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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Cytochrome P450 Gene Families: Role In Plant Secondary Metabolites Production And Plant Defense, Panchali Chakraborty, Ashok Biswas, Susmita Dey, Tuli Bhattacharjee, Swapan Chakrabarty
Cytochrome P450 Gene Families: Role In Plant Secondary Metabolites Production And Plant Defense, Panchali Chakraborty, Ashok Biswas, Susmita Dey, Tuli Bhattacharjee, Swapan Chakrabarty
Michigan Tech Publications, Part 2
Cytochrome P450s (CYPs) are the most prominent family of enzymes involved in NADPH- and O2-dependent hydroxylation processes throughout all spheres of life. CYPs are crucial for the detoxification of xenobiotics in plants, insects, and other organisms. In addition to performing this function, CYPs serve as flexible catalysts and are essential for producing secondary metabolites, antioxidants, and phytohormones in higher plants. Numerous biotic and abiotic stresses frequently affect the growth and development of plants. They cause a dramatic decrease in crop yield and a deterioration in crop quality. Plants protect themselves against these stresses through different mechanisms, which are accomplished by …
Identification Of Dialect For Eastern And Southwestern Ojibwe Words Using A Small Corpus, Kalvin Hartwig, Evan Lucas, Timothy C. Havens
Identification Of Dialect For Eastern And Southwestern Ojibwe Words Using A Small Corpus, Kalvin Hartwig, Evan Lucas, Timothy C. Havens
Michigan Tech Publications, Part 2
The Ojibwe language has several dialects that vary to some degree in both spoken and written form. We present a method of using support vector machines to classify two different dialects (Eastern and Southwestern Ojibwe) using a very small corpus of text. Classification accuracy at the sentence level is 90% across a five-fold cross validation and 72% when the sentence-trained model is applied to a data set of individual words. Our code and the word level data set are released openly at https://github.com/evanperson/OjibweDialect.
An Autoencoder-Based Deep Learning Method For Genotype Imputation, Meng Song, Jonathan Greenbaum, Joseph Luttrell, Weihua Zhou, Chong Wu, Zhe Luo, Chuan Qiu, Lan Juan Zhao, Kuan Jui Su, Qing Tian, Hui Shen, Huixiao Hong, Ping Gong, Xinghua Shi, Hong Wen Deng, Chaoyang Zhang
An Autoencoder-Based Deep Learning Method For Genotype Imputation, Meng Song, Jonathan Greenbaum, Joseph Luttrell, Weihua Zhou, Chong Wu, Zhe Luo, Chuan Qiu, Lan Juan Zhao, Kuan Jui Su, Qing Tian, Hui Shen, Huixiao Hong, Ping Gong, Xinghua Shi, Hong Wen Deng, Chaoyang Zhang
Michigan Tech Publications
Genotype imputation has a wide range of applications in genome-wide association study (GWAS), including increasing the statistical power of association tests, discovering trait-associated loci in meta-analyses, and prioritizing causal variants with fine-mapping. In recent years, deep learning (DL) based methods, such as sparse convolutional denoising autoencoder (SCDA), have been developed for genotype imputation. However, it remains a challenging task to optimize the learning process in DL-based methods to achieve high imputation accuracy. To address this challenge, we have developed a convolutional autoencoder (AE) model for genotype imputation and implemented a customized training loop by modifying the training process with a …
A Mild Dyssynchronous Contraction Pattern Detected By Spect Myocardial Perfusion Imaging Predicts Super-Response To Cardiac Resynchronization Therapy, Xiao Hu, Zhiyong Qian, Fengwei Zou, Siyuan Xue, Xinwei Zhang, Yao Wang, Xiaofeng Hou, Weihua Zhou, Jiangang Zou
A Mild Dyssynchronous Contraction Pattern Detected By Spect Myocardial Perfusion Imaging Predicts Super-Response To Cardiac Resynchronization Therapy, Xiao Hu, Zhiyong Qian, Fengwei Zou, Siyuan Xue, Xinwei Zhang, Yao Wang, Xiaofeng Hou, Weihua Zhou, Jiangang Zou
Michigan Tech Publications
Background: Using single photon emission computed tomography myocardial perfusion imaging (SPECT MPI) with phase analysis (PA), we aimed to identify the predictive value of a new contraction pattern in cardiac resynchronization therapy (CRT) response. Methods: Left ventricular mechanical dyssynchrony (LVMD) was evaluated using SPECT MPI with PA in non-ischemic dilated cardiomyopathy (DCM) patients with left bundle branch block (LBBB) indicated for CRT. CRT super-response was defined as LV ejection fraction (EF) ≥50% or an absolute increase of LVEF >15%. The LV contraction was categorized as the mild dyssynchronous pattern when the phase standard deviation (PSD) ≤ 40.3° and phase histogram …
Exploiting Block Structures Of Kkt Matrices For Efficient Solution Of Convex Optimization Problems, Zafar Iqbal, Saeid Nooshabadi, Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra
Exploiting Block Structures Of Kkt Matrices For Efficient Solution Of Convex Optimization Problems, Zafar Iqbal, Saeid Nooshabadi, Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra
Michigan Tech Publications
Convex optimization solvers are widely used in the embedded systems that require sophisticated optimization algorithms including model predictive control (MPC). In this paper, we aim to reduce the online solve time of such convex optimization solvers so as to reduce the total runtime of the algorithm and make it suitable for real-time convex optimization.We exploit the property of the Karush–Kuhn–Tucker (KKT) matrix involved in the solution of the problem that only some parts of the matrix change during the solution iterations of the algorithm. Our results show that the proposed method can effectively reduce the runtime of the solvers.
U-Net And Its Variants For Medical Image Segmentation: A Review Of Theory And Applications, Nahian Siddique, Paheding Sidike, Colin P. Elkin, Vijay Devabhaktuni
U-Net And Its Variants For Medical Image Segmentation: A Review Of Theory And Applications, Nahian Siddique, Paheding Sidike, Colin P. Elkin, Vijay Devabhaktuni
Michigan Tech Publications
U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in nearly all major image modalities, from CT scans and MRI to Xrays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. Given that U-net’s potential is still increasing, this narrative literature review examines …
Comparison Of Left Ventricular Mechanical Dyssynchrony Parameters Between Exercise And Adenosine Triphosphate Stress Tests Using Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging, Jianzhou Shi, Yanli Zhou, Priyaranjan Kata, Sheilabi Seeburun, Cheng Wang, Dianfu Li, Zhixin Jiang, Weihua Zhou
Comparison Of Left Ventricular Mechanical Dyssynchrony Parameters Between Exercise And Adenosine Triphosphate Stress Tests Using Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging, Jianzhou Shi, Yanli Zhou, Priyaranjan Kata, Sheilabi Seeburun, Cheng Wang, Dianfu Li, Zhixin Jiang, Weihua Zhou
Michigan Tech Publications
Background Left ventricular mechanical dyssynchrony (LVMD) can be induced after stress test. However, no studies have compared the influence of different stress-inducing methods on LVMD parameters. aims The aim of the study was to determine whether there is a difference between exercise and adenosine triphosphate (ATP) stress tests in terms of changes in LVMD parameters assessed using gated single-photon emission computed tomography myocardial perfusion imaging (GSPECT MPI). methods A total of 190 patients who underwent 99mTc-sestamibi GSPECT MPI were consecutively enrolled. Treadmill exercise and ATP stress tests were performed in 95 patients each. Normal myocardial perfusion was defined as the …
Accurate Diagnosis Of Colorectal Cancer Based On Histopathology Images Using Artificial Intelligence, K. S. Wang, G. Yu, C. Xu, X. H. Meng, J. Zhou, W. Zhou, Et. Al.
Accurate Diagnosis Of Colorectal Cancer Based On Histopathology Images Using Artificial Intelligence, K. S. Wang, G. Yu, C. Xu, X. H. Meng, J. Zhou, W. Zhou, Et. Al.
Michigan Tech Publications
Background: Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods: Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered …
Exploring Techniques For Vision Based Human Activity Recognition: Methods, Systems, And Evaluation, Xin Xu, Jinshan Tang, Xiaolong Zhang, Xiaoming Liu, Hong Zhang, Yimin Qiu
Exploring Techniques For Vision Based Human Activity Recognition: Methods, Systems, And Evaluation, Xin Xu, Jinshan Tang, Xiaolong Zhang, Xiaoming Liu, Hong Zhang, Yimin Qiu
Michigan Tech Publications
With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activity, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, …