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    Slip Risk Prediction Using Intelligent Insoles and a Slip Simulator
    (Multidisciplinary Digital Publishing Institute, 2023-10-24) Xu, Shou; Khan, Md Javed Imtiaze; Khaleghian, Meysam; Emami, Anahita
    Slip and fall accidents are the leading cause of injuries for all ages, and for fatal injuries in adults over 65 years. Various factors, such as floor surface conditions and contaminants, shoe tread patterns, and gait behavior, affect the slip risk. Moreover, the friction between the shoe outsoles and the floor continuously changes as their surfaces undergo normal wear over time. However, continuous assessment of slip resistance is very challenging with conventional measurement techniques. This study addresses this challenge by introducing a novel approach that combines sensor fusion technology and machine learning techniques to create intelligent insoles designed for fall risk prediction. In addition, a state-of-the-art slip simulator, capable of mimicking the foot’s motion during a slip, was developed and utilized for the assessment of slipperiness between various shoes and floor surfaces. Data acquisition involved the collection of pressure data and three-axial accelerations using instrumented shoe insoles, complemented by friction coefficient measurements via the slip simulator. The collected dataset includes four types of shoes, three floor surfaces, and four surface conditions, including dry, wet, soapy, and oily. After preprocessing of the collected dataset, the simulator was used to train five different machine learning algorithms for slip risk classification. The trained algorithms provided promising results for slip risk prediction for different conditions, offering the potential to be employed in real-time slip risk prediction and safety enhancement.
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    Development of Shortened miR-506-3p Mimics Exhibiting Strong Differentiation-Inducing Activity in Neuroblastoma Cells
    (Multidisciplinary Digital Publishing Institute, 2023-08-28) Mesa-Diaz, Nakya; Smith, Mitchell T.; Cardus, Daniela F.; Du, Liqin
    microRNA mimics are synthetic RNA molecules that imitate the mature miRNA duplexes and their functions. These mimics have shown promise in treating cancers. Nucleotide chemical modifications of microRNA mimics have been investigated and have improved the stability of miRNA mimics. However, the potential therapeutic benefit of mimic analogs based on sequence modifications has not been explored. miR-506-3p was identified as a differentiation-inducing microRNA in neuroblastoma cells, suggesting the potential of applying the miR-506-3p mimic in neuroblastoma differentiation therapy. In this study, we explored the possibility of developing shortened miR-506-3p analogs that can maintain differentiation-inducing activities comparable to the wild-type miR-506-3p mimic. We found that deleting up to two nucleotides at either the 30 end or within the middle region of the miR-506-3p sequence fully maintained the differentiation-inducing activity when compared to the wild-type mimic. Deleting up to four nucleotides from the 30 end or deleting three nucleotides in the middle positions diminished the differentiation-inducing activity, but the analogs still maintained differentiation-inducing activities that were significantly higher than the negative control oligo. The shortened analog designs potentially benefit patients from two perspectives: (1) the reduced cost of manufacturing shortened analogs, and (2) the reduced non-specific toxicity due to their smaller molecular sizes.
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    The Megaflora from the Quantico Locality (Upper Albian), Lower Cretaceous Potomac Group of Virginia
    (Virginia Museum of Natural History, 1994-01-01) Upchurch, Garland R.; Crane, Peter R.; Drinnan, Andrew N.
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    Pairwise comparative analysis of six haplotype assembly methods based on users’ experience
    (BioMed Central Ltd., 2023-06-29) Sun, Shuying; Cheng, Flora; Han, Daphne; Wei, Sarah; Zhong, Alice; Massoudian, Sherwin; Johnson, Alison B.
    Background: A haplotype is a set of DNA variants inherited together from one parent or chromosome. Haplotype information is useful for studying genetic variation and disease association. Haplotype assembly (HA) is a process of obtaining haplotypes using DNA sequencing data. Currently, there are many HA methods with their own strengths and weaknesses. This study focused on comparing six HA methods or algorithms: HapCUT2, MixSIH, PEATH, WhatsHap, SDhaP, and MAtCHap using two NA12878 datasets named hg19 and hg38. The 6 HA algorithms were run on chromosome 10 of these two datasets, each with 3 filtering levels based on sequencing depth (DP1, DP15, and DP30). Their outputs were then compared. Result: Run time (CPU time) was compared to assess the efficiency of 6 HA methods. HapCUT2 was the fastest HA for 6 datasets, with run time consistently under 2 min. In addition, WhatsHap was relatively fast, and its run time was 21 min or less for all 6 datasets. The other 4 HA algorithms’ run time varied across different datasets and coverage levels. To assess their accuracy, pairwise comparisons were conducted for each pair of the six packages by generating their disagreement rates for both haplotype blocks and Single Nucleotide Variants (SNVs). The authors also compared them using switch distance (error), i.e., the number of positions where two chromosomes of a certain phase must be switched to match with the known haplotype. HapCUT2, PEATH, MixSIH, and MAtCHap generated output files with similar numbers of blocks and SNVs, and they had relatively similar performance. WhatsHap generated a much larger number of SNVs in the hg19 DP1 output, which caused it to have high disagreement percentages with other methods. However, for the hg38 data, WhatsHap had similar performance as the other 4 algorithms, except SDhaP. The comparison analysis showed that SDhaP had a much larger disagreement rate when it was compared with the other algorithms in all 6 datasets. Conclusion: The comparative analysis is important because each algorithm is different. The findings of this study provide a deeper understanding of the performance of currently available HA algorithms and useful input for other users.
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    Filtering Eye-Tracking Data from an EyeLink 1000: Comparing Heuristic, Savitzky-Golay, IIR and FIR Digital Filters
    (2023-03) Raju, Mehedi H.; Friedman, Lee; Bouman, Troy M.; Komogortsev, Oleg
    In a previous report (Raju et al.,2023) we concluded that, if the goal was to preserve events such as saccades, microsaccades, and smooth pursuit in eye-tracking recordings, data with sine wave frequencies less than 100 Hz (-3db) were the signal and data above 100 Hz were noise. We compare 5 filters in their ability to preserve signal and remove noise. Specifically, we compared the proprietary STD and EXTRA heuristic filters provided by our EyeLink 1000 (SR-Research, Ottawa, Canada), a Savitzky-Golay (SG) filter, an infinite impulse response (IIR) filter (low-pass Butterworth), and a finite impulse filter (FIR). For each of the non-heuristic filters, we systematically searched for optimal parameters. Both the IIR and the FIR filters were zero-phase filters. Mean frequency response profiles and amplitude spectra for all 5 filters are provided. In addition, we examined the effect of our filters on a noisy recording. Our FIR filter had the sharpest roll-off of any filter. Therefore, it maintained the signal and removed noise more effectively than any other filter. On this basis, we recommend the use of our FIR filter. Several reports have shown that filtering increased the temporal autocorrelation of a signal. To address this, the present filters were also evaluated in terms of autocorrelation (specifically the first 3 lags). Of all our filters, the STD filter introduced the least amount of autocorrelation.
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    Determining Which Sine Wave Frequencies Correspond to Signal and Which Correspond to Noise in Eye-Tracking Time-Series
    (2022-01) Raju, Mehedi H.; Friedman, Lee; Bouman, Troy M.; Komogortsev, Oleg
    The Fourier theorem proposes that any time-series can be decomposed into a set of sinusoidal frequencies, each with its own phase and amplitude. The literature suggests that some of these frequencies are important to reproduce key qualities of eye-movements (``signal'') and some of these frequencies are not important (``noise''). We looked at three types of analysis: (1) visual inspection of plots of saccade, microsaccade and smooth pursuit exemplars; (2) an analysis of the percentage of variance accounted for (PVAF) in each of 1,033 unfiltered saccade trajectories by each frequency cutoff; (3) an analysis of saccade peak velocity in the unfiltered and various filtered conditions. Visual inspection suggested that frequencies up to 75 Hz are required to represent microsaccades. Our PVAF analysis indicated that data in the 0-25 Hz band are sufficient to account for nearly 100% of the variance in unfiltered saccade trajectories. Our analysis indicated that frequencies below 100 Hz are sufficient to maintain peak velocities. Therefore, our overall conclusion is that to maintain eye-movement signal and reduce noise, a cutoff frequency of 100 Hz is appropriate. Our results have implications for the proposed sampling rate of eye-tracking recordings. If one is working in the frequency domain and 100 Hz needs to be preserved, the minimum required sampling rate would be 200 Hz. However, in a time domain analysis, a minimum 1000 Hz sampling rate is required.
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    (2022-11) Friedman, Lee
    This is the site where Friedman and Komogortsev introduce and document a new method for the classification of eye movements (fixation, saccades and PSOs). This article is a complete description of the substantive functions of the Friedman-Komogortsev Method (FKM).
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    Relationships between Physical, Mechanical and Acoustic Properties of Asphalt Mixtures Using Ultrasonic Testing
    (Multidisciplinary Digital Publishing Institute, 2022-03-04) Hou, Shuguang; Deng, Yong; Jin, Rui; Shi, Xijun; Luo, Xue
    Ultrasonic testing can be used for a nondestructive and rapid determination of material properties. In this study, twelve asphalt mixture samples of four different types were fabricated and used in conventional material property tests and two ultrasonic wave tests. Physical properties such as bulk specific gravity and air void content, mechanical properties such as dynamic modulus and phase angle, and acoustic properties such as wave velocity were measured. Relationships between these properties were established and analyzed as a tool for the future material property determination. In addition, the dynamic modulus and phase angle, measured in a standard laboratory test, were used to construct two master curve models to predict their values at arbitrary temperatures and frequencies. Furthermore, a theoretical model for wave velocity in a linear isotropic viscoelastic material was utilized with measured density, Poisson’s ratio, phase angle and ultrasonic wave velocity to predict the dynamic modulus. Good agreement has been achieved between laboratory measurements and model predictions. It indicates that ultrasonic testing can serve as a rapid method for material property determination.
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    Correlated Electrical Conductivities to Chemical Configurations of Nitrogenated Nanocrystalline Diamond Films
    (Multidisciplinary Digital Publishing Institute, 2022-03-03) Zkria, Abdelrahman; Gima, Hiroki; Abubakr, Eslam; Mahmoud, Ashraf; Haque, Ariful; Yoshitake, Tsuyoshi
    Diamond is one of the fascinating films appropriate for optoelectronic applications due to its wide bandgap (5.45 eV), high thermal conductivity (3320 W m−1·K−1), and strong chemical stability. In this report, we synthesized a type of diamond film called nanocrystalline diamond (NCD) by employing a physical vapor deposition method. The synthesis process was performed in different ratios of nitrogen and hydrogen mixed gas atmospheres to form nitrogen-doped (n-type) NCD films. A high-resolution scanning electron microscope confirmed the nature of the deposited films to contain diamond nanograins embedded into the amorphous carbon matrix. Sensitive spectroscopic investigations, including X-ray photoemission (XPS) and near-edge X-ray absorption fine structure (NEXAFS), were performed using a synchrotron beam. XPS spectra indicated that the nitrogen content in the film increased with the inflow ratio of nitrogen and hydrogen gas (IN/H). NEXAFS spectra revealed that the σ*C–C peak weakened, accompanied by a π*C=N peak strengthened with nitrogen doping. This structural modification after nitrogen doping was found to generate unpaired electrons with the formation of C–N and C=N bonding in grain boundaries (GBs). The measured electrical conductivity increased with nitrogen content, which confirms the suggestion of structural investigations that nitrogen-doping generated free electrons at the GBs of the NCD films.
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    Fly Ash-Added, Seawater-Mixed Pervious Concrete: Compressive Strength, Permeability, and Phosphorus Removal
    (Multidisciplinary Digital Publishing Institute, 2022-02-14) Hwang, Sangchul; Yeon, Jung Heum
    A mix proportion of off-spec fly ash (FA)-added, seawater-mixed pervious concrete (SMPC) was optimized for compressive strength and permeability and then the optimized SMPC was tested for the rate and extent of aqueous phosphorus removal. An optimum mix proportion was obtained to attain the percentages (% wt.) of FA-to-binder at 15.0%, nano SiO2 (NS)-to-FA at 3.0%, liquid-to-binder at 0.338, and water reducer-to-binder at 0.18% from which a 7-day compressive strength of 14.0 MPa and a permeability of 5.5 mm/s were predicted. A long-term maximum compressive strength was measured to be ~16 MPa for both the optimized SMPC and the control ordinary pervious concrete (Control PC). The phosphorus removal was favorable for both the optimized SMPC and the Control PC based on the dimensionless Freundlich parameter (1/n). Both the optimized SMPC and Control PC had a first-order phosphorus removal constant of ~0.03 h−1. The optimized SMPC had a slightly lower capacity of phosphorus removal than the Control PC based on the Freundlich constant, Kf (mg1−1/n kg−1 L1/n): 15.72 for the optimized SMPC vs. 16.63 for Control. This study demonstrates a cleaner production and application of off-spec FA-added, seawater-mixed pervious concrete to simultaneously attain water, waste, and concrete sustainability.
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    Microfluidic Rheometry and Particle Settling: Characterizing the Effect of Polymer Solution Elasticity
    (Multidisciplinary Digital Publishing Institute, 2022-02-09) Faroughi, Salah; Del Giudice, Francesco
    The efficient transport of solid particles using polymeric fluids is an important step in many industrial operations. Different viscoelastic fluids have been designed for this purpose, however, the effects of elasticity have not been fully integrated in examining the particle-carrying capacity of the fluids. In this work, two elastic fluid formulations were employed to experimentally clarify the effect of elasticity on the particle drag coefficient as a proxy model for measuring carrying capacity. Fluids were designed to have a constant shear viscosity within a specific range of shear rates, ẏ < 50 (1/s), while possessing distinct (longest) relaxation times to investigate the influence of elasticity. It is shown that for dilute polymeric solutions, microfluidic rheometry must be practiced to obtain a reliable relaxation time (as one of the measures of viscoelasticity), which is on the order of milliseconds. A calibrated experimental setup, furnished with two advanced particle velocity measurement techniques and spheres with different characteristics, was used to quantify the effect of elasticity on the drag coefficient. These experiments led to a unique dataset in moderate levels of Weissenberg numbers, 0 < Wi < 8.5. The data showed that there is a subtle reduction in the drag coefficient at low levels of elasticity (Wi<1), and a considerable enhancement at high levels of elasticity (Wi > 1). The experimental results were then compared with direct numerical simulation predictions yielding R2 = 0.982. These evaluations endorse the numerically quantified behaviors for the drag coefficient to be used to compare the particle-carrying capacity of different polymeric fluids under different flow conditions.
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    An Updated Review of Hypotheses Regarding Bat Attraction to Wind Turbines
    (Multidisciplinary Digital Publishing Institute, 2022-01-31) Guest, Emma; Stamps, Brittany; Durish, Nevin; Hale, Amanda; Hein, Cris D.; Morton, Brogan; Weaver, Sara; Fritts, Sarah R.
    Patterns of bat activity and mortalities at wind energy facilities suggest that bats are attracted to wind turbines based on bat behavioral responses to wind turbines. For example, current monitoring efforts suggest that bat activity increases post-wind turbine construction, with bats making multiple passes near wind turbines. We separated the attraction hypothesis into five previously proposed explanations of bat interactions at or near wind turbines, including attraction based on noise, roost sites, foraging and water, mating behavior, and lights, and one new hypothesis regarding olfaction, and provide a state of the knowledge in 2022. Our review indicates that future research should prioritize attraction based on social behaviors, such as mating and scent-marking, as this aspect of the attraction hypothesis has many postulates and remains the most unclear. Relatively more data regarding attraction to wind turbines based on lighting and noise emission exist, and these data indicate that these are unlikely attractants. Analyzing attraction at the species-level should be prioritized because of differences in foraging, flight, and social behavior among bat species. Lastly, research assessing bat attraction at various scales, such as the turbine or facility scale, is lacking, which could provide important insights for both wind turbine siting decisions and bat mortality minimization strategies. Identifying the causes of bat interactions with wind turbines is critical for developing effective impact minimization strategies.
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    Gender and Sanitation: Women’s Experiences in Rural Regions and Urban Slums in India
    (Multidisciplinary Digital Publishing Institute, 2022-01-30) Vogel, Wren; Hwang, Christina; Hwang, Sangchul
    Without adequate sanitation facilities, environmental, social, and health risks are common and worsen as the state of sanitation stagnates. Vulnerable groups, specifically women, are unequally affected by poor sanitation. Attitudes towards and perceptions of gender and menstruation have created a health and social discrepancy between women and men. Women must undergo additional obstacles when practicing proper sanitation and managing menstruation. This article utilizes the sanitation insecurity measure to assess the lived experience of women in rural and urban India. This article also discusses accounts of women’s experiences managing menstruation in both the rural regions and urban slums of India and discusses the social implications of the state of sanitation. Examining the issue of sanitation by focusing on menstruation and the dichotomy of men’s and women’s experiences with sanitation and hygiene will indicate that achieving gender equity requires sanitation to be viewed as a human rights, social justice, and education issue.
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    A Meta-Model to Predict the Drag Coefficient of a Particle Translating in Viscoelastic Fluids: A Machine Learning Approach
    (Multidisciplinary Digital Publishing Institute, 2022-01-21) Faroughi, Salah; Roriz, Ana; Fernandes, Celio
    This study presents a framework based on Machine Learning (ML) models to predict the drag coefficient of a spherical particle translating in viscoelastic fluids. For the purpose of training and testing the ML models, two datasets were generated using direct numerical simulations (DNSs) for the viscoelastic unbounded flow of Oldroyd-B (OB-set containing 12,120 data points) and Giesekus (GI-set containing 4950 data points) fluids past a spherical particle. The kinematic input features were selected to be Reynolds number, 0
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    Do Females in a Unisexual-Bisexual Species Complex Differ in Their Behavioral Syndromes and Cortisol Production?
    (Multidisciplinary Digital Publishing Institute, 2021-03-03) Muraco, James J.; Monroe, Dillon J.; Aspbury, Andrea S.; Gabor, Caitlin R.
    Studies of suites of correlated behavioral traits (i.e., behavioral syndromes) aid in understanding the adaptive importance of behavioral evolution. Behavioral syndromes may be evolutionarily constrained, preventing behaviors from evolving independently, or they may be an adaptive result of selection on the correlation itself. We tested these hypotheses by characterizing the behavioral syndromes in two sympatric, closely related species and testing for differences between the species. We studied the unisexual Amazon molly (Poecilia formosa) and one of its bisexual, parent species, the sailfin molly (P. latipinna). Sympatric female sailfin and Amazon mollies compete for mating which could affect the behavioral syndromes found in each species. We identified a behavioral syndrome between exploration and activity in both species that did not differ between species. Additionally, we explored the relationship between a stress response hormone, cortisol, and behavioral type, and did not detect a relationship. However, P. formosa differed from P. latipinna in their cortisol release rates. Behavioral syndromes may be constrained in this complex, aiding in mate acquisition for P. formosa by virtue of having a similar behavioral type to P. latipinna. The difference between the females in cortisol release rates may be a useful mate identification cue for males to offset higher mating mistakes associated with the similar behavioral types.
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    Fly Ash-Based Eco-Efficient Concretes: A Comprehensive Review of the Short-Term Properties
    (Multidisciplinary Digital Publishing Institute, 2021-07-30) Amran, Mugahed; Fediuk, Roman; Murali, Gunasekaran; Avudaiappan, Siva; Ozbakkaloglu, Togay; Vatin, Nikolai; Karelina, Maria; Klyuev, Sergey; Gholampour, Aliakbar
    Development of sustainable concrete as an alternative to conventional concrete helps in reducing carbon dioxide footprint associated with the use of cement and disposal of waste materials in landfill. One way to achieve that is the use of fly ash (FA) as an alternative to ordinary Portland cement (OPC) because FA is a pozzolanic material and has a high amount of alumina and silica content. Because of its excellent mechanical properties, several studies have been conducted to investigate the use of alkali-activated FA-based concrete as an alternative to conventional concrete. FA, as an industrial by-product, occupies land, thereby causing environmental pollution and health problems. FA-based concrete has numerous advantages, such as it has early strength gaining, it uses low natural resources, and it can be configurated into different structural elements. This study initially presents a review of the classifications, sources, chemical composition, curing regimes and clean production of FA. Then, physical, fresh, and mechanical properties of FA-based concretes are studied. This review helps in better understanding of the behavior of FA-based concrete as a sustainable and eco-friendly material used in construction and building industries.
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    First and Second Law Thermodynamic Analyses of Hybrid Nanofluid with Different Particle Shapes in a Microplate Heat Exchanger
    (Multidisciplinary Digital Publishing Institute, 2021-08-10) Garud, Kunal; Hwang, Seong-Guk; Lim, Taek-Kyu; Kim, Namwon; Lee, Moo-Yeon
    The improvement in the quantitative and qualitative heat transfer performances of working fluids is trending research in the present time for heat transfer applications. In the present work, the first and second law analyses of a microplate heat exchanger with single-particle and hybrid nanofluids are conducted. The microplate heat exchanger with single-particle and hybrid nanofluids is analyzed using the computational fluid dynamics approach with symmetrical heat transfer and fluid flow analyses. The single-particle Al2O3 nanofluid and the hybrid Al2O3/Cu nanofluid are investigated for different nanoparticles shapes of sphere (Sp), oblate spheroid (OS), prolate spheroid (PS), blade (BL), platelet (PL), cylinder (CY) and brick (BR). The first law characteristics of NTU, effectiveness and performance index and the second characteristics of thermal, friction and total entropy generation rates and Bejan number are compared for Al2O3 and Al2O3/Cu nanofluids with considered different-shaped nanoparticles. The OS- and PL-shaped nanoparticles show superior and worse first and second law characteristics, respectively, for Al2O3 and Al2O3/Cu nanofluids. The hybrid nanofluid presents better first and second law characteristics compared to single-particle nanofluid for all nanoparticle shapes. The Al2O3/Cu nanofluid with OS-shaped nanoparticles depicts maximum values of performance index and Bejan number as 4.07 and 0.913, respectively. The first and second law characteristics of the best combination of the Al2O3/Cu nanofluid with OS-shaped nanoparticles are investigated for various volume fractions, different temperature and mass flow rate conditions of hot and cold fluids. The first and second law characteristics are optimum at higher hot fluid temperature, lower cold fluid temperature, lower hot and cold fluid mass flow rates. In addition, the first and second law characteristics have improved with increase in volume fraction.
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    Evaluation of Petroleum Resin in Rubberized Asphalt Binder
    (Multidisciplinary Digital Publishing Institute, 2021-08-19) Kim, Hyun Hwan; Mazumder, Mithil; Lee, Moon-Sup; Lee, Soon-Jae
    The crumb rubber modified (CRM) binder was evaluated considering the general operating temperatures of high, intermediate, and low temperatures. CRM binders were produced with four different contents (0, 5, 10, and 15%) using the base asphalt binder (PG64-22). Then, they were artificially aged by a rolling thin-film oven (RTFO) and pressure aging vessel (PAV). Superpave binder tests using a rotational viscometer (RV), dynamic shear rheometer (DSR), and bending beam rheometer (BBR) was applied to characterize the performance of the original and aged binders. Multiple stress creep recovery (MSCR) tests were also performed for deeper rutting characterization. The results of this study are as follows: (1) the presence of PR increases the binder viscosity, (2) the integration of CRM greatly improved the rutting resistance of the binder, and it was found that PR also improved the rutting characteristics, and (3) it is observed that PR is detrimental to the cracking properties of CRM binders.
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    An Initial Machine Learning-Based Victim’s Scream Detection Analysis for Burning Sites
    (Multidisciplinary Digital Publishing Institute, 2021-09-10) Saeed, Fairuz Samiha; Bashit, Abdullah Al; Viswanathan, Vishu; Valles, Damian
    Fire incidents are responsible for severe damage and thousands of deaths every year all over the world. Extreme temperatures, low visibility, toxic gases, and unknown locations of victims create difficulties and delays in rescue operations, escalating the risk of injury or death. It is time-critical to detect the victims trapped inside the burning sites for facilitating the rescue operations. This research work presents an audio-based automated system for victim detection in fire emergencies, investigating two machine learning (ML) methods: support vector machines (SVM) and long short-term memory (LSTM). The performance of these two ML techniques has been evaluated based on a variety of performance metrics. Our analyses show that both ML methods provide superior scream detection performance, with SVM slightly overperforming LSTM. Because of its lower complexity, SVM is a better candidate for real-time implementation in our autonomous embedded system vehicle (AESV).
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    Analysis of Health Care Billing via Quantile Variable Selection Models
    (Multidisciplinary Digital Publishing Institute, 2021-09-27) Ekin, Tahir; Damien, Paul
    Fraudulent billing of health care insurance programs such as Medicare is in the billions of dollars. The extent of such overpayments remains an issue despite the emerging use of analytical methods for fraud detection. This motivates policy makers to also be interested in the provider billing characteristics and understand the common factors that drive conservative and/or aggressive behavior. Statistical approaches to tackling this problem are confronted by the asymmetric and/or leptokurtic distributions of billing data. This paper is a first attempt at using a quantile regression framework and a variable selection approach for medical billing analysis. The proposed method addresses the varying impacts of (potentially different) variables at the different quantiles of the billing aggressiveness distribution. We use the mammography procedure to showcase our analysis and offer recommendations on fraud detection.