospective study in Quebec [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-01-39.

Numerical Evaluation on Effects of Upstream Sand-Dune-Shaped Ramp and Backward Coolant Injection on Heat Transfer

Numerical simulations are performed for the forward and backward injection film cooling with the presence of upstream ramp under three typical blowing ratios of 0.5, 1.0 and 1.5. Totally nine film cooling configurations are taken into considerations in the current study, where two ramps (straight-wedge-shaped ramp (SWR) and sand-dune-shaped ramp (SDR)), two coolant injection modes (forward injection (FW) and backward injection (BW)), and two film-hole shapes (cylindrical hole (CH) and fan-shaped hole (FH)) are involved. From the current study, the effects of coolant injection scheme and upstream ramp on the film cooling performance are evaluated in the viewing of the heat transfer. Based on the numerical results, it is demonstrated that a wide high net heat flux reduction (NHFR) zone is created in the forward injection cases at M(the blowing ratio)=0.5, but it is shrunk or disappeared rapidly at M=1.5, except the FH-FW-SDR case. While for the backward injection case, two high heat flux reduction zones are generated around the hole exit where the separate bubbles locate, and it remains even at M=1.5. Among the current cases, the FH-FW-SDR is demonstrated to be the best one for achieving the highest NHFR under the all three blowing ratios. With regard to the coolant injection scheme, its influence on heat transfer coefficient is more complicated, tightly associated with the blowing ratio, film-hole shape and the upstream ramp.

Peer-to-Peer Energy Trading for Residential Prosumers With Photovoltaic and Battery Storage Systems

The popularization of solar generation enables residential households to supply their loads and trade the surplus energy through residential peer-to-peer (P2P) energy trading market. Facing the increasing complexity of the market structure and decision-making strategies, this article proposes a P2P energy trading model for residential households, and the objective is to help the centralized market coordinator optimize the benefit of participants under such a P2P market. To this end, a new mathematical model, including the rules for buying and selling energy, is presented. In this model, a supply function bidding mechanism is formulated to match the power supply imbalance and calculate the market-clearing price. An optimization problem is formulated to identify the optimal strategies for energy buying and selling, which consists of two parts: the first part is to maximize the social welfare; the second part is to minimize the unfair benefit distribution that participants can gain through P2P energy trading. The case study based on the real data for four different household categories has revealed that households can achieve 26.38% net cost reduction, and the proposed fair benefit distribution function also can fairly allocate the benefit by enforcing households' benefit variance indexes at a low level.