SPARCS Data Management
Presentation on data import/export and data conversion using SPARCS-M and SPARCS-A applications.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Optimizing feed modulation for coupled methane and NO x conversion over Pd-Pt/Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith catalyst
Here the impacts of feed modulation (frequency, amplitude) and catalyst design (composition and architecture) parameters are reported for the conversion of methane and NO x over a dual-layer Pt+Pd/Al 2 O 3 + Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith. CH 4 and NO x conversion data show that the dual-layer catalyst outperforms single-layer samples having the same catalyst loadings, with and without spinel. Close proximity of the PGM and MFO functions in the mixed-layer catalyst lowers the CH 4 conversion at high temperature while separating the PGM and spinel layers with an intermediate Al 2 O 3 layer does not. Methane conversion enhancement is linked to its nonmonotonic dependence on O 2 . The performance gains are tied to a transient activity spike that occurs during the lean-to-rich feed transition when water is present in the feed. The transient spike is attributed to the removal of CO and H 2 products via reactions with stored O 2 in the spinel, eliminating inhibition of methane steam reforming.
03 NATURAL GAS↗
Heterojunction bipolar transistor technology for data acquisition and communication
Heterojunction Bipolar Transistor (HBT) technology has emerged as one of the most promising technologies for ultrahigh-speed integrated circuits. HBT circuits for digital and analog applications, data conversion, and power amplification have been realized, with speed performance well above 20 GHz. At Rockwell, a baseline AlGaAs/GaAs HBT technology has been established in a manufacturing facility. This paper describes the HBT technology, transistor characteristics, and HBT circuits for data acquisition and communication.
Wang, C.↗
Multi-scale simulation of reaction, transport and deactivation in a SBA-16 supported catalyst for the conversion of ethanol to butadiene
Effective design of heterogeneous catalytic systems requires careful coordination of physiochemical phenomena that span orders or magnitude in length and time scales. Multiscale modelling and simulation tools can provide useful insight for understanding and improving the performance of such systems. Mesoporous silica catalyst support materials present a versatile platform wherein support attributes may be tuned to control transport phenomena throughout the system. In this study we develop an integrated multiscale modelling approach for the conversion of ethanol to butadiene over a SBA-16 mesoporous silica supported catalyst. We use molecular dynamics simulations to calculate domain specific diffusivities of reactants and products in the various domains of SBA-16's nanostructure. This is used to calculate a resultant effective diffusivity through its microstructure using finite element method (FEM) models of the tessellated unit cell. The resultant intraparticle effective diffusivity enables the development of a reduced-order reactor level FEM model that is able to implicitly account for the SBA-16's transport effects without the explicit consideration of its detailed geometry. Experimental bench-scale conversion data for the ethanol to butadiene process over SBA-16 is used to extract intrinsic kinetic rate constants for a simplified reaction mechanism using this reduced order bench-scale reactor FEM model. The model is able to reproduce experimental trends in conversion and activity lifetimes. The impact of varying key support attributes such as pore-size and particle size on catalytic activity lifetimes is then explored. We demonstrate the utility of this multi-scale modelling strategy in guiding catalyst design for the development of rational strategies to improve the performance of heterogeneous supported catalytic systems.
09 BIOMASS FUELS↗
Characterized Variability of Biomass Feedstocks using The Idaho National Lab Bioenergy Feedstock Library
In order to achieve the Bioenergy Technology Office Goals of acquiring a billion tons of feedstock material that meets the physical, chemical, and cost requirements for conversion to fuel by 2030, research into understanding the overall causes of compositional, physical and conversion variability for the wide number of available biomass feedstock resources is necessary. One strategy for accomplishing this is the innovative knowledge-based management system currently being developed and maintained at Idaho National Laboratory (INL) known as the Bioenergy Feedstock Library (www.bioenergylibrary.inl.gov). The library currently has harvest, storage and logistic, analytical characterization, and/or conversion data for over 35,000 samples spanning 90 different feedstock types, 38 states, and 3 countries. These samples and data have been provided not only by the INL but from over 100 collaborating universities, feedstock supplier, national labs, and industrial partners. Of the 35,000 samples, 2300 have been characterized by one or more analytical processes including the compositional, proximate, ultimate, elemental ash, physical and conversion analyses. This presentation will demonstrate the significant research into the national understanding of biomass feedstock variability made possible by the continually updated contributions to the library that have historically only been available in the few published review papers regarding feedstock variability. Also, the benefits of contributing to this database, the analytical tools available, and the future prospects that this tool can provide research supporting sustainable and renewable energy will be presented.
09 BIOMASS FUELS↗
Evaluation of Advanced Signal Processing Techniques to Improve Detection and Identification of Embedded Defects
By the end of 1996, 109 Nuclear Power Plants were operating in the United States, producing 22% of the Nation’s electricity [1]. At present, more than two thirds of these power plants are more than 40 years old. The purpose of the U.S. Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) Program is to develop technologies and other solutions that can improve the reliability, sustain the safety, and extend the operating lifetimes of nuclear power plants (NPPs) beyond 60 years [2]. The most important safety structures in an NPP are constructed of concrete. The structures generally do not allow for destructive evaluation and access is limited to one side of the concrete element. Therefore, there is a need for techniques and technologies that can assess the internal health of complex, reinforced concrete structures nondestructively. Previously, we documented the challenges associated with Non-Destructive Evaluation (NDE) of thick, reinforced concrete sections and prioritized conceptual designs of specimens that could be fabricated to represent NPP concrete structures [3]. Consequently, a 7 feet tall, by 7 feet wide, by 3 feet and 4-inch-thick concrete specimen was constructed with 2.257-inch-and 1-inch-diameter rebar every 6 to 12 inches. In addition, defects were embedded the specimen to assess the performance of existing and future NDE techniques. The defects were designed to give a mix of realistic and controlled defects for assessment of the necessary measures needed to overcome the challenges with more heavily reinforced concrete structures. Information on the embedded defects is documented in [4]. We also documented the superiority of Frequency Banded Decomposition (FBD) Synthetic Aperture Focusing Technique (SAFT) over conventional SAFT when probing defects under deep concrete cover. Improvements include seeing an intensity corresponding to a defect that is either not visible at all in regular, full frequency content SAFT, or an improvement in contrast over conventional SAFT reconstructed images. This report documents our efforts in four fronts: 1) Comparative study between traditional SAFT and FBD SAFT for concrete specimen with and without Alkali-Silica Reaction (ASR) damage, 2) improvement of our Model-Based Iterative Reconstruction (MBIR) for thick reinforced concrete [5], 3) development of a universal framework for sharing, reconstruction, and visualization of ultrasound NDE datasets, and 4) application of machine learning techniques for automated detection of ASR inside concrete. Our comparative study between FBD and traditional SAFT reconstruction images shows a clear difference between images of ASR and non-ASR specimens. In particular, the left first harmonic shows an increased contrast and sensitivity to ASR damage. For MBIR, we show the superiority of model-based techniques over delay and sum techniques such as SAFT. Improvements include elimination of artifacts caused by direct arrival signals, and increased contrast and Signal to Noise Ratio. For the universal framework, we document a format for data storage based on the HDF5 file format, and also propose a modular Graphic User Interface (GUI) for easy customization of data conversion, reconstruction, and visualization routines. Finally, two techniques for ASR automated detection are presented. The first technique is based on an analysis of the frequency content using Hilbert Transform Indicator (HTI) and the second technique employees Artificial Neural Network (ANN) techniques for training and classification of ultrasound data as ASR or non-ASR damaged classes. The ANN technique shows great potential with classification accuracy above 95%. These approaches are extensible to the detection of additional reinforced, thick concrete defects and damage.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DSN Beowulf Cluster-Based VLBI Correlator
The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database used to delegate parallel tasks between nodes and storage areas (see Figure 2). This script forks into three processes: extract, translate, and correlate. Each of these processes iterates on available scan data and updates the status database as the work for each scan is completed. The extract process coordinates and monitors the transfer of data from each of the Mark5s to the Beowulf RAID storage systems. The translate process monitors and executes the data conversion processes on available scan files, and writes the translated files to the slave nodes. The correlate process monitors the execution of SoftC correlation processes on the slave nodes for scans that have completed translation. A comparison of the JVC and the legacy Block II correlator outputs reveals they are well within a formal error, and that the data are comparable with respect to their use in flight navigation. The processing speed of the JVC is improved over the Block II correlator by a factor of 4, largely due to the elimination of the reel-to-reel tape drives used in the Block II correlator.
Rogstad, Stephen P.↗
Noise measurements in a free-jet, flight simulation facility - Shear layer refraction and facility-to-flight corrections
The conversion of free-jet facility into equivalent flyover results is discussed. The essential problem is to 'calibrate out' the acoustic influence of the outer free-jet shear layer on the measurement, since this is absent in the flight case. Results are presented which illustrate the differences between current simplified models (vortex-sheet and geometric acoustics), and a more complete model based on the Lilley equation. Finally, the use of geometric acoustics for facility-to-flight data conversion is discussed.
Morfey, C. L.↗
Optimization Of Ocean Color Algorithms: Application To Satellite And In Situ Data Merging
The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project (McClain et al., 1995). The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage (Gregg et al., 1998; Gregg & Woodward, 1998). The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global ocean the merging of ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program (see e.g. Kwiatkowska & Fargion, 2003, Franz et al., 2003). As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized waterleaving radiances (LwN( )) from single or multiple sensors and uses them in the inversion of a semianalytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the LwN( ) data and, 4) it provides uncertainty estimates for the retrieved variables.
Maritorena, Stephane↗
Optimization of Ocean Color Algorithms: Application to Satellite Data Merging
The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project. The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage. The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global Ocean the merging of Ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances (L(sub WN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the (L(sub WN)(lambda)) data and, 4) it provides uncertainty estimates for the retrieved variables.
Maritorena, Stephane↗
Optimization of Ocean Color Algorithms: Application to Satellite Data Merging
The objective of the program is to develop and validate a procedure for ocean color data merging, which is one of the major goals of the SIMBIOS project. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances L((sub wN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) It works with single or multiple data sources regardless of their specific bands; 2) It exploits band redundancies and band differences; 3) It accounts for uncertainties in the L((sub wN)(lambda)) data; 4) It provides uncertainty estimates for the retrieved variables.
Ritorena, Stephane↗
Solar Bankability Data to Advance Transactions and Access (SB-DATA) Final Technical Report
The DOE project “Solar Bankability Data to Advance Transactions and Access”, known in the solar industry and referred to in this report as “Orange Button”, had project objectives of convening key stakeholder participants in the solar project lifecycle to develop a data taxonomy that meets to the solar industry’s needs for standardized data types for use in solar projects. Additional Orange Button deliverables included the development of an online data exchange to act as a clearinghouse of data that conformed to the data standard and additional solar industry data, and a Solar Data Translation Platform that could transform legacy solar project data to conform to the Orange Button data standard. All of these objectives were achieved. The Smart Electric Power Alliance (SEPA) provided program management, industry participant recruiting and convening, worked with the solar industry to define the scope of the Orange Button data taxonomy, and documented and delivered the taxonomy data requirements to funded project partners to develop both the taxonomy and the data conversion tools. Further efforts included performing extensive industry outreach and awareness to encourage adoption of the Orange Button taxonomy by the solar industry by enumerating the cost saving benefits of using the taxonomy and the public benefit of the increased use of solar energy due to increased bankability and viability of solar development projects. Solar PV panel and component prices have fallen in the last decade, while soft costs have remained stubbornly high and can account for as much as 64% of the total cost of a new solar system. Part of the U.S. Department of Energy SunShot Initiative, Orange Button enabled the creation and adoption of industry-led open data standards for rapid and seamless information exchange across the solar value chain, from origination to decommissioning. Standardizing data will reduce soft costs by making it easier to share solar data and speeding up processes. The taxonomy is a product of solar industry participants convening to identify the pain points caused by incompatible data, and to agree on and standardize data types to be used by the actors in the solar project lifecycle. This report focuses on the SEPA led first phase of Orange Button project that included industry outreach and recruiting participants for five industry working groups, widespread industry outreach to increase awareness and encourage eventual adoption of the taxonomy, and the definition of the scope, use cases, and supporting data types of the Orange Button taxonomy. The solar industry has been receptive of the completed Orange Button taxonomy. In SEPA’s work, 401 solar industry participants facilitated by SEPA defined the scope, use cases, and requirements for the taxonomy leading to over 150 taxonomy early adopters incorporating the taxonomy into their software products serving the solar industry, and several large investors and banks have started projects to enable them to utilize the taxonomy to gain back-office efficiencies. Moving forward, as the solar industry more widely embraces the Orange Button taxonomy and begins realizing the tangible benefits of adoption at scale, we expect further pressure on solar soft costs and increases in the bankability of solar projects.
14 SOLAR ENERGY↗
A multi-region approach for the analysis of porous materials and gas-solid reactions using USAXS-SAXS-WAXS: application to CaO carbonation
The reaction rate of gas-solid non-catalytic reactions is typically investigated using reactant conversion data over time and ex-situ measurements of the porous solid reactant textural properties; these data enable the experimental estimation of the initial intrinsic reaction rate, whereas the evolution of the textural properties and the reaction rate over time are evaluated theoretically using reaction models. In this work, a different methodology is presented, based on: a) in-situ time-resolved USAXS-SAXS-WAXS measurements of the solid sample, and b) a multi-region modeling approach; this methodology allows for the estimation of the textural properties and the intrinsic reaction rate at any time during the reaction. Referring to a reaction in which a solid product is obtained from a solid reactant and a gaseous reactant, the porous particle is described as consisting of several distinct regions with different microstructural properties, and both a gas-solid reaction model and a SAXS model are derived and applied to the carbonation of porous CaO. The proposed reaction model highlights the role of the inaccessible reactant and accurately predicts the solid reactant conversion versus time profile. The SAXS model accurately predicts the measured linear trends of the Porod invariant and of the pre-factor of the power law scattering profile versus CaO mass fraction; in the absence of chemical reactions, the proposed equations extend classical SAXS theory to porous materials containing macropores and nonporous solid phases in addition to standard nanoscale inhomogeneous regions.
CO2 solid sorbents↗
NO x adsorption with CO and C 2 H 4 on Pd/SSZ-13: Experiments and modeling
A transient monolith model containing microkinetic schemes for NO uptake and release over Pd/SSZ-13 without and with reductants CO or C2H4 is presented. The scheme involves three cationic Pd species (Z – [PdOH] + , Z – Pd 2+ Z – , Z – Pd + ) as the active sites during uptake of NO, CO and C 2 H 4 , and their desorption and conversion at higher temperature. Kinetic parameters are estimated through a combination of density functional theory (DFT) estimates and a fit of uptake, desorption and conversion data. The tuned model is validated at different uptake temperatures, ramp rates, and flowrates. A “degree of uptake control” parameter is defined that helps to identify the step(s) that are uptake controlling. The model helps to interpret the data features and is used to identify operating conditions to meet application-relevant performance metrics, including NO trapping efficiency and NO release temperature. Furthermore, the model demonstrates higher NO uptake on Pd/SSZ-13 compared to Pd/ZSM-5.
42 ENGINEERING↗
A Methodology to Create Prototypical Building Energy Models for Existing Buildings: A Case Study on U.S. Religious Worship Buildings
Prototypical building energy models are of great significance because they are the starting point in conducting analyses for various applications, such as building energy saving potential analysis, building design, building energy market evaluation, and building energy policy-making. However, current prototypical building energy models only represent limited types of buildings in certain countries. To fill the gap, this paper proposes a methodology to systematically create prototypical building energy models. First, a six-step methodology is introduced: model input identification, data collection, data cleaning, data conversion, model simulation, and model calibration. Then, the methodology is demonstrated by a case study of creating 30 prototypical energy models for U.S. religious worship buildings, representing buildings in 15 climate zones and 2 vintages (pre- and post-1980). Finally, to show the applications of the models, the building energy saving potentials from six efficiency measures are analyzed for pre-1980 U.S. religious worship buildings in three ASHRAE Climate Zones. The results show that the maximum energy saving potentials are approximately 30% for the religious worship buildings in all three climate zones investigated.
prototype building model, building simulation, Bui↗
Assessing the influence of microstructure on uranium hydride size distributions via small angle neutron scattering
Here, the effect of microstructure on the internal hydriding behavior of both cast (1 mm grain size) and rolled (25 μm grain size) uranium containing hydrogen concentrations between 0 and 1.8 wppm were evaluated via small angle neutron scattering (SANS). Increasing hydrogen content up to 1.8 wppm in the cast uranium only weakly affected the average uranium hydride (UH 3 ) precipitate size, calculated from the SANS data. Conversely, the UH 3 phase fraction was found to strongly depend on the hydrogen content in the same cast samples. A substantially reduced UH 3 particle size distribution was observed in the rolled uranium relative to cast uranium containing the same nominal hydrogen content. It is hypothesized that the suppression of UH 3 formation in the rolled uranium is driven by increased hydrogen trapping at grain boundaries, and theoretical calculations that account for trap density, potency, and hydrogen diffusion kinetics support this hypothesis.
36 MATERIALS SCIENCE↗
Reforming Biomass Derived Pyrolysis Bio-oil Aqueous Phase to Fuels
Fast pyrolysis and catalytic fast pyrolysis (CFP) of biomass produce a liquid product stream comprised of various classes of organic compounds having different molecule size and polarity. This liquid, either spontaneously in the case of catalytic fast pyrolysis or by water addition for the non-catalytic process separates into a non-polar organic-rich fraction and a highly polar water-rich fraction. The organic fraction can be used as a blendstock or feedstock for further processing in a refinery while, in the CFP process design, the aqueous phase is currently sent to wastewater treatment, which results in a loss of residual biogenic carbon present in this stream. Our work focuses on the catalytic conversion of the biogenic carbon in pyrolysis aqueous phase streams to produce hydrocarbons using a vertical micro-reactor coupled to a molecular beam mass spectrometer (MBMS). Furthermore, the MBMS provides real-time analysis of products while also tracking catalyst deactivation. The catalyst used in this work was HZSM-5, which upgraded the oxygenated organics in the aqueous fraction to fuels comprising small olefins and aromatic hydrocarbons. During processing the aqueous bio-oil fraction the HZSM-5 catalyst exhibited higher activity and coke resistance than those observed in similar experiments using biomass or whole bio-oils. Reduced coking is likely due to ejection of coke precursors from the catalyst pores that was enhanced by excess process water available for steam stripping. The water reacted with coke precursors to form phenol, methylated phenols, naphthol, and methylated naphthols. Conversion data shows that up to 40 wt% of the carbon in the feed stream is recovered as hydrocarbons.
09 BIOMASS FUELS↗
Bridging the Gap between Analytical and Microbial Sciences in Microbiome Research
Metabolites from the microbiome influence human, animal, and environmental health, but the diversity and functional roles of these compounds have only begun to be elucidated. Comprehensively characterizing these molecules are significant challenges, as it requires expertise in analytical methods, such as mass spectrometry and nuclear magnetic resonance spectroscopy, skills that not many traditional microbiologists or microbial ecologists possess. This creates a gap between microbiome scientists that want to understand the role of microbial metabolites in microbiome systems and the skills required to generate and interpret complex metabolomics data sets. To bridge this gap, microbiome scientists should engage analytical chemists to best understand the underlying chemical principles of the data. Conversely, analytical scientists are encouraged to engage with microbiome scientists to better understand the biological questions being asked with metabolomics and to best communicate its intricacies. Better communication across the chemistry/biology disciplines will further reveal the “dark matter” within microbiomes that maintain healthy humans and environments.
59 BASIC BIOLOGICAL SCIENCES↗