Engineering Commons^™

Continental Magmatism And Uplift As The Primary Driver For First-Order Oceanic 87sr/86sr Variability With Implications For Global Climate And Atmospheric Oxygenation, Timothy Paulsen, Chad Deering, Jakub Sliwinski, Snehamoy Chatterjee, Olivier Bachman

Michigan Tech Publications

Oceans cover 70% of Earth's surface, setting it apart from the other terrestrial planets in the solar system, but the mechanisms driving oceanic chemical evolution through time remain an important unresolved problem. Imbalance in the strontium cycle, introduced, for example, by increases in continental weathering associated with mountain building, has been inferred from shifts in marine carbonate 87Sr/86Sr ratios. There are, however, uncertainties about the spatial and temporal patterns of crustal evolution in Earth's past, particularly for the period leading up to the Cambrian explosion of life. Here we show that U-Pb age and trace element data from a global …

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) versus …

Life Cycle Assessment Of Pasture-Based Agrivoltaic Systems: Emissions And Energy Use Of Integrated Rabbit Production, Alexis Pascaris, Robert Handler, Chelsea Schelly, Joshua Pearce

Michigan Tech Publications

Agrivoltaic systems, which deliberately maximize the utility of a single parcel of land for both solar photovoltaic (PV) electricity production and agriculture, have been demonstrated as a viable technology that can ameliorate competing land uses and meet growing energy and food demands efficiently. The goal of this study is to assess the environmental impacts of a novel pasture-based agrivoltaic concept: co-farming rabbits and solar PV. A life cycle assessment (LCA) quantified the impacts of 1) the integrated agrivoltaic concept in comparison to conventional practices including 2) separate rabbit farming and PV production and 3) separate rabbit farming and conventional electricity …

A Comparison Of Multiple Machine Learning Algorithms To Predict Whole-Body Vibration Exposure Of Dumper Operators In Iron Ore Mines In India, Rahul Upadhyay, Amrites Senapati, Ashis Bhattacherjee, Aditya Kumar Patra, Snehamoy Chatterjee

Michigan Tech Publications

Background: This study deals with some factors that influence the exposure of whole-body vibration (WBV) of dumper operators in surface mines. The study also highlights the approach to improve the multivariate linear analysis outcomes when collinearity exists between certain factor pairs.

Material and Methods: A total number of 130 vibration readings was taken from two adjacent surface iron ore mines. The frequency-weighted RMS acceleration was used for the WBV exposure assessment of the dumper operators. The factors considered in this study are age, weight, seat backrest height, awkward posture, the machine age, load tonnage, dumper speed and haul …

3d Printing In Cardiology: A Review Of Applications And Roles For Advanced Cardiac Imaging, Ellen M. Lindquist, Jordan M. Gosnell, Sana K. Khan, John L. Byl, Weihua Zhou, Jingfeng Jiang, Et. Al.

Michigan Tech Publications

With the rate of cardiovascular diseases in the U.S increasing throughout the years, there is a need for developing more advanced treatment plans that can be tailored to specific patients and scenarios. The development of 3D printing is rapidly gaining acceptance into clinical cardiology.

In this review, key technologies used in 3D printing are briefly summarized, particularly, the use of artificial intelligence (AI), open-source tools like MeshLab and MeshMixer, and 3D printing techniques such as fused deposition molding (FDM) and polyjet are reviewed. The combination of 3D printing, multiple image integration, and augmented reality may greatly enhance data visualization …

New Innovations In Pavement Materials And Engineering: A Review On Pavement Engineering Research 2021, Jtte Editorial Office Chang’An Univeristy, Jiaqi Chen, Hancheng Dan, Yongjie Ding, Yangming Gao, Meng Guo, Zhanping You, Et. Al.

Michigan Tech Publications

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging. Deterioration of pavement infrastructure is a typical multi-physics problem. Because of actual coupled behaviors of traffic and environmental conditions, predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material analysis. In order to summarize the current and determine the future research of pavement engineering, Journal of …

Degradation Issues And Stabilization Strategies Of Protonic Ceramic Electrolysis Cells For Steam Electrolysis, Hanrui Su, Yun Hang Hu

Michigan Tech Publications

Protonic ceramic electrolysis cells (PCECs) are attractive electrochemical de-vices for converting electrical energy to chemicals due to their high conversion efficiency, favorable thermodynamics, fast kinetics, and inexpensive materials. Compared with conventional oxygen ion- conducting solid oxide electrolysis cells, PCECs operate at a lower operating temperature and a favorable operation mode, thus expecting high durability. However, the degradation of PCECs is still significant, hampering their development. In this review, the typical degradations of PCECs are summarized, with emphasis on the chemical stability of the electrolytes and the air electrode materials. Moreover, the degradation mechanism and influencing factors are assessed deeply. Finally, …

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 analyses. …

Research And Applications Of Artificial Neural Network In Pavement Engineering: A State-Of-The-Art Review, Xu Yang, Jinchao Guan, Ling Ding, Zhanping You, Vincent C.S. Lee, Mohd Rosli Mohd Hasan, Xiaoyun Cheng

Michigan Tech Publications

Given the great advancements in soft computing and data science, artificial neural network (ANN) has been explored and applied to handle complicated problems in the field of pavement engineering. This study conducted a state-of-the-art review for surveying the recent progress of ANN application at different stages of pavement engineering, including pavement design, construction, inspection and monitoring, and maintenance. This study focused on the papers published over the last three decades, especially the studies conducted since 2013. Through literature retrieval, a total of 683 papers in this field were identified, among which 143 papers were selected for an in-depth review. The …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

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 moderate to …

Open Source Software Toolchain For Automated Non‐Targeted Screening For Toxins In Alternative Foods, S. W. Breuer, L. Toppen, S. K. Schum, J. M. Pearce

Michigan Tech Publications

Previous published methods for non-targeted screening of toxins in alternative foods such as leaf concentrate, agricultural residues or plastic fed to biological consortia are time consuming and expensive and thus present accessibility, as well as, time-constraint issues for scientists from under resourced settings to identify safe alternative foods. The novel methodology presented here, utilizes a completely free and open source software toolchain for automatically screening unknown alternative foods for toxicity using experimental data from ultra-high-pressure liquid chromatography and mass spectrometry. The process uses three distinct tools (mass spectrometry analysis with MZmine 2, formula assignment with MFAssignR, and data filtering with …