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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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At least 415 records · Page 23

Comparison of Controller and Flight Deck Algorithm Performance During Interval Management with Dynamic Arrival Trees (STARS)

Managing the interval between arrival aircraft is a major part of the en route and TRACON controller s job. In an effort to reduce controller workload and low altitude vectoring, algorithms have been developed to allow pilots to take responsibility for, achieve and maintain proper spacing. Additionally, algorithms have been developed to create dynamic weather-free arrival routes in the presence of convective weather. In a recent study we examined an algorithm to handle dynamic re-routing in the presence of convective weather and two distinct spacing algorithms. The spacing algorithms originated from different core algorithms; both were enhanced with trajectory intent data for the study. These two algorithms were used simultaneously in a human-in-the-loop (HITL) simulation where pilots performed weather-impacted arrival operations into Louisville International Airport while also performing interval management (IM) on some trials. The controllers retained responsibility for separation and for managing the en route airspace and some trials managing IM. The goal was a stress test of dynamic arrival algorithms with ground and airborne spacing concepts. The flight deck spacing algorithms or controller managed spacing not only had to be robust to the dynamic nature of aircraft re-routing around weather but also had to be compatible with two alternative algorithms for achieving the spacing goal. Flight deck interval management spacing in this simulation provided a clear reduction in controller workload relative to when controllers were responsible for spacing the aircraft. At the same time, spacing was much less variable with the flight deck automated spacing. Even though the approaches taken by the two spacing algorithms to achieve the interval management goals were slightly different they seem to be simpatico in achieving the interval management goal of 130 sec by the TRACON boundary.

Battiste, Vernol↗

Evaluation Issues for a Flight Deck Interface; CAST SE-210 Output 2: Report 4 of 6

This report is part of a series of reports that addresses flight deck design and evaluation, written as a response to loss of control accidents. In particular, this activity is directed at failures in airplane state awareness, in which the pilot loses awareness of the airplane’s energy state or attitude and enters an upset condition. Another report in this series of reports speaks directly to flight deck evaluation methods and metrics for the types of attention and awareness issues that were revealed from the airplane state awareness events. In this report, we describe a wide range of flight deck evaluation issues tied to flight crew performance. The objectives are to establish a framework for thinking about how the flight deck interface should support the performance of the flight crew, and to aid the Federal Aviation Administration (FAA) in identifying relevant human performance issues during the evaluation/certification process. Issues are broken out into sections that cover physical ergonomics, design for usability, data integration and display content, attention and task management, flight crew problem solving, and flight crew teaming. For each issue, we recommend specific ways that the flight deck interface should support the flight crew. For each, we also identify existing 14 CFR Part 25 rules and guidance that are relevant to the issue. This allows the FAA to determine what current regulatory materials can support them in raising the issue with the applicant.

commercial aviation↗

Ares I-X Flight Test Philosophy

In response to the Vision for Space Exploration, the National Aeronautics and Space Administration (NASA) has defined a new space exploration architecture to return humans to the Moon and prepare for human exploration of Mars. One of the first new developments will be the Ares I Crew Launch Vehicle (CLV), which will carry the Orion Crew Exploration Vehicle (CEV), into Low Earth Orbit (LEO) to support International Space Station (ISS) missions and, later, support lunar missions. As part of Ares I development, NASA will perform a series of Ares I flight tests. The tests will provide data that will inform the engineering and design process and verify the flight hardware and software. The data gained from the flight tests will be used to certify the new Ares/Orion vehicle for human space flight. The primary objectives of this first flight test (Ares I-X) are the following: Demonstrate control of a dynamically similar integrated Ares CLV/Orion CEV using Ares CLV ascent control algorithms; Perform an in-flight separation/staging event between an Ares I-similar First Stage and a representative Upper Stage; Demonstrate assembly and recovery of a new Ares CLV-like First Stage element at Kennedy Space Center (KSC); Demonstrate First Stage separation sequencing, and quantify First Stage atmospheric entry dynamics and parachute performance; and Characterize the magnitude of the integrated vehicle roll torque throughout the First Stage (powered) flight. This paper will provide an overview of the Ares I-X flight test process and details of the individual flight tests.

Davis, S. R.↗

Spatiotemporal filtering of MR-temperature artifacts arising from bowel motion during transurethral MR-HIFU

Purpose: Transurethral MR-HIFU is a minimally invasive image-guided treatment for localized prostate cancer that enables precise targeting of tissue within the gland. The treatment is performed within a clinical MRI to obtain real-time MR thermometry used as an active feedback to control the spatial heating pattern in the prostate and to monitor for potential damage to surrounding tissues. This requires that the MR thermometry measurements are an accurate representation of the true tissue temperature. The proton resonance frequency shift thermometry method used is sensitive to tissue motion and changes in the local magnetic susceptibility that can be caused by the motion of air bubbles in the rectum, which can impact the performance of transurethral MR-HIFU in these regions of the gland. Methods: A method is proposed for filtering of temperature artifacts based on the temporal variance of the temperature, using empirical and dynamic positional knowledge of the ultrasonic heating beam, and an estimation of the measurement noise. A two-step correction strategy is introduced which eliminates artifact-detected temperature variations while keeping the noise level low through spatial averaging. Results: The filter has been evaluated by postprocessing data from five human transurethral ultrasound treatments. The two-step correction process led to reduced final temperature standard deviation in the prostate and rectum areas where the artifact was located, without negatively affecting areas distal to the artifact. The performance of the filter was also found to be consistent across all six of the data sets evaluated. The evaluation of the detection criterion parameter M determined that a value of M = 3 achieves a conservative filter with minimal loss of spatial resolution during the process. Conclusions: The filter was able to remove most artifacts due to the presence of moving air bubbles in the rectum during transurethral MR-HIFU. A quantitative estimation of the filter capabilities shows a systematic improvement in the standard deviation of the corrected temperature maps in the rectum zone as well as in the entire acquired slice.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗

Fully automatic characterization and data collection from crystals of biological macromolecules

A fully automatic system has been developed that performs X-ray centring and characterization of, and data collection from, large numbers of cryocooled crystals without human intervention. Considerable effort is dedicated to evaluating macromolecular crystals at synchrotron sources, even for well established and robust systems. Much of this work is repetitive, and the time spent could be better invested in the interpretation of the results. In order to decrease the need for manual intervention in the most repetitive steps of structural biology projects, initial screening and data collection, a fully automatic system has been developed to mount, locate, centre to the optimal diffraction volume, characterize and, if possible, collect data from multiple cryocooled crystals. Using the capabilities of pixel-array detectors, the system is as fast as a human operator, taking an average of 6 min per sample depending on the sample size and the level of characterization required. Using a fast X-ray-based routine, samples are located and centred systematically at the position of highest diffraction signal and important parameters for sample characterization, such as flux, beam size and crystal volume, are automatically taken into account, ensuring the calculation of optimal data-collection strategies. The system is now in operation at the new ESRF beamline MASSIF-1 and has been used by both industrial and academic users for many different sample types, including crystals of less than 20 µm in the smallest dimension. To date, over 8000 samples have been evaluated on MASSIF-1 without any human intervention.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data

Background: Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge. Results: We present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented. Conclusions: VizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/ VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux.

97 MATHEMATICS AND COMPUTING↗

Closure Report for the Central Facilities Area Sewage Treatment Plant Lagoon 3 and Land Application Area

Because of significantly reduced wastewater discharges to the Central Facilities Area Sewage Treatment Plant, wastewater has not been land applied since 2011. The future need to land apply wastewater was evaluated. Based on the current wastewater flows into the Central Facilities Area Sewage Treatment Plant, expected future missions at Central Facilities Area, and the discovery in 2014 that Lagoon 3 was leaking at an unacceptable rate, it was determined that the Central Facilities Area Sewage Treatment Plant is significantly oversized and that Lagoons 1 and 2 could be converted to total evaporation lagoons. Therefore, the decision was made to remove the existing sludge in Lagoon 3 and transfer it to Lagoon 2 for additional treatment, decommission Lagoon 3 and the land application area, and terminate the wastewater reuse permit. A closure plan was submitted and approved by the Idaho Department of Environmental Quality in 2016. This report describes the closure activities that were performed. Closure activities included: • Characterizing the soil/liner in Lagoon 3 to determine whether further characterization and/or remediation will be required under the Comprehensive Environmental Response, Compensation, and Liability Act. • Based on the results from the soil/liner sampling, determining whether additional sampling will be required for the land application area. • Removing the sludge in Lagoon 3 and placing it in Lagoon 2. • Puncturing the Lagoon 3 soil/liner to prevent ponding of storm water and becoming a source for vectors. • Installing a permanent cap on the inlet piping to Lagoon 3. Samples were collected on November 10, 2016, and were submitted for analysis to an off-site laboratory. Data validation and evaluation were performed by Portage, INC. Sample results confirmed that there is no hazard to human health and the environment and that Lagoon 3 and the land application area could be closed. In August 2017, sludge was removed from Lagoon 3 and placed in Lagoon 2, the soil/liner was punctured in 4 places, and caps were installed on the primary and bypass inlet lines.

99 GENERAL AND MISCELLANEOUS↗

An Earth-Based Equivalent Low Stretch Apparatus to Assess Material Flammability for Microgravity & Extraterrestrial Fire-Safety Applications

One of the performance goals for NASA's enterprise of Human Exploration and Development of Space (HEDS) is to develop methods, data bases, and validating tests for material flammability characterization, hazard reduction, and fire detection/suppression strategies for spacecraft and extraterrestrial habitats. This work addresses these needs by applying the fundamental knowledge gained from low stretch experiments to the development of a normal gravity low stretch material flammability test method. The concept of the apparatus being developed uses the low stretch geometry to simulate the conditions of the extraterrestrial environment through proper scaling of the sample dimensions to reduce the buoyant stretch in normal gravity. The apparatus uses controlled forced-air flow to augment the low stretch to levels which simulate Lunar or Martian gravity levels. In addition, the effect of imposed radiant heat flux on material flammability can be studied with the cone heater. After breadboard testing, the apparatus will be integrated into NASA's White Sands Test Facility's Atmosphere-Controlled Cone Calorimeter for evaluation as a new materials screening test method.

Olson, S. L.↗

Human Systems Integration: Unmanned Aircraft Control Station Certification Plan Guidance

This document provides guidance to the FAA on important human factors considerations that can be used to support the certification of a UAS Aircraft Control Station (ACS). This document provides a synopsis of the human factors analysis, design and test activities to be performed to provide a basis for FAA certification. The data from these analyses, design activities, and tests, along with data from certification/qualification tests of other key components should be used to establish the ACS certification basis. It is expected that this information will be useful to manufacturers in developing the ACS Certification Plan,, and in supporting the design of their ACS.

Source record↗

Tele-Supervised Adaptive Ocean Sensor Fleet

The Tele-supervised Adaptive Ocean Sensor Fleet (TAOSF) is a multi-robot science exploration architecture and system that uses a group of robotic boats (the Ocean-Atmosphere Sensor Integration System, or OASIS) to enable in-situ study of ocean surface and subsurface characteristics and the dynamics of such ocean phenomena as coastal pollutants, oil spills, hurricanes, or harmful algal blooms (HABs). The OASIS boats are extended- deployment, autonomous ocean surface vehicles. The TAOSF architecture provides an integrated approach to multi-vehicle coordination and sliding human-vehicle autonomy. One feature of TAOSF is the adaptive re-planning of the activities of the OASIS vessels based on sensor input ( smart sensing) and sensorial coordination among multiple assets. The architecture also incorporates Web-based communications that permit control of the assets over long distances and the sharing of data with remote experts. Autonomous hazard and assistance detection allows the automatic identification of hazards that require human intervention to ensure the safety and integrity of the robotic vehicles, or of science data that require human interpretation and response. Also, the architecture is designed for science analysis of acquired data in order to perform an initial onboard assessment of the presence of specific science signatures of immediate interest. TAOSF integrates and extends five subsystems developed by the participating institutions: Emergent Space Tech - nol ogies, Wallops Flight Facility, NASA s Goddard Space Flight Center (GSFC), Carnegie Mellon University, and Jet Propulsion Laboratory (JPL). The OASIS Autonomous Surface Vehicle (ASV) system, which includes the vessels as well as the land-based control and communications infrastructure developed for them, controls the hardware of each platform (sensors, actuators, etc.), and also provides a low-level waypoint navigation capability. The Multi-Platform Simulation Environment from GSFC is a surrogate for the OASIS ASV system and allows for independent development and testing of higher-level software components. The Platform Communicator acts as a proxy for both actual and simulated platforms. It translates platform-independent messages from the higher control systems to the device-dependent communication protocols. This enables the higher-level control systems to interact identically with heterogeneous actual or simulated platforms.

Lefes, Alberto↗

A Rapid, Low-Cost Approach to Permanently Extend Life Beyond Earth

This presentation covers the value proposition and challenges of permanently extending life beyond Earth. It proposes that this can be most expeditiously accomplished by starting with a population of small Closed Ecological Systems (CES)s, each with several specie populations that enable each CES to persist indefinitely without the need to add resources, remove wastes, or require human intervention. Each CES is instrumented and controlled so that it can be remotely maintained, experiments performed, and data collected. Data from the entire population of CESs are managed in a cloud server database for analyses on how to improve the performance of each CES as well as formulate new CESs. The presentation discusses a modular, artificial-spacecraft prototype that could be used to fly CES modules in space under various gravity and radiation conditions to study changes in the CESs relative to their counterparts that remain on Earth as the control group. The presentation concludes with the next, low-cost steps for rapidly executing the approach described.

Dorais, Gregory A.↗

Systemic Alterations with Spaceflight Associated Health Risks Originating from Both Circulating miRNAs and Mitochondrial Biology

The many known health risks currently associated with space travel include increased risk of cardiovascular disease, cancer, central nervous system related diseases, muscle degeneration, and changes with host-gut microbiome interactions that can have profound impact with these and other health risks. The majority of the risk from space travel stem of the two components of the space environment which are microgravity and radiation. Two specific systemic effects have been uncovered by us to impact the body as a whole due to the space environment. One factor is related from our earlier work (Beheshti et al, PLOS One, 2018), we predicted that there is a systemic component of the host that causes general increased health risks due to spaceflight driven by a circulating microRNA (miRNA) signature consisting of 13 miRNAs that directly regulates both p53 and TGF1. MiRNAs are small non-coding RNA molecules with a negative and post-transcriptional regulation on gene expression) are increasingly recognized as major systemic regulators of responses to stressors, including microgravity, oxidative stress, and DNA damage. In addition, due to the size and stability of miRNAs, it is known that miRNAs can circulate throughout the body and have been found in the majority of the bodily fluids including blood, urine, saliva, and tears. Here, we start to dissect the actual impact of this miRNA signature on both the radiation and microgravity components and prove that this miRNA signature actually exists in the circulation of a host. The other systemic factor we uncovered was the impact the mitochondria on the whole body due to spaceflight. We hypothesize that spaceflight may promote a physiologic response driven by systemic mitochondria pathways leading to metabolic disorder stemming from the liver and directly impacting other organs and tissues. A systems biology method was implemented utilizing GeneLab datasets that involved in vitro experiments performed at the low Earth orbit, in vivo experiments involving mice flown to space, and finally human physiological data from astronauts. A comprehensive multi-omics approach was implemented which involved correlating transcriptomic analysis with proteomics, metabolomics, and methylation analysis. This approach led us to confirm our hypothesis that a systemic mitochondrial driven response is responsible for increasing potential health risk and is conserved from the in vitro studies, to the in vivo studies, and finally confirmed in astronauts.

Radiation↗

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, we’ll compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, we’ll discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. We’ll also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata.

Gosses, Justin↗

A Preliminary Study on the Feasibility of Large Language Models for Detecting Micro-Behaviors Among Team Members in Space Missions

Large-language models (LLMs) have been recently used for spoken language understanding (SLU) to infer meaning and semantics from speech in tasks such as speaker intent and sentiment classification. Due to being trained on large amounts of data, and their ability to understand context and relationships between words, LLMs are competent, enabling them to generalize across tasks without requiring many task-specific training samples. This research examines the feasibility of few-shot learning in LLMs for detecting subtle, brief, and possibly unconscious interactions between team members, called ``micro-behaviors," and provides insights into the appropriate design of LLMs for this task. Our data came from 5 teams participating in a 45-day mission at the US National Aeronautics and Space Administration’s (NASA) Human Exploration Research Analog (HERA). More specifically we used data collected from team interaction battery (TIB) tasks teams performed five times in-mission which comprise an average 1.5 hours of conversation data per day. Micro-behaviors were coded according to an adapted version of Smith & Griffins (2022) theoretical framework in terms of Violation (i.e., presence of valenced behavior, uplifting/positive or discouraging/negative), Intensity (i.e., force of behavior in terms of how uplifting or discouraging is the behavior), and Intent (i.e., motive of the behavior in terms of whether it was deliberate or unintentional). We explore the ability of LLMs to detect the presence and intensity of micro-behaviors. We examine employing and fine-tuning readily available LLMs (i.e., RoBERTa, DistilBERT), as well as prompting state-of-the-art sequence classification models (i.e., Llama-2, Llama-3). In a total of 13,058 conversational turns (17.8% uplifting, 3.3% discouraging, 75.76% neutral, 3.14% nulls), we compute the macro F1-score of the 3-way micro-behavior classification task (i.e., classifying among uplifting, discouraging, and neutral; 33% chance). Results indicate that the RoBERTa model achieves a F1-score of 36.2% (uplift: 43.3% precision (P), 15.1% recall (R); discourage: 20% P, 0.5% R). These results significantly improve when we augment the data via paraphrasing in the RoBERTa model, reaching a 41.2% macro F1-score (uplift: 37.7% P, 86.3% R; discourage: 3.5% P, 1.8% R). Finally, the Llama-2 model with 3-shot prompting yields 38% macro F1-score (uplift: 28.7% P, 20% R; discourage: 7.2% P, 18% R), which is slightly better compared to the RoBERTa model without data augmentation, highlighting the effectiveness of sequence classification models in detecting minority classes with a small sample size. Findings indicate that LLMs hold potential to detect subtle behaviors in conversations, which could be valuable in assessing team behavior in space exploration missions. Future studies will evaluate the performance of different LLM prompting strategies or fine-tuning methods.

Ankush Raut↗

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗

Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers

Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the model observers using the IR images was always higher than that seen using the FBP images in the authors’ SKE and SKE location unknown detection tasks. To achieve a FBP-equivalent image quality in CT systems, the authors can lower the radiation dose by using this IR image reconstruction algorithm. Further studies are warranted using clinical data and human observer to validate these results for more complicated and realistic tasks.

60 APPLIED LIFE SCIENCES↗