Communicating about Contaminated Site Cleanup using Coordinated and Consistent Metrics: Opportunity and Challenge for the U.S. Department of Energy
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Mathematical Methods In Social Sciences↗
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Experimental determination of electron attenuation lengths in complex materials by means of epitaxial film growth: advantages and challenges
Accurate electron attenuation lengths are of critical importance in using electron spectroscopic methods to quantitatively characterize complex materials. Here we show that analysis of core-level and valence-band x-ray photoelectron spectra excited with monochromatic AlK? x-rays from the substrate and measured as a function of film thickness can be used to determine electron attenuation lengths in epitaxial SrTiO3 films on Ge(001). Closely lattice-matched epitaxial heterojunctions are ideal systems for determining attenuation lengths provided the films grow in a layer-by-layer fashion, leading to atomically flat surfaces, and the buried interfaces are atomically abrupt. In principle, either the rate of attenuation of substrate peak intensities or the rate of increase of film peak intensities can be used for this purpose. However, we find that structural nonuniformities in the films reduce the accuracy of electron attenuation lengths determined from photoelectrons that originate within the films. A more reliable source of information is found in photoelectrons from the substrate which traverse the film. By using the energy dependence of calculated electron attenuation lengths from the NIST database in combination with Ge 3d core and Ge-derived valence band intensities, we determine electron attenuation length as a function of kinetic energy for SrTiO3.
Chambers, Scott A.↗
Challenges and Optimization of Mu2e Proton Target Design with Radiative Cooling
Mu2e, the Muon-to-Electron Conversion Experiment, aims to identify physics beyond the Standard Model, namely, the conversion of muons to electrons without the emission of neutrinos. The muons are produced from pions generated in a production target when it is hit by an 8 GeV proton beam from the Fermilab Booster/Main Injector. The proton target design space is strongly constrained by a one-year operating lifetime and the need for radiative cooling in a vacuum environment. Uncertainties in the lifetime of the existing baseline design – a monolithic, segmented tungsten target – are large, particularly due to unknown impacts of radiation damage at the very high proton fluences expected in the experiment. We have begun evaluation of a new design utilizing Inconel 718 over the WL10 used in the existing target design. As a result, the structural design of the target has evolved significantly. This evolution focuses on lowering the target temperature, minimizing obstruction to muons, increasing structural stability, maximizing fatigue lifetime, simplifying the fabrication process, and more. The thermal management, structural stability and fatigue lifetime are emphasized here. These optimizations have led to a promising new target design for the Mu2e experiment.
Liu, Z. [Fermilab]↗
Sandia Mechanics Challenge: Determining Mechanical Performance and Model Calibration Inputs for the Challenge Material and Fasteners
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Kramer, Sharlotte LorraineBolyard↗
CFD2030 ? Aerospace Grand Challenges for Revolutionary CFD Capabilities: A DOE Perspective on Hypersonics Grand Challenges.
Abstract not provided.
Howard, Micah↗
ARPA-E Grid Optimization (GO) Competition Challenge 2
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment. Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. Specifically, the economic surplus, defined as the benefit of serving load minus the cost of generation, is being maximized. It was expected that the objective value of a given solution should be positive, representing economic gain, but negative objectives from poor solutions were possible. The two code submission feature of Challenge 1 was maintained. Additionally, Divisions 3 and 4 within the competition permitted on/off switching of transmission lines (Divisions 1 and 2 did not). After the initial release of the Problem Formulation on 7/20/2020, ARPA-E Director Lane Genatowski announced Challenge 2 on 9/12/2020. The final May 31, 2021, version of the Problem Formulation was 97 pages long with 299 equations. The Challenge proceeded with 2 non-prize Events and 2 prize Events. Teams receiving Challenge 1 FOA awards and prize money were required to use the prize money to fund their Challenge 2 efforts (Georgia Institute of Technology, Global Optimal Technology, Inc., Lawrence Livermore National Laboratory, Lehigh University, Northwestern University, Artelys, Columbia, Pearl Street Technologies, Pennsylvania State University, and University of Colorado Boulder). For more information on the competition and challenge 2 see the "GO Competition Challenge 2 Information" resource below. Challenge 1 and Challenge 3 information can be found in the resources linked below.
ACOPF↗
Ability to Simulate Absorption and Melt Pool Dynamics for Laser Melting of Bare Aluminum Plate: Results and Insights from the 2022 Asynchronous AM-Bench Challenge
The 2022 Asynchronous AM-Bench challenge was designed to test the ability of simulations to accurately predict laser power absorption as well as various melt pool behaviors (width, depth, and solidification) during laser melting of solid metal during stationary and scanned laser illumination. In this challenge, participants were asked to predict a series of experimental outcomes. Experimental data were obtained from a series of experiments performed at the Advanced Photon Source at Argonne National Laboratories in 2019. These experiments combined integrating sphere radiometry with high-speed X-ray imaging, allowing for the simultaneous recording of absolute laser power absorption and two-dimensional, projected images of the melt pool. All challenge problems were based on experiments using bare aluminum solid metal. Participants were provided with pertinent experimental information like laser power, scan speed, laser spot size, and material composition. Additionally, participants were given absorptance and X-ray imaging data from stationary and scanned laser experiments on solid Ti–6Al–4V that could be used for testing their models before attempting challenge problems. In total, this challenge received 56 submissions from eight different research groups for eight individual challenge problems. The data for this challenge, and associated information, are available for download from the NIST Public Data Repository. This paper summarizes the results from the 2022 Asynchronous AM-Bench challenge as well as discusses the lessons learned to help inform future challenges.
36 MATERIALS SCIENCE↗
Revisiting the Terawatt Challenge
Richard E. Smalley, in 2003, defined the Terawatt (TW) Challenge as “Adapting our energy infrastructure to simultaneously address diminishing oil resources and rising levels of atmospheric CO 2 .” Smalley, best known for the discovery of C 60 , for which he received the 1996 Nobel Prize in Chemistry, continued to address the challenges of anthropomorphic and natural global energy flows until he passed away in 2005. Smalley challenged the world to transform the energy sector. He envisioned electricity transmitted by high-voltage direct current (DC) lines from massively deployed solar plants in sunny areas and remotely sited nuclear plants. He also envisioned using advanced batteries for local storage of energy. To meet the needs of ~10 people in a world with a dwindling oil supply, Smalley asserted that the world would need to transform its fossil-fuel-driven 14-TW (average power) energy used in 2003 to a largely renewable-energy-driven 30–60 TW (average power) in 2050. This would be possible only if solar-electricity costs could be drastically reduced. The challenges associated with this transition have been called the “Terawatt Challenge.” Fifteen years later, solar-module costs have been reduced by tenfold and annual deployment of solar photovoltaic (PV) modules has grown by a factor of 100,from ~1 gigawatt (GW) in 2004 to ~100 GW in 2018, with a total of 500 GW installed worldwide, producing 2% of the planet’s electricity. As global installed solar generating capacity approaches1 TW, we revisit Smalley’s TW challenge to identify what has changed and quantify the TW Challenge for a baseline scenario and for two scenarios designed as upper and lower bounds determined by the degree we implement electrification and storage. In this paper, we show that the energy choices we make today will dramatically affect the magnitude of future global energy requirements.
SOLAR ENERGY↗
ARPA-E Grid Optimization (GO) Competition Challenge 3
Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023). For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.
ACOPF↗
ARPA-E Grid Optimization (GO) Competition Challenge 1
The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each dataset consisted of a collection of power system network models of different sizes with associated operating scenarios (snapshots in time defining instantaneous power demand, renewable generation, generator and line availability, etc.). The datasets were of two types: Real-Time, which included starting-point information, and Online, which did not. Week-Ahead data is also provided for some cases but was not used in the Competition. Although most datasets were synthetic and generated by GRIDDATA, a few came from industry and were only used in the Final Event. All synthetic Input Data and Team Results for the GO Competition Challenge 1 for the Sandbox, Trial Events 1 to 3, and the Final Event along with problem, format, scoring and rules descriptions are available here. Data for industry scenarios will not be made public. Challenge 1, a minimization problem, required two computational steps. Solver 1 or Code 1 solved the base SCOPF problem under a strict wall clock time limit, as would be the case in industry, and reported the base case operating point as output, which was used to compute the Objective Function value that was used as the scenario score. The feasibility of the solution was provided by the Solver 2 or Code 2, which solves the power flow problem for all contingencies based on the results from Solver 1. This is not normally done in industry, so the time limits were relaxed. In fact, there were no time limits for Trial Event 1. This proved to be a mistake, with some codes running for more than 90 hours, and a time limit of 2 seconds per contingency was imposed for all other events. Entrants were free to use their own Solver 2 or use an open-source version provided by the Competition. Containers, such as Docker, were considered to improve the portability of codes, but none that could reliably support a multi-node parallel computing environment, e.g., MPI, could be found. For more information on the competition and challenge see the "GO Competition Challenge 1 Information" and "GO Competition Challenge 1 Additional Information" resources below.
ACOPF↗
Computationally Selected Multivalent HIV-1 Subtype C Vaccine Protects Against Heterologous SHIV Challenge
Background: The RV144 trial in Thailand is the only HIV-1 vaccine efficacy trial to date to demonstrate any efficacy. Genetic signatures suggested that antibodies targeting the variable loop 2 (V2) of the HIV-1 envelope played an important protective role. The ALVAC prime and protein boost follow-up trial in southern Africa (HVTN702) failed to show any efficacy. One hypothesis for this is the greater diversity of subtype C viruses in southern Africa relative to CRF01_AE in Thailand. Methods: Here, we determined whether an ALVAC prime with computationally selected gp120 boost immunogens maximizing coverage of diversity of subtype C viruses in the variable V1 and V2 regions (V1V2) improved the protection of non-human primates (NHPs) from a heterologous subtype C SHIV challenge compared to more traditional regimens. Results: An ALVAC prime with Trivalent subtype C gp120 boosts resulted in statistically significant protection from repeated intrarectal SHIV challenges compared to the control. Evaluation of the immunogenicity of each vaccine regimen at the time of challenge demonstrated that different gp120 combination boosts elicited similar high magnitudes of gp120 and breadth of V1V2-binding antibodies, as well as strong Fc-mediated immune responses. Low-to-no neutralization of the challenge virus was detected. A Cox proportional hazard analysis of five pre-selected immune parameters at the time of challenge identified ADCC against the challenge envelope as a correlate of protection. Systems serology analysis revealed that immune responses elicited by the different vaccine regimens were distinct and identified further correlates of resistance to infection. Conclusions: Computationally designed vaccines with maximized subtype C V1V2 coverage mediated protection of NHPs from a heterologous Tier-2 subtype C SHIV challenge.
Immunology↗
DOE Cold Climate Heat Pump Challenge: Development, Metrics, and Early Field Observations
Space heating in residential buildings is a major contributor of Greenhouse Gas (GHG) emissions in the United States. New, advanced electric heat pumps are poised to provide a low carbon alternative to traditional fossil-based heating, especially in colder climates. Widespread deployment of cold climate heat pumps could help address the significant portion of building emissions and primary energy used in American households, but these gains will require broader acceptance from consumers and decision makers. As part of the “Energy, Emissions, and Equity” (E3) initiative, the U.S. Department of Energy launched the Cold Climate Heat Pump Challenge (CCHP) in 2021 to accelerate the deployment of the next generation of air source heat pumps. The Challenge is currently focused on residential, centrally ducted, electric heat pumps, with a nominal cooling capacity greater than or equal to 24,000 Btu/h (2 tons) and less than or equal to 65,000 Btu/h (5 tons). The Challenge specifications represent a best-in-class heat pump product that provides high-efficiency heating performance in cold climates, employs environmentally friendly low-Global Warming Potential (GWP) refrigerants, and is designed to be grid interactive. Spearheaded by DOE in partnership with the US Environmental Protection Agency (EPA) and Natural Resources Canada (NRCan), the CCHP Challenge brings together numerous major heat pump manufacturers and key stakeholders including utilities and state agencies across the country. In addition to performance testing in a laboratory environment, a key component of this research is evaluating the in-field performance of the prototype heat pumps developed as part of the Challenge. This paper will discuss the development of the CCHP Challenge, key performance specifications, and the energy and non-energy metrics that will be evaluated through the field study. The types of data that are being collected from the units installed in homes across North America as part of the field validation will be described, including details about the sensors and data acquisition system. Data cleaning and analysis methodologies will be discussed, along with early observations from the winter 2022-2023, spring and summer performance periods, and an assessment of non-energy metrics through pre- and post-installation homeowner surveys. Challenges uncovered and lessons learned throughout the process will also be discussed. Finally, the paper will discuss next steps for the second winter assessment period, areas needing additional research, and potential applications of the data collected and analyzed through this work.
Mendon, Vrushali V.↗
Sustainable Aviation Fuel Grand Challenge: Tracking Metrics and Mid-2024 Dashboard
The Sustainable Aviation Fuel Grand Challenge is the result of the U.S. Department of Energy, the U.S. Department of Transportation, the U.S. Department of Agriculture, and other federal government agencies working together to develop a comprehensive strategy for scaling up new technologies to produce sustainable aviation fuels (SAF) on a commercial scale. The SAF Grand Challenge Roadmap outlines a whole-of-government approach with coordinated policies and specific activities that should be undertaken to achieve the SAF Grand Challenge goals. Progress made supporting the SAF Grand Challenge occurs when federal agencies release new funding opportunities and initiatives aligned with the SAF Grand Challenge Roadmap; provide expertise and technical assistance to industry; increase interagency collaboration; and provide data, modeling, and analysis to decision makers. To track progress on achieving the SAF Grand Challenge goals, the following four metrics have been developed: Estimated total U.S. SAF production. Estimated life cycle CO2 equivalent reductions achieved with U.S. SAF production and use. Planned production potential of SAF in the United States. Applicable research, development, demonstration, and deployment projects. SAF Grand Challenge Goal Progress
Aviation↗
The 200 Gbps Challenge: Imagining HL-LHC analysis facilities
The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Why Is It So Challenging to Measure Residual Stresses ?
Abstract Background Residual stresses have a “hidden” character because they exist in a material without the presence of any external loads. They cannot easily be added or subtracted in a quantified manner, as is done when measuring applied stresses, and so are much more challenging to measure. Objective The objective here is to identify and describe the various features that make residual stress measurement methods challenging and to consider the ways that these challenges can be addressed in practice. Methods Various of the most common residual stress measurements methods are considered and the challenges associated with them are identified and classified. Results Five major challenges for residual stress measurements, and the approaches used for their resolution, are identified. Conclusions Despite the various challenges that need to be overcome, residual stress measurements can be successfully undertaken in practice. The most significant feature for success is a highly skilled and knowledge practitioner.
36 MATERIALS SCIENCE↗
Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics
Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.
Radiology, Nuclear Medicine & Medical Imaging↗
The effects of xylo-oligosaccharides on regulating growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids profile in Eimeria-challenged broiler chickens
A 21-d experiment was conducted to investigate the effects of xylo-oligosaccharides (XOS) on growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids (SCFA) profile of broiler chickens challenged with mixed Eimeria spp. Two hundred fifty-two zero-day-old chicks were allocated to 6 treatments in a 3 £ 2 factorial arrangement (corn-soybean meal diets supplemented with 0, 0.5, or 1.0 g/kg XOS; with or without Eimeria challenge). Challenged groups were inoculated with a solution containing E. maxima, E. acervulina, and E. tenella oocysts on d 15. During the infection period (d 15 to d 21), there was a significant (P < 0.05) Eimeria £ XOS interaction for weight gain (WG). XOS significantly (P < 0.05) increased WG in the unchallenged birds but not in the challenged treatments. There was no significant Eimeria £ XOS interaction for N and minerals utilization responses. XOS supplementation at 0.5 g/kg tended to alleviate Eimeria-induced depression in apparent ileal digestibility of DM (P = 0.052). Challenged birds had lower (P < 0.01) AME, AMEn, and total retention of N, Ca, and P. Eimeria upregulated (P < 0.01) gene expression of tight junction proteins claudin-1, junctional adhesion molecule-2, and glucose transporter GLUT1; but downregulated (P < 0.01) the peptide transporter PepT1, amino acid transporters rBAT, CAT2, y+LAT2, and zinc transporter ZnT1. XOS alleviated (P < 0.05) Eimeria-induced claudin-1 upregulation. Eimeria decreased (P < 0.05) cecal saccharolytic SCFA acetate, butyrate, and total SCFA, but increased (P < 0.05) branched chain fatty acids isobutyrate and isovalerate. The supplementation of XOS tended to decrease the concentration of isobutyrate (P = 0.08) and isovalerate (P = 0.062). In conclusion, 0.5 g/kg XOS supplementation alleviated depression in growth performance and nutrient utilization from the Eimeria challenge. In addition, supplemental XOS reversed the gene expression changes of claudin-1, also showed the potentials of alleviating the negative cecal fermentation pattern induced by Eimeria infection.
60 APPLIED LIFE SCIENCES↗
The effects of protease, xylanase, and xylo-oligosaccharides on growth performance, nutrient utilization, short-chain fatty acids, and microbiota in Eimeria -challenged broiler chickens fed low-protein diet
A total of 392 Cobb 500 off-sex male broiler chicks were used in a 21-day experiment to study the effect of protease, xylanase, and xylo-oligosaccharides (XOS) on improving growth performance, nutrient utilization (ileal digestibility and total tract retention), gene expression of nutrient transporters, cecal short-chain fatty acids (SCFAs), and microbiota profile of broilers challenged with Eimeria spp. Chicks at 0-day old were allocated to 8 treatments in a 4 × 2 factorial arrangement: 1) corn-soybean meal diet with no enzyme (Con); 2) Con plus 0.2 g/kg protease alone (PRO); 3) Con plus 0.2 g/kg protease combined with 0.1 g/kg xylanase (PRO + XYL); or 4) Con plus 0.5 g/kg xylo-oligosaccharides (XOS); with or without Eimeria challenge. The 4 diets were formulated to be marginally low in crude protein (183 g/kg). Challenged groups were inoculated with a solution containing E. maxima, E. acervulina, and E. tenella oocysts on d 15. Eimeria depressed (P < 0.01) growth performance and nutrient utilization. Supplemental protease improved (P < 0.05) body weight gain and feed intake in the prechallenge phase (d 0-15) but had no effect during the infection period (d 15-21). There was no interaction between infection and feed supplementation for nutrient utilization. The supplementations of either PRO or XOS alone increased (P < 0.01) total tract retention of Ca and tended (P < 0.1) to improve total tract retention of N, P, AME, and AMEn. Eimeria decreased (P < 0.05) expressions of GLUT2, GLUT5, PepT1, ATP2B1, CaSR, Calbidin D28K, NPT2, and ZnT1 but increased (P < 0.01) expression of GLUT1. XOS supplementation increased (P < 0.05) ATP2B1 expression. Protease decreased (P < 0.05) isobutyrate concentration in unchallenged treatments but not in challenged treatments. Eimeria decreased (P < 0.01) cecal saccharolytic SCFAs acetate and propionate but increased (P < 0.01) branched-chain fatty acid isovalerate. The supplementation of PRO + XYL or XOS increased (P < 0.05) cecal butyrate or decreased cecal isobutyrate concentrations, respectively. PRO + XYL and XOS decreased cecal protein levels in unchallenged birds but not challenged ones. Eimeria challenge significantly (P < 0.05) decreased the microbial richness (Observed features) and diversity (Shannon index and phylogenetic diversity) and changed the microbial composition by reducing the abundance of certain bacteria, such as Ruminococcus torques, and increasing the abundance of others, such as Anaerostipes. In contrast, none of the additives had any significant effect on the cecal microbial composition. In conclusion, PRO or XOS supplementation individually improved nutrient utilization. All the additives decreased the cecal content of branched-chain fatty acids, consistent with decreased cecal N concentration, although the effects were more pronounced in unchallenged birds. In addition, none of the feed additives impacted the Eimeria-induced microbial perturbation.
60 APPLIED LIFE SCIENCES↗