Showing papers by "Michigan Technological University published in 2022"
TL;DR: Wang et al. as mentioned in this paper presented a 25.4-Gb chromosome-level assembly of Chinese pine (Pinus tabuliformis) and revealed that its genome size is mostly attributable to huge intergenic regions and long introns with high transposable element (TE) content.
88 citations
TL;DR: In this article , the structural evolution of catalysts caused by the interplay with electric fields, electrolytes and reactants/intermediates brings about the formation of real active sites.
Abstract: Studying structure-activity correlations of electrocatalysts is essential for improving the conversion of electrical to chemical energy. Recently, increasing evidence obtained by operando characterization techniques reveal that the structural evolution of catalysts caused by the interplay with electric fields, electrolytes and reactants/intermediates brings about the formation of real active sites. Hence, it is time to summarize structural evolution related research advances and envisage future developments. In this Minireview, we first introduce the fundamental concepts associated with structural evolution (e.g., catalysts, active sites/centers and stability/lifetime) and their relevance. Then, the multiple triggers of structural evolution and advanced operando characterizations are discussed. Significantly, a brief overview of structural evolution and its reversibility in heterogeneous electrocatalysis is provided, especially for the representative electrocatalytic oxygen evolution reaction (OER) and CO2 reduction reaction (CO2 RR) processes. Lastly, key challenges and opportunities in this exciting field are highlighted.
76 citations
TL;DR: The core theme of this paper is to seek to treat CO2 as a commodity instead of a liability.
Abstract: CO2 utilizations are essential to curbing the greenhouse gas effect and managing the environmental pollutant in an energy-efficient and economically-sound manner. This paper seeks to critically analyze these technologies in the context of each other and highlight the most important utilization avenues available thus far. This review will introduce and analyze each major pathway, and discuss the overall applicability, potential extent, and major limitations of each of these pathways to utilizing CO2. This will include the analysis of some previously underreported utilization avenues, including CO2 utilization in industrial filtration and the processing of raw industrial materials such as iron and alumina. The core theme of this paper is to seek to treat CO2 as a commodity instead of a liability.
68 citations
TL;DR: In this article, the authors provide a thorough analysis of the biodegradation of per-and polyfluoroalkyl substances (PFAS) in multiple environmental matrices and offer a future outlook.
50 citations
TL;DR: The adsorption approach has attracted the most attention for the removal of heavy metals from wastewater, leading to the great development of adsorbents in the past decade (2011-2020) as mentioned in this paper .
Abstract: The adsorption approach has attracted the most attention for the removal of heavy metals from wastewater, leading to the great development of adsorbents in the past decade (2011–2020).
36 citations
TL;DR: A critical discussion on the progress of thermo-photo coupled catalytic CRM is provided, and suggestions to drive the prosperous development of the processes are stated.
30 citations
TL;DR: In this article, the experimental and numerical studies of flexural-fracture behaviors of steel fiber-reinforced rubber self-compacting concrete (SRSCC) materials are presented.
Abstract: This paper presents the experimental and numerical studies of flexural-fracture behaviors of steel fiber–reinforced rubber self-compacting concrete (SRSCC) materials. The scrap-tires rubber...
24 citations
TL;DR: In this article , the authors presented the experimental and numerical studies of flexural-fracture behaviors of steel fiber-reinforced rubber self-compacting concrete (SRSCC) materials.
Abstract: This paper presents the experimental and numerical studies of flexural-fracture behaviors of steel fiber–reinforced rubber self-compacting concrete (SRSCC) materials. The scrap-tires rubber aggregate was used to partially (10%, 15%, and 25%) replace the fine aggregate based on its volume for SRSCC samples, and the microsteel fiber was introduced with an addition ratio of 0.2% based on the entire mixture volume. The plain self-compacting concrete (SCC) and the rubberized SCC specimens were produced for comparison. The three-point bending test on the single-edge notched beam showed the increased flexural strength and total fracture energy of SRSCC samples by adding steel fiber and rubber. The critical fracture parameters including initial fracture energy (Gf) and fracture toughness (KІc) were determined based on the Load-CMOD curves and two parameters fracture model. With these properties, the bilinear tension-softening model (aggregate interlock effect) and trilinear tension-softening model (aggregate interlock and fiber-bridging effects) were calibrated for normal SCC and SRSCC, respectively. The tension-softening functions were utilized in the FEM model to predict the flexural-fracture behaviors of corresponding specimens, and the numerical simulation results showed reasonable agreement with experiments. Overall, the experimental testing data and numerical simulation model can reveal the detailed fracture behavior of SRSCC for future improved material design.
22 citations
TL;DR: In this paper , a critical discussion on the progress of thermo-photo coupled catalytic CO2 reforming of methane (CRM) is provided, after addressing the general issues for conventional thermocatalytic and photocatallytic CRM.
17 citations
TL;DR: In this paper, a new asphalt molecular model including 50 types of molecules was proposed, and the dipole moment, molecular electrostatic potential, and HOMO-LUMO gap were calculated by quantum chemistry methods.
16 citations
TL;DR: In this paper , the influence of sea salt on the adhesion properties of bitumen-aggregate systems by molecular dynamics simulations was investigated in order to fundamentally understand the mechanism of damage in the seawater environment.
TL;DR: In this article , a new asphalt molecular model including 50 types of molecules was proposed, and the dipole moment, molecular electrostatic potential, and HOMO-LUMO gap were calculated by quantum chemistry methods.
TL;DR: Wang et al. as mentioned in this paper presented a long shortterm memory (LSTM)-augmented deep learning framework for time-dependent reliability analysis of dynamic systems, where multiple LSTMs were trained to generate local surrogate models of dynamic system in the time-independent system input space.
TL;DR: In this paper, a simple synthesis route is used to fabricate multishaped silver nanoparticles to create a coupled plasmonic effect in DSSC to cover more of the solar spectrum.
TL;DR: In this paper , a convolutional neural network is trained to correct the output of fast and approximate N-body simulations at the field level, which can reproduce the results of the full N -body simulations with subpercent accuracy down to k ≃ 1 h Mpc −1 .
Abstract: Abstract We train convolutional neural networks to correct the output of fast and approximate N -body simulations at the field level. Our model, Neural Enhanced COLA (NECOLA), takes as input a snapshot generated by the computationally efficient COLA code and corrects the positions of the cold dark matter particles to match the results of full N -body Quijote simulations. We quantify the accuracy of the network using several summary statistics, and find that NECOLA can reproduce the results of the full N -body simulations with subpercent accuracy down to k ≃ 1 h Mpc −1 . Furthermore, the model that was trained on simulations with a fixed value of the cosmological parameters is also able to correct the output of COLA simulations with different values of Ω m , Ω b , h , n s , σ 8 , w , and M ν with very high accuracy: the power spectrum and the cross-correlation coefficients are within ≃1% down to k = 1 h Mpc −1 . Our results indicate that the correction to the power spectrum from fast/approximate simulations or field-level perturbation theory is rather universal. Our model represents a first step toward the development of a fast field-level emulator to sample not only primordial mode amplitudes and phases, but also the parameter space defined by the values of the cosmological parameters.
TL;DR: This paper introduces an approach for efficient and extremely high resolution 3D structural dynamic identification/modal analysis from point cloud data acquired using a commercial, low-cost, time-of-flight imager and demonstrates the potential of this technique on laboratory tests.
The Royal Marsden NHS Foundation Trust1, Royal Marsden Hospital2, Human Technopole3, University College London4, UCL Institute of Child Health5, Michigan Technological University6, University of Perugia7, University of Manchester8, Tongren University9, Institute of Cancer Research10, University of Birmingham11, Great Ormond Street Hospital for Children NHS Foundation Trust12, National Institute of Technology, Rourkela13, Business-Higher Education Forum14, Genentech15, Carnegie Mellon University16
TL;DR: In this article , a clinically relevant (67 gene) NGS capture panel and accompanying workflow was developed to enable sensitive and reliable detection of low-frequency genetic variants in cell-free DNA (cfDNA) from children with solid tumours.
Abstract: Clinical diagnostic sequencing of circulating tumour DNA (ctDNA) is well advanced for adult patients, but application to paediatric cancer patients lags behind.To address this, we have developed a clinically relevant (67 gene) NGS capture panel and accompanying workflow that enables sensitive and reliable detection of low-frequency genetic variants in cell-free DNA (cfDNA) from children with solid tumours. We combined gene panel sequencing with low pass whole-genome sequencing of the same library to inform on genome-wide copy number changes in the blood.Analytical validity was evaluated using control materials, and the method was found to be highly sensitive (0.96 for SNVs and 0.97 for INDEL), specific (0.82 for SNVs and 0.978 for INDEL), repeatable (>0.93 [95% CI: 0.89-0.95]) and reproducible (>0.87 [95% CI: 0.87-0.95]). Potential for clinical application was demonstrated in 39 childhood cancer patients with a spectrum of solid tumours in which the single nucleotide variants expected from tumour sequencing were detected in cfDNA in 94.4% (17/18) of cases with active extracranial disease. In 13 patients, where serial samples were available, we show a close correlation between events detected in cfDNA and treatment response, demonstrate that cfDNA analysis could be a useful tool to monitor disease progression, and show cfDNA sequencing has the potential to identify targetable variants that were not detected in tumour samples.This is the first pan-cancer DNA sequencing panel that we know to be optimised for cfDNA in children for blood-based molecular diagnostics in paediatric solid tumours.
TL;DR: In this paper , a photothermal catalytic hydrogenation of CO2 into CH4 over Ru/black TiO2 catalysts was presented, aiming to achieve the synergistic use of light and heat in solar energy during CO2 conversion.
TL;DR: Wang et al. as mentioned in this paper applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major world stock market indexes.
Abstract: Starting on February 20, 2020, the global stock markets began to suffer the worst decline since the Great Recession in 2008, and the COVID-19 has been widely blamed on the stock market crashes. In this study, we applied the log-periodic power law singularity (LPPLS) methodology based on multilevel time series to unravel the underlying mechanisms of the 2020 global stock market crash by analyzing the trajectories of 10 major world stock market indexes from both developed and emergent stock markets, including the S&P 500, the DJIA, and the NASDAQ from the United State, the FTSE from the United Kingdom, the DAX from Germany, the NIKKEI from Japan, the CSI 300 from China, the HSI from Hong Kong, the BSESN from India, and the BOVESPA from Brazil. In order to effectively distinguish between endogenous crash and exogenous crash in stock market, we proposed using the LPPLS confidence indicator as a classification proxy. The results show that the apparent LPPLS bubble patterns of the super-exponential increase, corrected by the accelerating logarithm-periodic oscillations, have indeed presented in the price trajectories of the seven indexes: S&P 500, DJIA, NASDAQ, DAX, CSI 300, BSESN, and BOVESPA, indicating that the large positive bubbles have formed endogenously prior to the 2020 stock market crash, and the subsequent crashes for the seven indexes are endogenous, stemming from the increasingly systemic instability of the stock markets inherently, while the well-known external shocks, such as the COVID-19 pandemic, the corporate debt bubble, and the 2020 Russia–Saudi Arabia oil price war, only served as sparks during the 2020 global stock market crash. In contrast, the crashes in the three remaining indexes: FTSE, NIKKEI, and HSI, are exogenous and hence are perhaps the only crashes truly due to the COVID-19 pandemic. We also found that in terms of the regime changes of the stock markets, no obvious LPPLS negative bubble pattern has been observed in the price trajectories of the 10 stock market indexes, indicating that the regime changes from a bear market to a bull market in late March 2020 are exogenous, stemming from external factors. The unprecedented market and economy rescue efforts from federal reserves and central banks across the world in unison may have played a critical role in quelling the 2020 global stock market crash in the nick of time. This paper creates a paradigm for future studies in real-time crash detection and underlying mechanism dissection. It serves to warn us of the imminent risks in not only the stock market but also other financial markets and economic indexes.
TL;DR: In this article, a Gaussian process meta-model has been used to characterize the multi-physics and multi-scale nature of composite manufacturing process and an importance ranking analysis of uncertainties was carried out using a series of metrics, i.e., Pearson coefficient, Sobol index and Shapley additive explanations (SHAP).
TL;DR: In this paper , the influence of silane-hydrolysate coupling agents on various parameters of the interfacial adhesion between bitumen and mineral aggregate by applying molecular dynamics simulations was investigated.
TL;DR: In this article, the influence of silane-hydrolysate coupling agents on various parameters of the interfacial adhesion between bitumen and mineral aggregate by applying molecular dynamics simulations was investigated.
TL;DR: In this paper, the authors present a novel pilot-scale system that integrates torrefaction and extrusion to convert mix fiber-plastic waste into fuel pellets, which can be used as solid fuels or as feedstock for pyrolysis and gasification.
TL;DR: In this paper, the role of paleochannels, a product of migrating rivers, in a catastrophic flood in the south-western part of the Indian Peninsula was exposed, exposing whether these geomorphic features facilitate or impede floods.
TL;DR: In this paper, the potential of vermite technology for eco-friendly recycling of pollutant-loaded biochar was assessed by using arsenic-saturated native (NBC) and exfoliated (EBC) biochars as feedstocks for the first time.
TL;DR: In this article, the authors used 360-degree panoramic virtual environments enhanced with virtual humans to produce realistic site visits for practicing collaborative problem-solving opportunities (iVisit-Collaborate).
Abstract: Collaborative problem-solving skills are required from learners in the 21st century, particularly in construction graduates upon entering the workforce. However, challenges associated with spatiotemporal contexts of construction sites and resource limitations of educational programs reduce the opportunities available for students to practice these skills. This study focuses on using 360-degree panoramic virtual environments enhanced with virtual humans to produce realistic site visits for practicing collaborative problem-solving opportunities (iVisit-Collaborate). The goal of this phenomenological research study is to understand the collaborative problem-solving process of student dyads within iVisit-Collaborate. The findings suggest that student collaborative behaviors did not directly result in successful problem-solving. A hierarchical relationship between student problem-solving and collaborative behaviors was observed, indicating that problem-solving behaviors must take place to enable the occurrence of collaborative behaviors. Moreover, it was also observed that instructor scaffolding helped reduce the degrees of freedom in complex problem-solving activities. Finally, it was observed that student discussion engagement supported the creation and maintenance of shared mental models.
TL;DR: In this paper , a unique waste plastic pyrolysis pilot plant was used for fast pyrolys (1-5 s vapor residence time) of HDPE at 600 °C.
TL;DR: In this article, the authors evaluated risk factors (personal, including behavioral and work organizational) that influence human error and evaluated those risk factors as predictors of injury occurrences at continuous miner worksites.
TL;DR: A novel method to estimate group velocities from experimental data-driven models from experimental in-plane and out-of-plane FRFs of a one-dimensional structure and the vector-fitting (VF) algorithm is adopted.
TL;DR: In this paper , the parity of the coefficients of certain eta-quotients was investigated and the density of their odd values was investigated, in particular establishing lacunarity modulo 2 for specified coefficients and infinite families of congruences in arithmetic progressions.