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A Novel Machine Learning Algorithm Selects Proteome Signature To Specifically Identify Cancer Exosomes, Bingrui Li, Fernanda G Kugeratski, Raghu Kalluri

Faculty, Staff and Student Publications

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing …

A Review On Role Of Bacillus Species In Bio-Calcification: A Way Forward In Carbonate Precipitation, Ardil Bin Mansoor, Sheema Yousaf, Amna Gulzar, Ramsha Iqbal, Aisha Waheed Qurashi

Journal of Bioresource Management

Bio-calcification, also known as microbiologically induced calcite precipitation, is a phenomenon involving the activity of the enzyme urease. A large number of soil microorganism exhibit urease-producing ability. The main purpose of this review article is to signify the calcium carbonate bio-precipitation by Bacillus species including Lysinibacillus sphaericus and Bacillus subtilis. They both precipitated calcite and the shape and size depending on the external and internal conditions like the type of culture medium and the bacterial strains that were used. The research group increased attentions toward MICP (microbial-induced carbonated precipitation) because of its eco-friendly application. Different bacterial strains had been …

Novel Drug Approvals 2023, Emily Wagner, Christina Swiger, Mary Hoang, Maley Zents

Transformative Medicine

This article provides an overview of the novel drugs approved for 2023. The Food and Drug Administration’s (FDA) Center for Drug Evaluation and Research (CDER) provides standards to drug developers. The CDER sets standards for required data needed in the drug development and application process. Every year a variety of new drugs and biological products are approved. Some are new molecular compounds while others are structurally similar to those already on the market. Therefore, products may not have been used in medical practice previously while others have already been used in practice. This article highlights medications that are new in …

Metformin Continuation Versus Holding Pre And Post Coronary Angiography With Normal Renal Function: A Systematic Review And Meta-Analysis, Mohammad Hamza, Yasar Sattar, Sadaf Fakhra, Neel Patel, Mubashar Karamat, Saman Razzaq, Aamir Saeed, Khaled M. Harmouch, Islam Elgendy, Mamas Mamas, Anand Prasad, Wael Aljaroudi, Ramesh Daggubati, M Chadi Alraies

Transformative Medicine

Background

It is common practice to withhold metformin prior to cardiac catheterization due to fear of developing lactic acidosis in the setting of contrast-associated acute kidney injury (AKI). The evidence behind this recommendation is currently weak.

Methods

We collected 851 articles from PubMed and Embase, of which 3 met our inclusion criteria. Inclusion criteria were age > 18 years, baseline use of long-term metformin with continued or interrupted metformin use in patients during diagnostic or interventional cardiac catheterization. The outcomes studied were differences between post-catheterization and pre-catheterization serum creatinine (SCr) and glomerular filtration rate (GFR). We excluded studies dealing with patients …

The Impact Of Covid-19 Related Stress On Parenting And Community Engagement In A Small Iowa Community, Danny Trip, Savanna Farley

Research in the Capitol

This study addresses the question, “Does COVID-19-related stress and household income during COVID-19 predict parents’ interactions with children and family community engagement one year later?” The hypothesis was that higher levels of COVID-19-related stress and lower household income would predict more negative interactions between parent and the focal child and less community engagement. The participants within this study were drawn from a larger ongoing study, the Dubuque Youth and Family Resilience Project (DYFRP). Control variables included household income, child’s gender, and child’s age. The independent variable was reported COVID-19 related stress and the dependent variables were community engagement, positive parenting …

Senatorial Behavior In Recent Supreme Court Confirmation Hearings, Alex Perrin, Donna Hoffman

Research in the Capitol

Supreme Court confirmation hearings in the Senate have heightened stakes in today's political environment. The public stands at attention while Senators engage in questions and dialogue with the nominees. With increased stakes after the 2016 removal of the filibuster, Senators are in a prominent position to demonstrate their opposition to a nominee during the hearing. This study shows how Senators have quantitatively changed their tactics since 2016. I show this by examining the transcripts of the six most recent hearings (Roberts, Alito, Sotomayor, Kagan, Gorsuch, and Kavanaugh). I was able to show that opposition Senators engage in significantly more back-and-forth …

Political Orientation And Moral Values: Examining Their Effects On Susceptibility To Misinformation, Makayla L. Hall, Jordan A. Neely, Helen C. Harton

Research in the Capitol

According to past research, political misinformation is prevalent within social media, where information often goes unchecked. Both liberals and conservatives tend to believe misinformation that supports their beliefs. Values emphasized also tend to differ by political orientation, with liberals being more concerned with issues of harm, fairness, and universalism, and conservatives, with loyalty, authority, purity, and self-reliance. This study examines whether misinformation susceptibility is influenced by which of these values the information appeals to. 136 participants read social media posts that either supported or did not support their party’s platforms and that appealed to one of the seven values. They …

Characterization Of Mtdna Minicircles In A Chewing Louse, Geomydoecus Centralis, John Lehmkuhl, Grace Mraz, James W. Demastes, Theresa A. Spradling

Research in the Capitol

The DNA of living organisms is packaged into chromosomes differently in different species, but typically following a standard set of "rules." Understanding how DNA can be packaged for different species provides a better understanding of life and the genetic rules that must be followed, and the "rules" that can be broken. Mitochondria are crucial subcomponents of cells, providing the energy for life. Mitochondria always have their own mtDNA. In our study, we have learned that chewing lice mtDNA differs from that of other animals by spreading the genes across 12 separate small, circular chromosomes instead of one large, circular chromosome. …

Gender Socialization And Social Media In College Students' Fear Of Crime, Ashlyn Miller

Research in the Capitol

The purpose of this study is to explore the relationship between gender, viewing crime related material on social media, and fear of crime experienced by college students. While violent crime rates have fallen, the majority of college students report levels of crime are increasing. Many individuals lack both knowledge and experience related to crime, leading media exposure to influence their levels of fear. Previous research has focused on television media related to fear of crime with little research on social media, the preferred media source of young adults. College students (n = 126) from a midwestern university completed a survey …

Unearthing Uni's First Football Stadium, Hannah Huffman

Research in the Capitol

Campus archaeology conducted at the University of Northern Iowa unearths historical artifacts that are tied to the institution’s past. In 2020, students in the archaeological fieldwork class performed excavations at the former Latham Stadium site, where remnants of the structure were discovered, documented, and archived for further examination. My research of the artifacts includes collaborative efforts between university archives, close laboratory analysis, and the interpretation of hand-written journals from fieldwork students who recorded their data on-site. This interdisciplinary approach provides a comprehensive understanding of the site’s historical significance and glimpses of human occupation that span decades into the past.

An Argument For Expanding Research On Quantitative Pedagogical Content Knowledge, Randall E. Groth

Numeracy

Pedagogical content knowledge (PCK) traditionally has been used in research concerning prospective and practicing classroom teachers. This essay argues that PCK is also relevant to other professions including those advancing quantitative reasoning (QR). To illustrate, the case of PCK for teaching QR is considered. Those in fields such as public health, journalism, meteorology, and government increasingly find themselves responsible for helping the public understand an ever-growing amount of quantitative information that has a bearing on societal well-being. Several examples illustrate how such professionals’ responsibilities require knowing prevalent QR patterns in society, strategies for fostering sound reasoning, and the general nature …

A Case Study Of Backward Design In A Customized Business English Course For Global Supply Chain Vendors In Francophone Africa, Steven J. Sacco

Global Advances in Business Communication

The present article describes a case study in which the author used domain analysis to create a backward-designed remedial listening comprehension course for global supply chain vendors employed with logistics-focused multinational corporations operating in Francophone Africa. The course is designed to address weaknesses in listening comprehension skills as exhibited by global supply chain vendors in Francophone Africa who work daily with South Asian customers. The weaknesses emanate, in large part, from the existence of World Englishes due to the rise of English as a lingua franca by multinational corporations. World Englishes refers to the existence of “emerging localized or indigenized …

The Impact Of Using Blended Learning On Linguistic Fluency Towards Learning Among Palestinian University Students At English Departments According To Their Academic Achievement Level, نايل درويش الشرعة, Muawiyah Saleh Alawneh

Association of Arab Universities Journal for Education and Psychology

This study aimed at investigating the effect of using blended learning on the linguistic fluency towards learning English of second-year TEFEL students at the University College of Educational Sciences (UCES)/ UNRWA, Palestine, according to their academic achievement level. To achieve the aim of the study, the researcher constructed a pre-posttest and made sure of the validity and reliability of the study tool. A quasi-experimental approach followed. The participants of the study consisted of 60 students divided into experimental groups of 30 students who were exposed to the training program (blended learning) and a control group of 30 students who were …

The Role Of Kuwaiti Universities In Developing Awareness Of Political Participation Among Their Students From Students' Point Of View. دور الجامعات الكويتية في تنمية الوعي بالمشاركة السياسية لدى طلبتها من وجهة نظر الطلبة أنفسهم, محمد سليم الزبون, Abdul Aziz Muhammad Al-Rayes

Association of Arab Universities Journal for Education and Psychology

The study aimed to define the reality of the existence of a role for Kuwaiti universities in developing awareness of political participation among their students based on the ideas of Gabriel Almond from the point of view of the students themselves and its relationship to some variables.To achieve the objectives of the study the descriptive survey approach was used.The study sample consisted of (648) male and female students from Kuwait University and the Public Authority for Applied Education. The research relied on a questionnaire as a tool for the study. It consisted of (53) items distributed over three domains.The study …

The Effectiveness Of Employing The Ring House Shape Strategy In Acquiring The Scientific Concepts In Chemistry In The Tenth Grade Female Students In The Light Of Their Motivation Towards Learning Science. أثر استخدام إستراتيجية شكل البيت الدائري في اكتساب طالبات الصف العاشر الأساسي المفاهيم العلميّة في مادة الكيمياء في ضوء دافعيتهم نحو تعلّم العلوم, Ali Moqbel Al-Alimat

Association of Arab Universities Journal for Education and Psychology

This study aimed to investigate the effect of using ring house shape strategy on tenth grade Female students’ acquisition of scientific concepts. To achieve the objectives of the study, aquasi- experimental design was used. Two instruments were used: a test to measure the acquisition of scientific concepts and a scale to measure students’ motivation towards learning science. The subjects of the study consisted of (67) tenth grade students. They were chosen purposefully from a school for girls in Mafraq Educational Directorate. They were divided randomly into two groups: experimental group (n=33) who were taught by using ring house shape strategy …

The Status Quo Of Investment In Saudi Public Universities And Its Relationship To Some Variables. واقع الاستثمار في الجامعات السعودية العامة وعلاقته ببعض المتغيرات, صالح Ahmad عبابنة Dr, [email protected] Hamoud Al-Anazi

Association of Arab Universities Journal for Education and Psychology

The study aimed at identifying of the investment development in Saudi Arabia Universities. The study sample consisted of (309) academic leaders from Public Saudi Arabia Universities, which were selected using a random cluster sampling method representing the study population. To accomplish the purpose of study, a questionnaire was developed, and its validity and reliability were confirmed. The results of the study indicated that the reality of the application of investment development in Saudi universities and its relationship to some variables from the point of view of academic leaders came to a medium degree for all its domains: privatization of universities, …

Death Anxiety And Its Relationship To Social Support Among A Sample Of Elderly People "A Field Study On A Sample Of The Elderly In The Lebanese Beqaa Governorate". قلق الموت وعلاقته بالمساندة الاجتماعية لدى عينة من المسنين د ا رسة ميدانية على عينة من المسنين في محافظة البقاع اللبنانية, Nidal Muhammad Murtada

Association of Arab Universities Journal for Education and Psychology

The research aimed to identify the relationship between death anxiety and its relationship to social support among a sample of elderly people. To detect the differences in death anxiety and social support according to the variable of gender, the researcher relied on the descriptive analytical approach. The research sample consisted of (94) elderly men and women in Beqaa- Lebanon.To achieve the objectives of the research, the death anxiety scale was used. According to Templar, and the social support scale prepared by Spender, 1982.The following results were reached: The level of death anxiety among the members of the research sample was …

Acamda: Improving Data Efficiency In Reinforcement Learning Through Guided Counterfactual Data Augmentation, Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang

Machine Learning Faculty Publications

Data augmentation plays a crucial role in improving the data efficiency of reinforcement learning (RL). However, the generation of high-quality augmented data remains a significant challenge. To overcome this, we introduce ACAMDA (Adversarial Causal Modeling for Data Augmentation), a novel framework that integrates two causality-based tasks: causal structure recovery and counterfactual estimation. The unique aspect of ACAMDA lies in its ability to recover temporal causal relationships from limited non-expert datasets. The identification of the sequential cause-and-effect allows the creation of realistic yet unobserved scenarios. We utilize this characteristic to generate guided counterfactual datasets, which, in turn, substantially reduces the need …

Dynamic Spiking Graph Neural Networks, Nan Yin, Mengzhu Wang, Zhenghan Chen, Giulia De Masi, Huan Xiong, Bin Gu

Machine Learning Faculty Publications

The integration of Spiking Neural Networks (SNNs) and Graph Neural Networks (GNNs) is gradually attracting attention due to the low power consumption and high efficiency in processing the non-Euclidean data represented by graphs. However, as a common problem, dynamic graph representation learning faces challenges such as high complexity and large memory overheads. Current work often uses SNNs instead of Recurrent Neural Networks (RNNs) by using binary features instead of continuous ones for efficient training, which would overlooks graph structure information and leads to the loss of details during propagation. Additionally, optimizing dynamic spiking models typically requires propagation of information across …

Enhancing Training Of Spiking Neural Network With Stochastic Latency, Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojković, Giulia De Masi, Huan Xiong, Bin Gu

Machine Learning Faculty Publications

Spiking neural networks (SNNs) have garnered significant attention for their low power consumption when deployed on neuromorphic hardware that operates in orders of magnitude lower power than general-purpose hardware. Direct training methods for SNNs come with an inherent latency for which the SNNs are optimized, and in general, the higher the latency, the better the predictive powers of the models, but at the same time, the higher the energy consumption during training and inference. Furthermore, an SNN model optimized for one particular latency does not necessarily perform well in lower latencies, which becomes relevant in scenarios where it is necessary …

Exploring Channel-Aware Typical Features For Out-Of-Distribution Detection, Rundong He, Yue Yuan, Zhongyi Han, Fan Wang, Wan Su, Yilong Yin, Tongliang Liu, Yongshun Gong

Machine Learning Faculty Publications

Detecting out-of-distribution (OOD) data is essential to ensure the reliability of machine learning models when deployed in real-world scenarios. Different from most previous test-time OOD detection methods that focus on designing OOD scores, we delve into the challenges in OOD detection from the perspective of typicality and regard the feature’s high-probability region as the feature’s typical set. However, the existing typical-feature-based OOD detection method implies an assumption: the proportion of typical feature sets for each channel is fixed. According to our experimental analysis, each channel contributes differently to OOD detection. Adopting a fixed proportion for all channels results in several …

Iterative Regularization With K-Support Norm: An Important Complement To Sparse Recovery, William De Vazelhes, Bhaskar Mukhoty, Xiao Tong Yuan, Bin Gu

Machine Learning Faculty Publications

Sparse recovery is ubiquitous in machine learning and signal processing. Due to the NP-hard nature of sparse recovery, existing methods are known to suffer either from restrictive (or even unknown) applicability conditions, or high computational cost. Recently, iterative regularization methods have emerged as a promising fast approach because they can achieve sparse recovery in one pass through early stopping, rather than the tedious grid-search used in the traditional methods. However, most of those iterative methods are based on the ℓ1 norm which requires restrictive applicability conditions and could fail in many cases. Therefore, achieving sparse recovery with iterative regularization methods …

Limited Memory Online Gradient Descent For Kernelized Pairwise Learning With Dynamic Averaging, Hilal Alquabeh, William De Vazelhes, Bin Gu

Machine Learning Faculty Publications

Pairwise learning, an important domain within machine learning, addresses loss functions defined on pairs of training examples, including those in metric learning and AUC maximization. Acknowledging the quadratic growth in computation complexity accompanying pairwise loss as the sample size grows, researchers have turned to online gradient descent (OGD) methods for enhanced scalability. Recently, an OGD algorithm emerged, employing gradient computation involving prior and most recent examples, a step that effectively reduces algorithmic complexity to O(T), with T being the number of received examples. This approach, however, confines itself to linear models while assuming the independence of example arrivals. We introduce …

Robustly Train Normalizing Flows Via Kl Divergence Regularization, Kun Song, Ruben Solozabal, Hao Li, Martin Takáč, Lu Ren, Fakhri Karray

Machine Learning Faculty Publications

In this paper, we find that the training of Normalizing Flows (NFs) are easily affected by the outliers and a small number (or high dimensionality) of training samples. To solve this problem, we propose a Kullback–Leibler (KL) divergence regularization on the Jacobian matrix of NFs. We prove that such regularization is equivalent to adding a set of samples whose covariance matrix is the identity matrix to the training set. Thus, it reduces the negative influence of the outliers and the small sample number on the estimation of the covariance matrix, simultaneously. Therefore, our regularization makes the training of NFs robust. …

Knowledge-Aware Explainable Reciprocal Recommendation, Kai Huang Lai, Zhe Rui Yang, Pei Yuan Lai, Chang Dong Wang, Mohsen Guizani, Min Chen

Machine Learning Faculty Publications

Reciprocal recommender systems (RRS) have been widely used in online platforms such as online dating and recruitment. They can simultaneously fulfill the needs of both parties involved in the recommendation process. Due to the inherent nature of the task, interaction data is relatively sparse compared to other recommendation tasks. Existing works mainly address this issue through content-based recommendation methods. However, these methods often implicitly model textual information from a unified perspective, making it challenging to capture the distinct intentions held by each party, which further leads to limited performance and the lack of interpretability. In this paper, we propose a …

Prior And Prediction Inverse Kernel Transformer For Single Image Defocus Deblurring, Peng Tang, Zhiqiang Xu, Chunlai Zhou, Pengfei Wei, Peng Han, Xin Cao, Tobias Lasser

Machine Learning Faculty Publications

Defocus blur, due to spatially-varying sizes and shapes, is hard to remove. Existing methods either are unable to effectively handle irregular defocus blur or fail to generalize well on other datasets. In this work, we propose a divide-and-conquer approach to tackling this issue, which gives rise to a novel end-to-end deep learning method, called prior-and-prediction inverse kernel transformer (P2IKT), for single image defocus deblurring. Since most defocus blur can be approximated as Gaussian blur or its variants, we construct an inverse Gaussian kernel module in our method to enhance its generalization ability. At the same time, an inverse kernel prediction …

Skin-Former: Mobile-Friendly Transformer For Skin Lesion Diagnosis, Sheng Zhang, Muzammal Naseer, Guangyi Chen, Zhiqiang Shen, Salman Khan, Kun Zhang, Fahad Shahbaz Khan

Machine Learning Faculty Publications

Large-scale pre-trained Vision Language Models (VLMs) have proven effective for zero-shot classification. Despite the success, most traditional VLMs-based methods are restricted by the assumption of partial source supervision or ideal target vocabularies, which rarely satisfy the open-world scenario. In this paper, we aim at a more challenging setting, Realistic Zero-Shot Classification, which assumes no annotation but instead a broad vocabulary. To address the new problem, we propose the Self Structural Semantic Alignment (S3A) framework, which extracts the structural semantic information from unlabeled data while simultaneously self-learning. Our S3A framework adopts a unique Cluster-Vote-Prompt-Realign (CVPR) algorithm, which iteratively groups unlabeled data …

The Utah Statesman, March 25, 2024, Utah State University

The Utah Statesman

Weekly student newspaper of Utah State University in Logan.

Experimental Study On Acoustic Emission Evolution Characteristics And Response Mechanism Of Damaged Rocks, Zhang Kai, Zhang Dongxiao, Zhao Yongqiang, Yang Yingming, Guo Weiyao, Sun Peng, Xu Linpeng, Fu Guangsheng

Coal Geology & Exploration

The evolution of rock internal damage is one of the causes of geotechnical engineering disasters, and revealing the response characteristics of key parameters during the rock failure could provide a basis for the identification instability state after rock failure, which is of great importance for the early warning and prevention of rock engineering disasters. Herein, the siltstone specimens with different damage degrees were prepared by cyclic loading-unloading tests, and uniaxial loading tests were carried out with the damaged specimens. On this basis, the relationship between the damage degree of specimen and the wave velocity, as well as the acoustic emission …

Book Reviews: Jane Goodall At 90 & The Emotional Lives Of Animals, 2024 Revision, Andrew Rowan

Tales of WellBeing

Jane Goodall and Marc Bekoff have made significant contributions to our understanding of animal emotions and feelings.