Showing papers by "University of Maine published in 2022"

Recycling of natural fiber composites: Challenges and opportunities

Abstract: Natural fibers have been widely used for reinforcing polymers attributed to their sustainable nature, excellent stiffness to weight ratio, biodegradability, and low cost compared with synthetic fibers like carbon or glass fibers. Thermoplastic composites offer an advantage of recyclability after their service life, but challenges and opportunities remain in the recycling of natural fiber reinforced polymer composites (NFRPCs). This article summarized the effects of reprocessing/recycling on the material properties of NFRPCs. The material properties considered include mechanical performance, thermal properties, hygroscopic behavior, viscoelasticity, degradation, and durability. NFRPCs can generally be recycled approximately 4–6 times until their thermomechanical properties change. After recycling 7 times, the tensile strength of NFRPCs can decrease by 17%, and the tensile modulus can decrease by 28%. The mitigation approaches to overcome degradation of material properties of NFRPCs such as adding functional additives and virgin plastics are also discussed. The main challenges in these approaches such as degradation and incompatibility are discussed, and an effort is made to provide a rationale for reprocessing/recyclability assessment. Future applications of NFRPCs such as additive manufacturing and automotive part use are discussed.

A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations

Abstract: Lending decisions are usually made with proprietary models that provide minimally acceptable explanations to users. In a future world without such secrecy, what decision support tools would one want to use for justified lending decisions? This question is timely, since the economy has dramatically shifted due to a pandemic, and a massive number of new loans will be necessary in the short term. We propose a framework for such decisions, including a globally interpretable machine learning model, an interactive visualization of it, and several types of summaries and explanations for any given decision. The machine learning model is a two-layer additive risk model, which resembles a two-layer neural network, but is decomposable into subscales. In this model, each node in the first (hidden) layer represents a meaningful subscale model, and all of the nonlinearities are transparent. Our online visualization tool allows exploration of this model, showing precisely how it came to its conclusion. We provide three types of explanations that are simpler than, but consistent with, the global model: case-based reasoning explanations that use neighboring past cases, a set of features that were the most important for the model's prediction, and summary-explanations that provide a customized sparse explanation for any particular lending decision made by the model. Our framework earned the FICO recognition award for the Explainable Machine Learning Challenge, which was the first public challenge in the domain of explainable machine learning. 1

Quantitative serology for SARS-CoV-2 using self-collected saliva and finger-stick blood

Abstract: Convenient and widespread serology testing may alter the trajectory of the COVID-19 pandemic. This study seeks to leverage high-throughput, multiplexed serologic assays, which have been adopted as benchmarks for vaccine efficacy, to support large-scale surveys of SARS-CoV-2 immunity using finger-stick blood and/or saliva. Specifically, we optimized MSD's serology assays, which were analytically validated for serum, to test self-collected finger-stick blood and saliva samples to identify prior infection. We show that these assays can be used with FDA-registered specimen collection devices to obtain quantitative measurements for self-collected samples. First, we show that salivary antibodies are stable without refrigeration or preservatives for at least 5 days. We selected classification thresholds for antibodies against SARS-CoV-2 N, RBD and Spike in finger-stick blood and saliva that provided 98% specificity in a set of individuals without known COVID-19 exposure. Using matched samples, we show that testing of saliva and finger-stick blood equivalently identified individuals with humoral responses to CoV-2 antigens. Moreover, we piloted a simple saliva collection kit that can be used to safely send samples through the mail using written instructions only. This work establishes key parameters to robustly assay self-collected finger-stick blood and saliva using quantitative immunoassays that could support large-scale serology testing.

Comparing the Morphologies and Adsorption Behavior of Electrospun Polystyrene Composite Fibers with 0D Fullerenes, 1D Multiwalled Carbon Nanotubes and 2D Graphene Oxides

Abstract: Nanoscale adsorbents with unique engineered morphologies give them properties that can be transformative for water treatment. Unlike bulk-scale and top-down sorbents such as activated carbon, bottom-up nanoscale adsorbents dispersed into water are difficult to recover from water unless enmeshed in macro-scale architectures. Electrospinning is a facile and scalable method of immobilizing nanomaterials (NM) including fullerenes (C60), multi-walled carbon nanotubes (MWCNT) and graphene oxide (GO) into non-woven, flexible polymeric fabric architectures. In this study, electrospinning was used to compare three types of NM-polystyrene (PS) composites. The integration of NMs into electrospun fibers created pores, increased fiber diameter, decreased polymer beading and maintained fibers’ surface pore size distribution for all composites. The scanning electron microscopy inspection indicated that GO in electrospun PS coated the surface of the fibers. This was attributed to the 2D sheet like structure of GO that was pushed outside by the evaporating organic solvent during electrospinning. Phenanthrene adsorption experiments indicated that GO preserved adsorptive properties when incorporated into PS whereas MWCNT and C60 did not. The restricted adsorption of MWCNT and C60 was caused by the concealing of NMs within the PS filaments. On the other, partial exposure of GO surfaces enabled adsorption of phenanthrene by GO. Despite the similarities in pore formation and increased diameter when NMs are incorporated into electrospun PS, the type, and morphological properties of the NMs played a critical role on their application potential as an adsorbent for water treatment. Further advances in fiber synthesis are needed such as higher NM loadings in fibers, partial exposure without compromising the composite integrity and continuous pores that allow pollutant access to NM surfaces where adsorption occurs.

The role of temperature and microclimate in the survival of wintering grassland birds

Abstract: Pérez-Ordoñez, D. J., M. Titulaer, M. D. Correll, E. H. Strasser, F. Baeza-Tarin, R. L. Martin, and L. A. Harveson. 2022. The role of temperature and microclimate in the survival of wintering grassland birds. Avian Conservation and Ecology 17(1):1. https://doi.org/10.5751/ACE-02010-170101

Computational Modeling of Voice Production Using Excised Canine Larynx.

Abstract: A combined experimental-numerical work was conducted to comprehensively validate a subject-specific continuum model of voice production in larynx using excised canine laryngeal experiments. The computational model is a coupling of the Navier-Stokes equations for glottal flow dynamics and a finite element model of vocal fold dynamics. The numerical simulations employed a cover-body vocal fold structure with the geometry reconstructed from magnetic resonance imaging scans and the material properties determined through an optimization-based inverse process of experimental indentation measurement. The results showed that the simulations predicted key features of the dynamics observed in the experiments, including the skewing of the glottal flow waveform, mucosal wave propagation, continuous increase of the divergent angle and intraglottal swirl strength during glottal closing, and flow recirculation between glottal jet and vocal fold. The simulations also predicted the increase of the divergent angle, glottal jet speed, and intraglottal flow swirl strength with the subglottal pressure, same as in the experiments. Quantitatively, the simulations over-predicted the frequency and jet speed and under-predicted the flow rate and divergent angle for the larynx under study. The limitations of the model and their implications were discussed.

Robust Estimation of 1/f Activity Improves Oscillatory Burst Detection

Abstract: Abstract Neural oscillations often occur as transient bursts with variable amplitude and frequency dynamics. Quantifying these effects is important for understanding brain-behaviour relationships, especially in continuous datasets. To robustly measure bursts, rhythmical periods of oscillatory activity must be separated from arrhythmical background 1/f activity, which is ubiquitous in electrophysiological recordings. The Better OSCillation (BOSC) framework achieves this by defining a power threshold above the estimated background 1/f activity, combined with a duration threshold. Here we introduce a modification to this approach called fBOSC which uses a spectral parametrisation tool to accurately model background 1/f activity in neural data. fBOSC (which is openly available as a MATLAB toolbox) is robust to power spectra with oscillatory peaks and can also model non-linear spectra. Through a series of simulations, we show that fBOSC more accurately models the 1/f power spectrum compared with existing methods. fBOSC was especially beneficial where power spectra contained a “knee” below ∼0.5-10 Hz, which is typical in neural data. We also found that, unlike other methods, fBOSC was unaffected by oscillatory peaks in the neural power spectrum. Moreover, by robustly modelling background 1/f activity, the sensitivity for detecting oscillatory bursts was standardised across frequencies (e.g. theta- and alpha-bands). Finally, using openly available resting state magnetoencephalography and intracranial electrophysiology datasets, we demonstrate the application of fBOSC for oscillatory burst detection in the theta-band. These simulations and empirical analyses highlight the value of fBOSC in detecting oscillatory bursts, including in datasets that are long and continuous with no distinct experimental trials. GRAPHICAL ABSRACT To determine a power threshold for burst detection, the Better OSCillation framework (BOSC) estimates background 1/f activity by modelling neural power spectra. Here we introduce a modification, termed fBOSC, to more robustly estimate 1/f activity in situations with prominent oscillatory peaks and/or the presence of a non-linear “knee” in the power spectrum. This was shown to standardise burst detection across frequency bands in both simulated and empirical data.

Sustainable waste management solutions for the foodservice industry: A Delphi study

Abstract: Foodservice businesses influence the sustainability of their natural environment by producing significant amounts of waste. Yet, research has, thus far, been dominated by studies that limit their scope to food waste alone. Few studies have taken a broader look at sustainable waste initiatives, including innovative waste processing techniques, with a view to constructing management indicators for foodservices. This study combines management innovation practices related to resource management, waste prevention, processing and disposal techniques, and stakeholder involvement to offer sustainable standards. It primarily adopts the Delphi technique to propose specific solutions pertaining to waste management. Experts from government, industry, and academia reveal that potential waste management initiatives comprise three facets - service, process (operational), and organisational practices and innovations, 15 sub-facets and 41 indicators. This study thus establishes a catalogue of solutions for food, packaging and other 'non-food' waste that foodservice establishments can implement. In addition to its practical implications, an important contribution is its focus on management systems to establish waste management standards for hospitality, food and beverage (F&B) services, restaurants, and non-commercial catering.

Hydrogenation of 2-methylnaphthalene over bi-functional Ni catalysts

Abstract: Nickel catalysts were synthesized by incipient wetness impregnation and coprecipitation and compared to a commercial Ni/kieselguhr catalyst for selective hydrogenation of 2-methylnaphthalene to yield methyldecalin. The catalysts were characterized using N2 physisorption, TGA, XRD, and TEM. The apparent activation energy for hydrogenation depends on the support identity, with the highest value (87 kJ/mol) obtained for Ni/SiO2-Al2O3 and the lowest (30 kJ/mol) for Ni/kieselguhr. The selectivity to cis-/trans-methyldecalin varied as a function of both catalyst identity and reaction conditions, with high selectivity to cis-methyldecalin obtained using catalysts with higher Ni loadings and at lower reaction temperatures. The impregnation of a precious metal onto coprecipitated Ni catalysts also changed their selectivity, as catalysts containing ruthenium selectively formed cis-methyldecalin, whereas platinum catalysts produced mostly trans-methyldecalin. This research demonstrates that Ni catalysts can be useful for producing inexpensive catalysts for hydrogenation of polyaromatic-containing feedstocks.

Delegating Responsibility

Abstract: Delegating Responsibility explores the politics of migration in the European Union and explains how the EU responded to the 2015–17 refugee crisis. Based on 86 interviews and fieldwork in Greece and Italy, Nicholas R. Micinski proposes a new theory of international cooperation on international migration. States approach migration policies in many ways—such as coordination, collaboration, subcontracting, and unilateralism—but which policy they choose is based on capacity and on credible partners on the ground. Micinski traces the fifty-year evolution of EU migration management, like border security and asylum policies, and shows how EU officials used “crises” as political leverage to further Europeanize migration governance. In two in-depth case studies, he explains how Italy and Greece responded to the most recent refugee crisis. He concludes with a discussion of policy recommendations regarding contemporary as well as long-term aspirations for migration management in the EU.

Uncovering a new form of digitally-enabled agility: an improvisational perspective

Abstract: Agile organisations address changes with ease and speed. These changes are tackled through the concept of ongoing agility, using a sense-respond process, composed of sensing, decision-making, and acting. Increasingly, however, unexpected events require a different agility response. In this study, we propose and empirically examine how improvisational agility – conceptualised as organisation improvisational capability, the ability to sense and respond to unexpected events with speed and creativity – is a type of agility better suited for unanticipated events. Specifically, we focus on the improvisational agility sense-respond process. Using four exploratory cases, we find that organisations can leverage existing ongoing agility mechanisms for improvisational agility and, through learning, can leverage improvisational agility in ongoing agility. We also explain how different components of information management capability support improvisational agility, depending on the unexpected events and the need for speed or creativity.

A ¹⁰ Be Moraine Chronology of the Last Glaciation and Termination at 49°N in the Mongolian Altai of Central Asia

Abstract: Determining what caused the global Last Glaciation and last glacial termination, despite opposing orbital summer insolation signatures between the polar hemispheres, remains a puzzle of paleoclimatology. This problem can be addressed by comparing chronologies of glaciation from different latitudes and different climatic regimes in both hemispheres. Here, we present a 10Be surface-exposure chronology of glacial landforms constructed during and since the local Last Glaciation in the continental environment of Central Asia in the high Mongolian Altai (49°N, 88°E). Four belts of lateral moraines document maximal phases of the former Khoton glacier at 35,440 ± 980 years ago, 23,430 ± 850 years ago, 20,780 ± 610 years ago, and 19,520 ± 550 years ago. Our chronology indicates that deglaciation from these maximal positions began as early as 18,810 ± 510 years ago, was well underway by 17,680 ± 510 years ago, and was nearly completed by 16,040 ± 490 years ago. Overall, our chronology shows that glaciation in western Mongolia overlapped with the global Last Glacial Maximum and that extensive recession from glacial-to-interglacial limits took place early in the last glacial termination during Heinrich Stadial 1. Khoton Nuur deglaciation led the demise of large Northern Hemisphere ice sheets and increases in radiative forcing agents by several millennia. We suggest that this rapid switch in the mode of glaciation implies the involvement of an additional climatic factor that could have produced locally rapid warming and deglaciation ∼18,800–16,000 years ago.

Stock return asymmetry in China

Abstract: In this study, we find that the upside asymmetry calculated based on a new distribution-based asymmetry measure proposed by Jiang et al. (2020) is negatively related to average future returns in the cross-section of Chinese stock returns. Conversely, when using the conventional skewness measure, the relationship between asymmetry and the average returns is unclear. Furthermore, an asymmetry factor constructed from the new asymmetry measure cannot be explained by the three- (CH-3) or four-factor (CH-4) models proposed by Liu et al. (2019). When augmenting the CH-3 model with our asymmetry factor, the augmented four-factor model can explain 32 anomalies out of a universe of 37 significant anomalies in the Chinese stock market, outperforming both the CH-3 and CH-4 models.

Insights into the adipose stem cell niche in health and disease

Abstract: Stem cell self-renewal and differentiation are supported by the neighboring microenvironment, which is referred to as the stem cell “niche.” The adipose tissue stem cell niche comprises multiple cell types that regulate adipocyte precursor function, including endothelial cells, immune cells, mural cells, and adipocytes that interact directly or indirectly with adipocyte precursors to control their self-renewal or differentiation into adipocytes. We are only beginning to understand the mechanisms by which the niche is maintained and coordinated to support adipocyte precursor function, which is critical for proper regulation of adipose tissue homeostasis. An understanding of adipocyte precursor renewal and differentiation is particularly challenging for human studies owing to the lack of appropriate surface receptors for their identification, suitable culture conditions for ex vivo expansion, and the inability to perform many types of in vivo studies as are performed in rodent models. This chapter will review the current state of knowledge concerning adipocyte precursors within the adipose stem cell niche, including their identification, cell–cell interactions, factors that promote their renewal and commitment toward adipocytes, and the changes they undergo during obesity and aging.

Sorting of Poly-Disperse Particle by Entrapment Using Liquid Carrier System

Abstract: A thin viscous layer is found over a substrate when it is immersed in a polymer solution. The layer thickness depends on the polymer and solvent type, their volume fraction, and the substrate. If the liquid solution contains particles, they are entrapped on the viscous polymer layer, acting as the binder. The trade-off between the viscous force and the centrifugal force on the particle determines the entrapment. Furthermore, the size of entrained particles are dictated by the binder concentration of the solution., A particle filtration technique is presented using the entrapment phenomenon from a poly-disperse mixture. A dimensionless number called the entrapment factor is introduced to correlate the particle entrapment with various parameters. By changing the entrapment factor, three distinct entrapment regimes are achieved and explained from a poly-disperse mixture. The experimental result shows that entrapped particles become larger as the factor increases, which can be controlled with multiple parameters of the dipping process. The proposed technique can lead to a filtration process of the wide-range poly-disperse particle mixture over the capillary filtration processes.

LiDAR Measurements of Wind Shear Exponents and Turbulence Intensity Offshore the Northeast United States

Abstract: Abstract This paper presents wind speed shear exponents and turbulence intensity (TI) measurements collected from light imaging, detection, and ranging instruments (LiDARs) measuring wind speeds from 40 m to 200 m above sea level and provides comparisons to industry design guidelines. The high-altitude wind speed data are unique and represent some of the first measurements made offshore in this part of the country, which is actively being developed for offshore wind. The data are used to support the New England Aqua Ventus I Floating Offshore Wind Farm to be located 17 km offshore the Northeast United States. Multiple LiDAR measurements were made using a DeepCLiDAR floating buoy and LiDARs located on a nearby island. The measured wind speed shear exponents are compared against industry standard mesoscale model outputs and offshore design codes including the American Bureau of Shipping, American Petroleum Institute, and Det Norske Veritas-Germanischer Lloyd guides. Significant variation in the vertical wind speed profile occurs throughout the year which is not addressed in design standards. Additionally, TI measurements made from the LiDAR, although not widely accepted in the scientific community, are presented and compared against industry guidelines.

A global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5

Abstract: Abstract. Marine particles of different nature are found throughout the global Ocean. The term "marine particles" describes detritus aggregates, fecal pellets, but also bacterio-, phyto-, zooplankton and nekton. Here we present a global particle size distribution dataset obtained with several Underwater Vision Profiler 5 (UVP5) camera systems. Overall, within the 64 μm to about 50 mm size range covered by the UVP5, detrital particles are the most abundant component of all marine particles in this size range and thus measurements of the particle size distribution with the UVP5 can yield important information on detrital particle dynamics. During deployment, which is possible down to 6000 m depth, the UVP5 images a volume of about 1 L at a frequency of 6 to 20 Hz. Each image is segmented in real time and size measurements of particles are automatically stored. All UVP5 units used to generate the here presented dataset were inter-calibrated using a UVP5 High Definition unit as reference. Our consistent particle size distribution dataset contains 8805 vertical profiles collected between 2008-06-19 and 2020-11-23. All major ocean basins, as well as the Mediterranean and the Baltic Sea were sampled. 19 % of all profiles had a maximum sampling depth shallower than 200 dbar, 80 % had a maximum sampling depth greater than 200 dbar, 38 % sampled at least the upper 1000 dbar depth range and 11 % went down to at least 3000 dbar depth. First analysis of the particle size distribution dataset shows that particle abundance is found to be high at high latitudes and in coastal areas where surface productivity or continental inputs are elevated. Lowest values are found in the deeep ocean and in the oceanic gyres. Our dataset should be valuable for more in-depth studies that focus on the analysis of regional, temporal and global patterns of particle size distribution and flux as well as for the development and adjustment of regional and global biogeochemical models. The marineparticle size distribution dataset (Kiko et al., 2021) is available at https://doi.pangaea.de/10.1594/PANGAEA.924375.