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Full-Text Articles in Engineering

Bioabsorbable Metal Zinc Differentially Affects Mitochondria In Vascular Endothelial And Smooth Muscle Cells, Olivia R. M. Bagshaw, Fereshteh Moradi, Christopher S. Moffatt, Hillary A. Hettwer, Ping Liang, Jeremy Goldman, Jaroslaw Drelich, Jeffrey A. Stuart Dec 2021

Bioabsorbable Metal Zinc Differentially Affects Mitochondria In Vascular Endothelial And Smooth Muscle Cells, Olivia R. M. Bagshaw, Fereshteh Moradi, Christopher S. Moffatt, Hillary A. Hettwer, Ping Liang, Jeremy Goldman, Jaroslaw Drelich, Jeffrey A. Stuart

Michigan Tech Publications

Zinc is an essential trace element having various structural, catalytic and regulatory interactions with an estimated 3000 proteins. Zinc has drawn recent attention for its use, both as pure metal and alloyed, in arterial stents due to its biodegradability, biocompatibility, and low corrosion rates. Previous studies have demonstrated that zinc metal implants prevent the development of neointimal hyperplasia, which is a common cause of restenosis following coronary intervention. This suppression appears to be smooth muscle cell-specific, as reendothelization of the neointima is not inhibited. To better understand the basis of zinc's differential effects on rat aortic smooth muscle (RASMC ...


Decarbonizing Rural Residential Buildings In Cold Climates: A Techno-Economic Analysis Of Heating Electrification, Filippo Padovani, Nelson Sommerfeldt, Francesca Longobardi, Joshua M. Pearce Nov 2021

Decarbonizing Rural Residential Buildings In Cold Climates: A Techno-Economic Analysis Of Heating Electrification, Filippo Padovani, Nelson Sommerfeldt, Francesca Longobardi, Joshua M. Pearce

Michigan Tech Publications

Given the need for decarbonization of the heating sector and the acute need of a propane replacement in the U.S. Upper Midwest, this study quantifies the techno-economic characteristics of sustainable heating electrification in isolated rural, residential buildings in cold climates without natural gas supply. Archetypal buildings are modeled under four levels of electrification. At each electrification level, a parametric solar photovoltaic (PV) sizing analysis is performed and the total life cycle cost, renewable fraction and greenhouse gas (GHG) emissions are calculated based on the primary energy supply for each building type. Cost optimal solutions are stress-tested with multi-dimensional sensitivity ...


The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 36, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 36, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 76, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 76, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


The Winter Adverse Driving Dataset (Wads) - Sequence 37, Akhil Kurup, Jeremy Bos Oct 2021

The Winter Adverse Driving Dataset (Wads) - Sequence 37, Akhil Kurup, Jeremy Bos

Michigan Tech Research Data

Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of ...


Me-Em Enewsbrief, September 2021, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University Oct 2021

Me-Em Enewsbrief, September 2021, Department Of Mechanical Engineering-Engineering Mechanics, Michigan Technological University

Department of Mechanical Engineering-Engineering Mechanics eNewsBrief

No abstract provided.


Mechanical Properties And Characterization Of Epoxy Composites Containing Highly Entangled As-Received And Acid Treated Carbon Nanotubes, Aaron Krieg, Julia A. King, Gregory M. Odegard, Timothy Leftwich, Leif K. Odegard, Paul D. Fraley, Ibrahim Miskioglu, Claire Jolowsky, Matthew Lundblad, Jin Gyu Park, Richard Liang Sep 2021

Mechanical Properties And Characterization Of Epoxy Composites Containing Highly Entangled As-Received And Acid Treated Carbon Nanotubes, Aaron Krieg, Julia A. King, Gregory M. Odegard, Timothy Leftwich, Leif K. Odegard, Paul D. Fraley, Ibrahim Miskioglu, Claire Jolowsky, Matthew Lundblad, Jin Gyu Park, Richard Liang

Michigan Tech Publications

Huntsman–Merrimack MIRALON® carbon nanotubes (CNTs) are a novel, highly entan-gled, commercially available, and scalable format of nanotubes. As-received and acid-treated CNTs were added to aerospace grade epoxy (CYCOM® 977-3), and the composites were characterized. The epoxy resin is expected to infiltrate the network of the CNTs and could improve mechanical properties. Epoxy composites were tested for flexural and viscoelastic properties and the as-re-ceived and acid treated CNTs were characterized using Field-Emission Scanning and Transmission Electron Microscopy, X-Ray Photoelectron Spectroscopy, and Thermogravimetric Analysis. Composites containing 0.4 wt% as-received CNTs showed an increase in flexural strength, from 136.9 MPa ...


A High Solids Field-To-Fuel Research Pipeline To Identify Interactions Between Feedstocks And Biofuel Production, Meenaa Chandrasekar, Leela Joshi, Karleigh M. Krieg, Sarvada Chipkar, Emily Burke, Derek J. Debrauske, Kurt D. Thelen, Trey K. Sato, Rebecca Ong Sep 2021

A High Solids Field-To-Fuel Research Pipeline To Identify Interactions Between Feedstocks And Biofuel Production, Meenaa Chandrasekar, Leela Joshi, Karleigh M. Krieg, Sarvada Chipkar, Emily Burke, Derek J. Debrauske, Kurt D. Thelen, Trey K. Sato, Rebecca Ong

Michigan Tech Publications

Background: Environmental factors, such as weather extremes, have the potential to cause adverse effects on plant biomass quality and quantity. Beyond adversely affecting feedstock yield and composition, which have been extensively studied, environmental factors can have detrimental effects on saccharification and fermentation processes in biofuel production. Only a few studies have evaluated the effect of these factors on biomass deconstruction into biofuel and resulting fuel yields. This field-to-fuel evaluation of various feedstocks requires rigorous coordination of pretreatment, enzymatic hydrolysis, and fermentation experiments. A large number of biomass samples, often in limited quantity, are needed to thoroughly understand the effect of ...


Editorial: Development And Application Of Bituminous Materials For Civil Infrastructures, Zhanping You, Jie Ji, Dawei Wang, Feng Li, Hui Yao, Yue Hou Sep 2021

Editorial: Development And Application Of Bituminous Materials For Civil Infrastructures, Zhanping You, Jie Ji, Dawei Wang, Feng Li, Hui Yao, Yue Hou

Michigan Tech Publications

No abstract provided.


Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue Sep 2021

Evaluating Essential Processes And Forecast Requirements For Meteotsunami-Induced Coastal Flooding, Chenfu Huang, Eric Anderson, Yi Liu, Gangfeng Ma, Greg Mann, Pengfei Xue

Michigan Tech Publications

Meteotsunamis pose a unique threat to coastal communities and often lead to damage of coastal infrastructure, deluge of nearby property, and loss of life and injury. The Great Lakes are a known hot-spot of meteotsunami activity and serve as an important region for investigation of essential hydrodynamic processes and model forecast requirements in meteotsunami-induced coastal flooding. For this work, we developed an advanced hydrodynamic model and evaluate key model attributes and dynamic processes, including: (1) coastal model grid resolution and wetting and drying process in low-lying zones, (2) coastal infrastructure, including breakwaters and associated submerging and overtopping processes, (3) annual ...


Sliding Mode Control Of A Nonlinear Wave Energy Converter Model, Tania Demonte Gonzalez, Gordon Parker, Enrico Anderlini, Wayne Weaver Sep 2021

Sliding Mode Control Of A Nonlinear Wave Energy Converter Model, Tania Demonte Gonzalez, Gordon Parker, Enrico Anderlini, Wayne Weaver

Michigan Tech Publications

The most accurate wave energy converter models for heaving point absorbers include nonlinearities, which increase as resonance is achieved to maximize the energy capture. Over the power production spectrum and within the physical limits of the devices, the efficiency of wave energy converters can be enhanced by employing a control scheme that accounts for these nonlinearities. This paper proposes a sliding mode control for a heaving point absorber that includes the nonlinear effects of the dynamic and static Froude‐Krylov forces. The sliding mode controller tracks a reference velocity that matches the phase of the excitation force to ensure higher ...


Progressive Poling Of Large Area, High R33 Electro-Optic Polymer Seo100c, Michael Maurer, Evan Gawron, Christopher Middlebrook Sep 2021

Progressive Poling Of Large Area, High R33 Electro-Optic Polymer Seo100c, Michael Maurer, Evan Gawron, Christopher Middlebrook

Michigan Tech Publications

SEO100c, an EO-polymer, has been reported of having an r33 in excess of 100 pm/V. Experimental poling research was performed on rib waveguide modulator for device design and development. Reported is the determination of the impact that temperature and voltage have on the poling of a SEO100c waveguide device in order to maximize the r33 while avoiding damage to the device structure ensuring high yield in manufacture. The poling process is shown to have a nonlinear relationship between r33 and poling field aiding in the selection of achievable poling voltages for required r33 values. Device thermal stability is quantified ...


Validation Of The Mathematics Motivation Questionnaire (Mmq) For Secondary School Students, Logan Fiorella, So Yoon Yoon, Kinnari Atit, Jason R. Power, Grace Panther, Sheryl Sorby, David H. Uttal, Norma Veurink Aug 2021

Validation Of The Mathematics Motivation Questionnaire (Mmq) For Secondary School Students, Logan Fiorella, So Yoon Yoon, Kinnari Atit, Jason R. Power, Grace Panther, Sheryl Sorby, David H. Uttal, Norma Veurink

Michigan Tech Publications

Background: Motivation is critical for supporting persistence and achievement in science, technology, engineering, and mathematics (STEM) disciplines. In this study, we focus on the assessment of mathematics motivation among secondary school students. We provide validity and reliability evidence for the Mathematics Motivation Questionnaire (MMQ)—adapted from the Science Motivation Questionnaire designed for college students—using data from 2551 secondary students from seven states across the United States. Results: Exploratory and confirmatory factor analyses confirmed five latent factors of the MMQ indicated by 19 items: intrinsic value, self-regulation, self-efficacy, utility value, and test anxiety. The nonlinear SEM reliability coefficients of the ...