Biomedical Engineering and Bioengineering Commons^™

Biodegradable Magnesium Materials Regulate Ros-Rns Balance In Pro-Inflammatory Macrophage Environment, Maria Paula Kwesiga, Amani A. Gillette, Seyedehfatemeh Razaviamri, Margaret E. Plank, Alexia L. Canull, Zachary Alesch, Weilue He, Bruce Lee, Roger J. Guillory Ii

Michigan Tech Publications

The relationship between reactive oxygen and nitrogen species (ROS-RNS) secretion and the concomitant biocorrosion of degradable magnesium (Mg) materials is poorly understood. We found that Mg foils implanted short term in vivo (24 h) displayed large amounts of proinflammatory F4/80+/iNOS + macrophages at the interface. We sought to investigate the interplay between biodegrading Mg materials (98.6% Mg, AZ31 & AZ61) and macrophages (RAW 264.7) stimulated with lipopolysaccharide (RAW 264.7LPS) to induce ROS-RNS secretion. To test how these proinflammatory ROS-RNS secreting cells interact with Mg corrosion in vitro, Mg and AZ61 discs were suspended approximately 2 mm above a monolayer of …

The Effect Of Pulse Duration On Mitochondrial Stability And Er Stress, Aislin West

Undergraduate Research Symposium

Abstract titled "The Effect of Pulse Duration on mitochondrial stability and ER stress" to be presented at the ODU Undergraduate Research Symposium 2023

Time Evolution Is A Source Of Bias In The Wolf Algorithm For Largest Lyapunov Exponents, Kolby Brink, Tyler Wiles, Nicholas Stergiou, Aaron Likens

UNO Student Research and Creative Activity Fair

Human movement is inherently variable by nature. One of the most common analytical tools for assessing movement variability is the largest Lyapunov exponent (LyE) which quantifies the rate of trajectory divergence or convergence in an n-dimensional state space. One popular method for assessing LyE is the Wolf algorithm. Many studies have investigated how Wolf’s calculation of the LyE changes due to sampling frequency, filtering, data normalization, and stride normalization. However, a surprisingly understudied parameter needed for LyE computation is evolution time. The purpose of this study is to investigate how the LyE changes as a function of evolution time …

Efficient Scopeformer: Towards Scalable And Rich Feature Extraction For Intracranial Hemorrhage Detection Using Hybrid Convolution And Vision Transformer Networks, Yassine Barhoumi

Theses and Dissertations

The field of medical imaging has seen significant advancements through the use of artificial intelligence (AI) techniques. The success of deep learning models in this area has led to the need for further research. This study aims to explore the use of various deep learning algorithms and emerging modeling techniques to improve training paradigms in medical imaging. Convolutional neural networks (CNNs) are the go-to architecture for computer vision problems, but they have limitations in mapping long-term dependencies within images. To address these limitations, the study explores the use of techniques such as global average pooling and self-attention mechanisms. Additionally, the …

Raman Spectroscopy - An Analytical Tool For Biologics, Cindy Mayorga, Shreya Milind Athalye, Mohit Verma

Graduate Industrial Research Symposium

Raman Spectroscopy (RS) is a non-invasive technique that analyses biomolecules qualitatively and quantitatively. Raman spectroscopy measures the inelastic scattering of light due to molecular vibrations. It can be applied to liquid, solid, or semi-solid forms of the biological sample reducing the sample preparation measures. The minimal sample preparation and non-invasive nature of Raman Spectroscopy can be applied in developing a Process analytical technology (PAT) tool and as a diagnostic tool. We demonstrated qualitative and quantitative measurements of biologics with Raman spectroscopy through our previous studies. Our results indicate that RS distinguishes various Gram-positive and Gram-negative bacteria, fungi, and a mixture …

The Next-Gen Crop Nutrient Stress Identification With High-Precision Sensing Technology In Digital Agriculture, Zhihang Song, Ziling Chen, Xing Wei, Jian Jin

Graduate Industrial Research Symposium

Crop yields are facing significant losses from nutrient deficiencies. Over-fertilizing also has negative economic and environmental impacts. It is challenging to optimize fertilizing without an accurate diagnosis. Recently, plant phenotyping has demonstrated outstanding capabilities in estimating crop traits. As one of the leading technologies, LeafSpec, provides high-quality crop image data for improving phenotyping quality. In this study, novel algorithms are developed for LeafSpec to identify crop nutrient deficiencies more accurately. Combined with UAV system, this technology will bring growers a robust solution for fertilizing diagnosis and scientific crop management.

Sea-Phages Course-Based Undergraduate Research Experience For Creating A Biotechnology Workforce Development Pipeline, Daphne Fauber, Kari Clase, Carol Weaver

Graduate Industrial Research Symposium

Purdue University has been a member of the SEA-PHAGES (Science Education Alliance-Phage Hunters Advancing Genomics and Evolutionary Science) program since 2011. This program, created in conjunction with the Howard Hughes Medical Institute (HHMI), facilitates undergraduate curriculum for the authentic discovery of novel bacteriophages within the classroom. Since joining the program, undergraduates at Purdue have harnessed wet lab and bioinformatics principles to contribute over 200 previously uncharacterized bacteriophages and 25 novel genomes to the wider scientific literature. The SEA-PHAGES classes at Purdue have resulted in tangible professional deliverables for students through conference presentations and publications. Student outcomes also include transferable skills …

Effects Of Post-Translational Histone Modifications On Transcription Rate, Aaron Bohn

Annual Research Symposium

No abstract provided.

Session 12: Active Learning To Minimize The Possible Risk From Future Epidemics, Kc Santosh

SDSU Data Science Symposium

In medical imaging informatics, for any future epidemics (e.g., Covid-19), deep learning (DL) models are of no use as they require a large dataset as they take months and even years to collect enough data (with annotations). In such a context, active learning (or human/expert-in-the-loop) is the must, where a machine can learn from the first day with minimum possible labeled data. In unsupervised learning, we propose to build pre-trained DL models that iteratively learn independently over time, where human/expert intervenes only when it makes mistakes and for only a limited data. In our work, deep features are used to …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Therapeutic Options For Covid-19: Drug Repurposing Of Serine Protease Inhibitor Against Tmprss2, Mohammad Wildan Abiyyi, Surya Dwira, Arleni Bustami, Linda Erlina

Indonesian Journal of Medical Chemistry and Bioinformatics

The SARS-Coronavirus 2 (SARS-CoV-2) outbreak is a serious global public health threat. Researchers around the world are conducting mass research to control this epidemic, starting from the discovery of vaccines, to new drugs that have specific activities as antivirals. Drug repurposing is a potential method of using drugs with known activity for reuse as COVID-19 therapy. This method has the advantage that it can reduce costs and also the duration in the development of potential drugs. The initial step in drug repurposing can be done computationally to determine the effectiveness and specificity of the drug on the target protein. Molecular …

Virtual Screening On Indonesian Herbal Compounds As Sars-Cov-2 Spike (S2) Glycoprotein Inhibitors: Pharmacophore Modelling & Molecular Docking Approaches, Syailendra Karuna Sugito, Artha Uli Cristina, Putri Saskia Harimurti, Gabriella Regita Cendani, Fauzi Azhar Insani, Linda Erlina, Rafika Indah Paramita, Fadilah Fadilah

Indonesian Journal of Medical Chemistry and Bioinformatics

Background: There are still no specific treatments for coronavirus disease (COVID-19) until present days. Several studies have been conducted to determine whether herbal medicine can be an option to be used as a definitive medicine for COVID-19. S2 subunit of spike protein which is responsible for SARS-CoV-2 entry to the host cell, is a potential drug target to inhibit the viral infection. In this study, we aimed to find some compounds from the HerbalDB database that have potential as SARS-CoV-2 spike (S2) glycoprotein inhibitor.

Methods: The 6LXT protein was used as the target protein. The procedure in this study consisted …

An Attention Residual U-Net With Differential Preprocessing And Geometric Postprocessing: Learning How To Segment Vasculature Including Intracranial Aneurysms, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Jinshan Tang, Jingfeng Jiang

Michigan Tech Publications

Objective

Intracranial aneurysms (IA) are lethal, with high morbidity and mortality rates. Reliable, rapid, and accurate segmentation of IAs and their adjacent vasculature from medical imaging data is important to improve the clinical management of patients with IAs. However, due to the blurred boundaries and complex structure of IAs and overlapping with brain tissue or other cerebral arteries, image segmentation of IAs remains challenging. This study aimed to develop an attention residual U-Net (ARU-Net) architecture with differential preprocessing and geometric postprocessing for automatic segmentation of IAs and their adjacent arteries in conjunction with 3D rotational angiography (3DRA) images.

Methods

The …

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …

Electromagnetic Theory And Applications, Nicholas Madamopoulos, George Kliros

Open Educational Resources

This book intends to provide both the fundamentals of Electromagnetics but also some practical applications of the concepts covered. Having taught electromagnetics for several years, the authors feel that many times the field of electromagnetics comes as “old” and often times students do not appreciate the concepts and their importance in everyday applications. The authors intend to accompany the EM concepts with life applications. Hence, students may see the direct impact of the knowledge they acquire through the study of the field of electromagnetics and better appreciate the field.

Developing A Finite Element Model For Evaluating The Posterior Tibial Slope In A Medial Opening Wedge High Tibial Osteotomy, Victor Alexander Carranza

Electronic Thesis and Dissertation Repository

This thesis aimed to develop and validate a computation finite element (FE) model to investigate the effect of hinge axis orientation on the posterior tibial slope (PTS) and mechanical medial proximal tibial angle (mMPTA) while analyzing the mechanical response around the hinge in a medial opening wedge high tibial osteotomy (MOWHTO). Chapter 2 highlights the importance of selecting an appropriate modeling method that best represents the clinical scenario. Chapter 3 validated a FE model using the Bland-Altman agreement analysis which yielded 95% limits of agreement of −0.9° to 1.2° for PTS and −1.4° to 1.9° for mMPTA. A parametric study …

The Implications Of Iot In The Modern Healthcare Industry Post Covid-19, Avaneesh Mohapatra

International Journal of Smart Sensor and Adhoc Network

The healthcare industry has recently seen a massive surge in the use of the Internet of Things (IoT) during and after the COVID-19 pandemic. IoT’s main objective is to provide people with the necessities in these uncertain times. During the pandemic, the availability of IoT-based healthcare systems is crucial. Using IoT, healthcare systems are becoming more individualized, allowing for more precise patient diagnosis, treatment, and monitoring. Since the beginning of the epidemic, many researchers have worked tirelessly to find solutions to this global problem, and IoT technology has the potential to revamp the current system completely. Over 6 million people …

Effect Of Blank Moisture Content On Forming Behaviour And Mechanical Properties Of Paperboard Tray Packages, Arvo Niini, Lena Berthold, Tobias Müller, Panu Tanninen, Jens-Peter Majschak, Juha Varis, Ville Leminen

Journal of Applied Packaging Research

Tray blanks were moisturised to study the effect of different blank moisture content levels on forming behaviour and mechanical properties of paperboard tray packages. The blank moisturisation was done by spraying water to the blanks before their three-dimensional (3D) forming. The trays were 3D formed by press forming or deep drawing. Visual quality and punch force values were used as indicators to evaluate the forming behaviour of the trays. The mechanical properties of the trays were investigated with compression, torsion, and storing tests. A high blank moisture content reduced the punch force, and the elevated blank moisture was connected to …

Gesture-Based American Sign Language (Asl) Translation System, Kayleigh Moore, Stefano Pecile, Mahdi Yazdanpour

Posters-at-the-Capitol

According to the World Health Organization (WHO), over 5% of the world's population experiences severe hearing loss. Approximately 9 million people in the U.S. are either functionally deaf or have mild-to-severe hearing loss. In this research, we designed and implemented a translation interface which turns American Sign Language (ASL) gestures captured from a pair of soft robotic gloves into text and speech instantaneously.

We used a combination of flex sensors, tactile sensors, and accelerometers to recognize hand gestures and to record hand and fingers positions, movements, and orientations. The digitized captured gestures were then sent to our proposed translation interface …

Comparison Of In-Vitro 3d Human Embryoids With Current Models For Gastrulation, Jin Park

McKelvey School of Engineering Theses & Dissertations

Gastrulation is an early morphogenetic process that is conserved across most metazoans and lays out the future body plan through the formation and shaping of the three germ layers: endoderm, mesoderm, and ectoderm. Despite its importance, not much is known about the events surrounding human gastrulation that occurs in utero due to ethical and technical limitations on studying human embryos. Therefore, many researchers have devised protocols for creating in vitro models of gastrulation using embryonic stem cells. Initially starting with mouse embryonic stem cells, the field of in vitro embryo models has advanced rapidly, with protocols using human embryonic stem …