Ilyas Ustun

DePaul University · Data Science

Introduction Preeclampsia (PreE) remains a major source of maternal and newborn complications. Prenatal prediction of these complications could significantly improve pregnancy management. Objectives Using metabolomic analysis we investigated the prenatal prediction of maternal and newborn complications in early and late PreE and investigated the p...

Background: Alzheimer's disease (AD) is the most common form of dementia, accounting for 80% of all cases. Mild cognitive impairment (MCI) is a transitional state between normal aging and AD. Early detection is crucial, as irreversible brain damage occurs before symptoms manifest. Objective: This study aimed to identify potential biomarkers for...

This prospective observational study aimed to evaluate the association of metabolomic alterations with weight loss outcomes following sleeve gastrectomy (SG). We evaluated the metabolomic profile of serum and feces prior to SG and three months post-SG, along with weight loss outcomes in 45 adults with obesity. The percent total weight loss for the...

Computational progressive failure analysis (PFA) is vital for the analysis of carbon fiber reinforced polymer (CFRP) composites. The damage initiation criterion is one of the essential components of a PFA code to determine the transition of a material's state from pristine or microscopically damaged to macroscopically damaged. In this paper, data‐d...

View Video Presentation: https://doi.org/10.2514/6.2022-0104.vid Computational progressive failure analysis (PFA) is vital for the design, verification, and validation of carbon fiber reinforced polymer (CFRP) composites. However, the computational cost of PFA is usually high due to the complexity of the model. The damage initiation criterion is on...

Alzheimer’s disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of AD pathology (Braak 0–6). Using high-resolution mass spectrometry, we em...

Objective To identify maternal second and third trimester urine metabolomic biomarkers for the detection of fetal congenital heart defects (CHDs). Study design This was a prospective study. Metabolomic analysis of randomly collected maternal urine was performed, comparing pregnancies with isolated, non-syndromic CHDs versus unaffected controls. Ma...

Empty truck trips constitute an important aspect of commodity-based freight planning and modeling. But this information is generally not available to state Departments of Transportation (DOTs) or Metropolitan Planning Organizations (MPOs) since detecting empty trips is a challenge with traditional vehicle sensors as they do not provide the body typ...

CSF from unique groups of Parkinson's disease (PD) patients was biochemically profiled to identify previously unreported metabolic pathways linked to PD pathogenesis, and novel biochemical biomarkers of the disease were characterized. Utilizing both 1 H NMR and DI-LC-MS/MS we quantitatively profiled CSF from patients with sporadic PD (n = 20) and t...

Background: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer’s disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new,...

IntroductionAutism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficiencies in social interactions and communication, combined with restricted and repetitive behavioral issues.Objectives As little is known about the etiopathophysiology of ASD and early diagnosis is relatively subjective, we aim to employ a ta...

Background: CSF from unique groups of Parkinson’s disease (PD) patients were biochemically profiled to identify previously unreported metabolic pathways linked to PD pathogenesis and novel biochemical biomarkers of the disease were characterized. Methods: Utilizing both ¹H NMR and DI-LC-MS/MS we quantitatively profiled CSF from patients with sporad...

This paper is focused on developing an algorithm to estimate vehicle speed from accelerometer data generated by an onboard smartphone. The kinetic theory tells that the integration of acceleration gives the speed of a vehicle. Thus, the integration of the acceleration values collected with the smartphone in the direction of motion would theoretical...

According to the Federal Highway Administration (FHWA), US work zones on freeways account for nearly 24% of nonrecurring freeway delays and 10% of overall congestion. Historically, there have been limited scalable datasets to investigate the specific causes of congestion due to work zones or to improve work zone planning processes to characterize t...

This paper is focused on developing machine learning algorithms to extract useful traffic information from crowdsourced data. In particular, high-resolution accelerometer data collected by smartphones onboard vehicles are analyzed, and advanced classification algorithms are developed to reliably detect vehicle stops (e.g., at traffic signals). Supp...

The transportation sector accounts for one third of greenhouse gas emissions in USA. In addition, billions of gallons of fuel are wasted every year due to congestion. To address these challenges, transportation decision makers need data to understand how emissions vary over the network links by the time of day. To support that, this project aims to...

Recent studies show that the market share of smartphones continues to grow with over 60 percent U.S. mobile subscribers owning smartphones as of December 2013. Smartphones have matured as a computing platform and are now equipped with multiple low-energy sensors including gyroscope, compass, accelerometer, proximity sensor, and ambient light sensor...

Vehicle reidentification methods can be used to anonymously match vehicles crossing two locations based on vehicle attribute data. This paper investigates key factors that affect the accuracy of vehicle reidentification algorithms. The analyses are performed with reidentification algorithms to match commercial vehicles that cross upstream and downs...

Istanbul Strait is one of the most crowded, narrowest straits in the world. Even though the number of accidents has been decreased in recent years, the risk is still high. Simulation of marine traffic in Istanbul Strait is very important to be able to see the effects of different management strategies and possible changes in the parameters that aff...

Origin-destination (OD) flows are important for transportation planning and modeling. The main objective of this paper is to estimate OD flows for trucks based on re-identification algorithms. Trucks crossing two weigh-in-motion (WIM) sites are anonymously re-identified based on axle spacing and axle weight data. The sites selected for this study a...