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At least 937 records · Page 52

Meta‐Analysis and Regression Modeling of the Impacts of Four Indoor Environmental Quality Metrics on Office Performance

Awareness of how buildings interact with the occupant experience—especially human performance—is becoming more prevalent, as seen by increasing interest and investment in healthy built environments. However, there is a need to synthesize the wide array of existing indoor environmental assessment and performance research in a way that can translate directly to building design and operation. Existing research in this area typically focuses on a single isolated metric and has not focused on making the results utilizable by building practitioners. The aim of this research is to investigate existing office performance literature through meta‐analyses and produce regression models for four indoor environmental quality (IEQ) metrics to support critical decision‐making for building operation and renovation. To reach this aim, a literature review was conducted to identify studies that measure the impact of changing ventilation rate, temperature, horizontal illuminance, and noise level in offices on occupant task performance. This repository of field and laboratory studies was analyzed to visualize the trends between the selected IEQ metrics and task performance. The temperature, ventilation rate, and horizontal illuminance regression models showed clear improvement potential when modifying indoor conditions toward the defined high‐performance range, while the regression model for noise level was inconclusive. The discussion notes the importance of designing holistically for all components of these IEQ categories to utilize the results, for example, good filtration on outdoor air for quantifying ventilation impact and uniform overhead lighting with low contrast for quantifying horizontal illuminance impact. The novelty of this work is in considering multiple facets of the indoor environment under a single, unified analysis schema and producing IEQ‐based performance gains that can directly inform cost‐benefit analyses of building design and renovation.

60 APPLIED LIFE SCIENCES↗

EXSCLAIM!

Due to recent improvements in image resolution and acquisition speed, materials microscopy is experiencing an explosion of published imaging data. The standard publication format, while sufficient for traditional data ingestion scenarios where a select number of images can be critically examined and curated manually, is not conducive tolarge-scale data aggregation or analysis, hindering data sharing and reuse. Most images in publications are presented as components of a larger figure with their explicit context buried in the main body or caption text, so even if aggregated, collections of images with weak or no digitized contextual labels have limited value. To solve the problem of curating labeled microscopy data from literature, we introduce the EXSCLAIM! Python toolkit for the automatic EXtraction, Separation, and Caption-based natural Language Annotation of IMages from scientific literature. The software is implemented through a three part pipeline: the JournalScraper, which searches the web and downloads figures and captions based on a user provided query, the CaptionDistributor, which separates caption text based on the subfigure each portion of the caption refers to, and the FigueSeparator, which separates figures into component subfigures and extracts other visual information. Also included is a Django user interface for exploring the resulting dataset.

CHAN, MARIA↗

Openpronghorn

OpenPronghorn is a simulation tool specifically tailored for modeling thermal-hydraulic phenomena in advanced nuclear reactors. It is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE), an open-source platform that facilitates the development of high-performance scientific computing applications. OpenPronghorn solves the Navier-Stokes equations, which describe the conservation of mass, momentum, and energy in fluid flows, using the finite volume numerical method. The code supports a wide range of fluid flow conditions that are applicable to nuclear reactors, including incompressible and weakly compressible flows, as well as single-phase and multiphase flows. It is capable of modeling diverse flow regimes, including laminar and turbulent flows, using various turbulence models such as the standard k-epsilon models, the v2f model, and the mixing length model. For multiphase flows, OpenPronghorn employs a mixture a Eulerian modeling approach with mixture, drift-flux, and full Eulerian models, and includes open-sourced interfacial transfer correlations for drag, exchange, and heat transfer coming from the scientific literature. OpenPronghorn's modular design allows it to handle multiscale simulations, ranging from detailed Reynolds-Averaged Navier Stokes (RANS) simulations to coarse-mesh and lumped parameter models. This flexibility enables users to perform high-fidelity simulations of specific reactor components as well as system-level analyses of entire reactor circuits. The code can be coupled with other MOOSE-based tools using the MultiApp system, allowing for the transfer of coupling quantities such as mass flow rates, heat fluxes, and boundary conditions between different simulation scales. One of the main features of OpenPronghorn is the it includes built-in validation cases from the open-source scientific literature and supports the implementation of user-defined models and correlations through MOOSE's FunctorMaterial system. OpenPronghorn is designed to be computationally efficient, leveraging the SIMPLE projection method for large-scale problems, and can be run on high-performance computing systems to handle the extensive computational demands of detailed reactor simulations. Overall, OpenPronghorn is a versatile and robust tool that provides critical insights into the thermal-hydraulic behavior of advanced nuclear reactors, supporting the design, safety, and optimization of next-generation nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

A meta-analysis of semantic classification of citations

The aim of this literature review is to examine the current state of the art in the area of citation classification. In particular, we investigate the approaches for characterizing citations based on their semantic type. We conduct this literature review as a meta-analysis covering 60 scholarly articles in this domain. Although we included some of the manual pioneering works in this review, more emphasis is placed on the later automated methods, which use Machine Learning and Natural Language Processing (NLP) for analyzing the fine-grained linguistic features in the surrounding text of citations. The sections are organized based on the steps involved in the pipeline for citation classification. Specifically, we explore the existing classification schemes, data sets, pre-processing methods, extraction of contextual and non-contextual features, and the different types of classifiers and evaluation approaches. The review highlights the importance of identifying the citation types for research evaluation, the challenges faced by the researchers in the process, and the existing research gaps in this field.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Columnar Vertical Profile (CVP) Methodology for Validating Polarimetric Radar Retrievals in Ice Using In Situ Aircraft Measurements

Abstract A novel way to process polarimetric radar data collected via plan position indicator (PPI) scans and display those data in a time–height format is introduced. The columnar vertical profile (CVP) methodology uses radar data collected via multiple elevation scans, limited to data within a set region in range and azimuth relative to the radar, to create vertical profiles of polarimetric radar data representative of that limited region in space. This technique is compared to others existing in the literature, and various applications are discussed. Polarimetric ice microphysical retrievals are performed on CVPs created within the stratiform rain region of two mesoscale convective systems sampled during two field campaigns, where CVPs follow the track of research aircraft. Aircraft in situ data are collocated to microphysical retrieval data, and the accuracy of these retrievals is tested against other retrieval techniques in the literature.

Engineering↗

Improved Infrared Optical Constants from Pressed Pellets: II. Ellipsometric n and k Values for Ammonium Sulfate with Variability Analysis

Infrared spectral imaging is facilitated via the comparison of spectra recorded in situ to a databank of actual or synthetic infrared reflectance spectra. It has recently been shown that reference spectra corresponding to the many different morphological forms of the same chemical can be generated synthetically using the imaginary, k, and real, n, components of the complex refractive index, n~ = n + ik. One method to obtain the n and k vectors is infrared ellipsometry, which measures the changes in amplitude, tan ?, and phase, ?, of polarized light reflected from the sample both as a function of wavenumber and angle of incidence. The method requires specularly reflected light so best results are usually obtained with polished planar samples of large surface area. Due to the difficulties of obtaining such samples, however, we investigate the possibility of pressing powders of neat materials and obtaining the corresponding optical constants from the pellets. In this paper, variability in the sample pellet and preparation method is investigated, as is variability in the fitting procedure for the derived optical constants. The n/k vectors are derived from the measured ellipsometric parameters, tan ? and ?, as they are fit by an oscillator model which yield n(?) and k(?) vectors as a function of wavenumber, ?. Construction of the oscillator model is not automatic and depends on significant input from the analyst as well as the sample’s physical characteristics. For the pellet pressing, the experimental variability was found to be minimized for size-selected powdered samples as gauged by the minimal variance in ? and ? for three different pellets; similarly, the analytical precision for multiple measurements of the same pellet was also quite good, suggesting that a pressed pellet is a viable sample preparation method. The greatest variability came in the analytic fitting procedure with differences up to 20% arising from four different fits to the same data set. The final ellipsometric n/k data are compared to literature values obtained from crystalline (NH4)2SO4 samples as well as single-angle reflectance measurements that also used pressed pellets. Comparison with the previous literature values shows generally good agreement although higher k-values are observed for the independent sets of data derived from pressed pellets. These data are suggested as an improved set of optical constants for (NH4)2SO4.

optical constants, ellipsometry, ammonium sulfate,↗

Misclassification in Workers’ Telecommuting Frequency Choices Using a Generalized Extreme Value Model

Telecommuting frequency is a response variable collected in travel surveys and is, therefore, prone to errors leading to mismeasurements or misclassification. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. We define “misclassification” as a response reported or recorded in the wrong category; for example, a variable is recorded as a 1 when it should be 0. Here, in this context, this study aims to develop a statistical model to analyze telecommuting data which accounts for potential misclassification errors by building on existing literature in econometrics. The empirical analysis was undertaken using the 2017 National Household Travel Survey (NHTS) and the general extreme value (GEV) models available in the literature. Specifically, the frequency of telecommuting days was analyzed using the negative binomial (NB) model recast as the multinomial logit (MNL) model. By nature—and consistent with other studies—NHTS data are prone to errors that can be classified as intentional or unintentional misinformation provided by the person being interviewed. Ignoring these errors while modeling telecommuting frequencies using standard discrete count models can result in biased parameter estimates. The misclassification parameter was calculated for both over-reporting and under-reporting scenarios. The misclassification errors can be as high as 14% over-reported and 10% under-reported, particularly for the neighboring values. Statistical fit comparison between the models shows that models that ignore misclassification have worse data fit and biased parameter estimates with significant policy implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life

Agent-based models (ABMs) in transportation modeling simulate activity and travel decisions at the disaggregate level of households and individuals. To do this, ABMs require detailed and realistic information on agents’ socioeconomic and demographic characteristics. Various synthetic population generators have been proposed to address this need. However, most of those currently in practice are cross-sectional in nature and do not account for the dynamics within households and individuals as they progress through life events over time. This is a major shortcoming, as literature has shown that transportation decisions are affected by the transition between and co-occurrence of life cycle events. While some demographic evolution simulators have been proposed to address this issue, they are developed using cross-sectional data and capture only a small set of life cycle events and their interdependence. Addressing these drawbacks, we propose a demographic microsimulator (DEMOS) that captures the “continuum of life” by considering a range of household- and individual-level life cycle events. DEMOS is developed using the Panel Survey of Income Dynamics, one of the world’s longest-running longitudinal surveys. The DEMOS submodels consider key life cycle events that are influenced by agents’ demographic variables. DEMOS is applied to evolve the population of the San Francisco Bay Area over a 9-year horizon. Results demonstrate how DEMOS generates life trajectories and how DEMOS outputs match the observed demographic trends. DEMOS is expected to enable longitudinal analysis in the context of ABMs and expand ABMs analyses relating to dynamic processes such as household-level vehicle transactions.

Demographic evolution↗

Investigating realistic anode off-gas combustion in SOFC/ICE hybrid systems: mini review and experimental evaluation

Solid oxide fuel cells (SOFCs) have been deployed in hybrid decentralized energy systems, in which they are directly coupled to internal combustion engines (ICEs). Prior research indicated that the anode tailgas exiting the SOFC stack should be additionally exploited due to its high energy value, with typical ICE operation favoring hybridization due to matching thermodynamic conditions during operation. Consequently, extensive research has been performed, in which engines are positioned downstream the SOFC subsystem, operating in several modes of combustion, with the most prevalent being homogeneous compression ignition (HCCI) and spark ignition (SI). Experiments were performed in a 3-cylinder ICE operating in the latter modus operandi, where the anode tailgas was assimilated by mixing syngas (H 2 : 33.9%, CO: 15.6%, CO 2 : 50.5%) with three different water vapor flowrates in the engine’s intake. While increased vapor content significantly undermined engine performance, brake thermal efficiency (BTE) surpassed 34% in the best case scenario, which outperformed the majority of engines operating under similar operating conditions, as determined from the conducted literature review. Nevertheless, the best performing application was identified operating under HCCI, in which diesel reformates assimilating SOFC anode tailgas, fueled a heavy duty ICE (17:1), and gross indicated thermal efficiency ([Formula: see text]) of 48.8% was achieved, with the same engine exhibiting identical performance when operating in reactivity-controlled compression ignition (RCCI). Overall, emissions in terms of NO x and CO were minimal, especially in SI engines, while unburned hydrocarbons (UHC) were non-existent due to the absence of hydrocarbons in the assessed reformates.

Engineering↗

Influence of gradation on failure mode of saturated sand at particle scale

Extensive research has been reported in the literature to characterize the failure mode of dry sand using various experimental techniques such as surface optical imaging, photo-elastic materials, three-dimensional (3D) computed tomography (CT), and 3D synchrotron micro-computed tomography (SMT). However, there is a limited literature about the behavior of saturated sand. This paper presents the results of axisymmetric triaxial compression (ATC) experiments that were conducted on saturated sand specimens. The behavior of specimens composed of a uniform sand with grain size between US sieves #40 and #50 is compared to specimens conducted on the same sand that has a wider gradation. 3D SMT technique was used to acquire 3D scans while shearing the specimens to probe localized events that are completely missed or misinterpreted when analyzing ATC measurements based on global standard measurements. The results show a higher effective principal stress ratio (EPSR) for the non-uniform specimen and a thicker shear band when compared to uniform specimen.

Elnur, Mohammed [University of Tennessee]↗

Calibration of V-Notch and Compound Weirs for Subsurface Drainage Water Level Control Structures

Highlights Accurate discharge estimation is important when evaluating edge-of-field conservation practices. V-notch weir equations were developed for three sizes of subsurface drainage water level control structures. Compound weir equations were developed for subsurface drainage water level control structures. The compound weir equation accurately estimates discharge for flows within and overtopping the V-notch. Abstract.Numerous edge-of-field conservation practices use subsurface drainage water level control structures to monitor water levels and estimate discharge. In a control structure, procedures for calculating discharge when flow depth (head) exceeds the V-notch depth and overflows in the rectangular portion of the compound weir (CW) are ambiguous. In this study, we developed calibration equations for V-notch weirs in Agri Drain inline water level control structures of different sizes for flows within the V-notch and overtopping flow events. The discharge equation for overtopping events (Q CW , L s -1 ) was determined as: Q CW = a 1 (h b1 -h 1 b1 )+a 2 (W e -W v )h 1 b2 , where h and h 1 are heads above vertex/bottom and top of V-notch (cm), respectively, W is the effective crest width of rectangular weir (cm), W v is the top width of V-notch (cm), a 1 and b 1 are parameters for V-notch weir obtained by calibration, and a 2 and b 2 are calibration parameters for rectangular weir obtained from literature. Results were compared with a weir equation available in the literature (Q V+R ), which combines a V-notch equation with a head equal to V-depth and a rectangular weir equation for flow above V-depth. Discharge at overflow was estimated with high accuracy with Q CW, whereas Q V+R underestimated discharge (e.g., PBIAS of 0.67% vs. 17.82% for a 15.2 cm structure). An example using Q V+R resulted in a 14% lower annual estimation of nitrate-N load diverted to a saturated buffer than Q CW due to underestimation of drainage discharge during overflow events. Results suggest that the developed equation (Q CW ) accurately estimates discharge and will thus improve the estimated N load compared to Q V+R . Keywords: Compound weir, Flow monitoring, Subsurface drainage, V-notch weir, Water level control structure, Weir calibration.

Agriculture↗

Burst-mode dual-comb spectroscopy

We introduce a new modality of dual-comb spectroscopy that enables a simplified and powerful new approach for time-resolved measurements with increased acquisition rates. This "burst mode" form of dual-comb spectroscopy (BM-DCS) relies on the multiplexing of each probe pulse into a short train of pulses. With this approach we demonstrate a time-resolved series of absorption-based spectroscopic measurements of a laser-induced plasma using only a single laser ablation shot and identify 22 Nd lines not previously reported in the literature. The transmission spectra spanned 3.1 THz and were acquired at an effective acquisition rate of 25 kHz with 40 ms time-resolution. This simple modification to 100 MHz level dual-comb systems provides a flexible approach for studying transient and low duty-cycle events such as laser-induced plasmas, combustion, and explosive reactions.

(280.5395) Plasma Diagnostics, broadband laser spe↗

COVIDScholar: An automated COVID-19 research aggregation and analysis platform

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community’s COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org/, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

60 APPLIED LIFE SCIENCES↗

Metabolic multireactor: Practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments

We present a system for carrying out small batch reactor oxygen consumption experiments on water and sediment samples for environmental questions. In general, it provides several advantages that can help researchers achieve impactful experiments at relatively low costs and high data quality. In particular, it allows for multiple reactors to be operated and their oxygen concentrations to be measured simultaneously, providing high throughput and high time-resolution data, which can be advantageous. Most existing literature on similar small batch-reactor metabolic studies is limited to either only a few samples, or only a few time points per sample, which can restrict the ability for researchers to learn from their experiments. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. As such we do not delve deeply into the specifics of the fluorescent dye sensing mechanism. Instead, we focus on practical considerations. We describe the construction and operation of the calibration and experimental systems, and answer many of the questions likely to come up when other researchers choose to build and operate a similar system themselves (questions we ourselves had when we first built the system). In this way, we hope to provide an approachable and easy to use research article that can help other researchers construct and operate a similar system that can be tailored to ask their own research questions, with a minimum of confusion and missteps along the way.

3D printing↗

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗

Community Based Data of Potentiometric Titration of Iron Oxides: Ferrihydrite (HFO), Goethite, Hematite, Magnetite

This data release includes experimental data of potentiometric titration for iron oxides. The data in the provided .csv files is not our own experimental data but have been compiled from the multiple literature sources. The master database is L-SCIE (LLNL Surface Complexation/Ion Exchange) database, and the provided .csv files are extracted data from L-SCIE. The .csv files were obtained by using the Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) code written in the R programming language (free licensing available at https://ipo.llnl.gov/technologies/software/llnl-surface-complexation-database-converter-scdc).The released data was used for developing a comprehensive community data-driven surface complexation modeling (SCM) framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources.

54 ENVIRONMENTAL SCIENCES↗

NGEE Arctic Phase 4 Plant Functional Type Framework for Pan-Arctic Vegetation

The NGEE-Arctic research team identified a common set of hierarchical plant functional types (PFTs) for pan-arctic vegetation that we will use across our research activities. Interdisciplinary work within a large team requires agreement regarding levels of functional organization so that knowledge, data, and technologies can be shared and combined effectively. The team has identified plant functional types as a crucial area where such interoperability is needed. PFTs are used to represent plant pools and fluxes within models, summarize observational data, and map vegetation across the landscape. Within each of these applications, varying levels of PFT specificity are needed according to the specific scientific research goal, computational limitations, and data availability. By agreeing on a specific hierarchical framework for grouping variables in our vegetation data, we ensure the resulting research products will be robust, flexible, and scalable. In this document, we lay out the agreed upon PFT framework with definitions and references to existing literature. Table 1 included in the "NGA700_Phase4PFTFramework_about*" file outlines the relationship between NGEE-Arctic Phase 4, Tier 1 PFTs and the PFTs used within prominent arctic literature as well as publications by the NGEE-Arctic team during phases 1-3.This dataset consists of a table detailing a hierarchical PFT framework that spans 4 tiers with the most granular PFTs listed in tier 1 and the most general PFTs in tier 4. The PFTs within each tier has a single column in the dataset where the PFTs are named and a separate column where the characteristics used to define that PFT are listed. Grey fill of the cells is used to indicate where a given PFT starts to “lose” tier 1 details as you look from left to right. Note the excel file has merged cells to indicate grouping of PFTs across the Tiers- it will not translate into a delimited filetype (.csv, .txt, etc) without modification thus the hierarchical PFT framework table is available in three different file formats: 1) NGA700_Phase4PTS.xlsx – maintains the merged cells and grey fill; 2) NGA700_Phase4PTS.csv – merged cells are split, and grey fill is removed; 3) NGA700_Phase4PTS.pdf – image of the table with merged cells and grey fill. Metadata document included as a *.pdf and file-level metadata and data dictionary as *.csv files.

54 ENVIRONMENTAL SCIENCES↗

An Exact Algorithm for the Linear Tape Scheduling Problem

Magnetic tapes are often considered as an outdated storage technology, yet they are still used to store huge amounts of data. Their main interests are a large capacity and a low price per gigabyte, which come at the cost of a much larger file access time than on disks. With tapes, finding the right ordering of multiple file accesses is thus key to performance. Moving the reading head back and forth along a kilometer long tape has a non-negligible cost and unnecessary movements thus have to be avoided. However, the optimization of tape request ordering has rarely been studied in the scheduling literature, much less than I/O scheduling on disks. For instance, minimizing the average service time for several read requests on a linear tape remains an open question. Therefore, in this paper, we aim at improving the quality of service experienced by users of tape storage systems, and not only the peak performance of such systems. To this end, we propose a reasonable polynomial-time exact algorithm while this problem and simpler variants have been conjectured NP-hard. We also refine the proposed model by considering U-turn penalty costs accounting for inherent mechanical accelerations. Then, we propose a low-cost variant of our optimal algorithm by restricting the solution space, yet still yielding an accurate suboptimal solution. Finally, we compare our algorithms to existing solutions from the literature on logs of the mass storage management system of a major datacenter. This allows us to assess the quality of previous solutions and the improvement achieved by our low-cost algorithm. Aiming for reproducibility, we make available the complete implementation of the algorithms used in our evaluation, alongside the dataset of tape requests that is, to the best of our knowledge, the first of its kind to be publicly released.

Honoré, Valentin↗