Physical Sciences and Mathematics Commons^™

Impact Of Urban Development On Uv Exposure: A Clustering And Machine Learning Assessment, Taufik Roni Sahroni Mr., Verdi Yasin, Lulut Alfaris, Reza Ariefka, Ruben Cornelius Siagian, Mohammad Alfin Karim, Nana Rahdiana, Ade Suhara

Journal of Environmental Science and Sustainable Development

The relocation of Indonesia's capital city is anticipated to promote inclusive economic growth while embracing cultural diversity. However, this transition may affect ultraviolet (UV) radiation exposure patterns. The study investigated variations in UV exposure in the IKN region, focusing on urban development factors such as land use and population density that affect public health, sun protection, and skin cancer prevention. The research hypothesized that UV radiation is significantly correlated with these factors. UV Index data from 2010-2023, a hierarchical clustering method, identifies complex data patterns without determining the number of clusters. XGBoost, a machine learning model, was used for handling …

Surveying The Role Of Visual Analytics In Human-Machine Teaming, Naga Datha Saikiran Battula

Theses

Humans and machines both possess their unique capabilities and have their strengths and weaknesses, which can be complementary to one another and allow them to achieve a common goal. Teaming in the modern era involves text prompts, voice commands, gesture recognition, touch interfaces, and the latest visualization techniques that allow parties/agents to interact. Communication through visualization plays a vital role in allowing robust insights to be gained through a glance. Using visualization as a medium between humans and machines can increase the communication bandwidth. Human-machine teaming has witnessed much progress, with many theories and practical examples emerging. In the report, …

Automated Segmentation Of The Ulnar Nerve In Mri Using Deep Learning Techniques, Akhil Nagulapalli

Theses

Cubital Tunnel Syndrome (CuTS), a condition caused by compression of the ulnar nerve, results in numbness, tingling, pain, and even muscle atrophy, affecting fine motor skills and diminishing patient quality of life. Accurate diagnosis of CuTS is challenging, as current diagnostic methods—including clinical exams, nerve conduction studies, and unaided MRI—often lack the precision to reliably identify the nerve and detect compression in its early stages. Deep learning-based segmentation offers a promising solution, enabling precise and automated identification of nerve structures in MRI images, which could significantly improve diagnostic accuracy and support timely intervention.

A novel deep learning model for segmenting …

Advancing Prediction Of Stimulant Medication Misuse Through Graph Representation Learning, Hamid Razavi

Theses

The misuse of stimulant prescription medications poses a significant and escalating public health concern in the United States, particularly among young adults. Addressing this issue requires sophisticated methodologies capable of uncovering complex patterns and relationships in data. Geometric Deep Learning, a paradigm designed to analyze data with non-Euclidean structures, has achieved remarkable success across various domains, offering a powerful framework for tackling complex graph structure data challenges.

This study leverages Graph Convolutional Networks (GCNs) to predict the likelihood of stimulant medication misuse using data from the National Survey on Drug Use and Health (NSDUH). Individuals are represented as nodes in …

A New Form Of Soft Supersymmetry Breaking?, Scott Chapman

Mathematics, Physics, and Computer Science Faculty Articles and Research

Starting with a supersymmetric U(N) × U(N) gauge theory built in N = 1 superspace, a nonsupersymmetric theory is obtained by “twisting” the gauginos into a different representation of the group than the gauge bosons. Despite the fact that this twisting breaks supersymmetry, it is still possible to construct an action that is holomorphic and invariant to local “twisted” gauge transformations in superspace. It is conjectured that these two properties may allow the theory to be free of quadratic divergences to all orders, despite a lack of supersymmetry. An explicit calculation shows that the theory is free of quadratic divergences …

Multi-Sensor Data Fusion And Gis-Drastic Integration For Groundwater Vulnerability Assessment With Rainfall Consideration, Wu Jiazhe, Dai Xinrui, Su Yangcheng, Zheng Xiangtian, Bushra Ghaffar, Rabiya Nasir, Ahsan Jamil, Zeeshan Zafar, Mohammad Suhail Meer, M. Abdullah-Al-Wadud, Rahila Naseer, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

In many areas of the world, particularly in arid and semi-arid regions, groundwater is the primary source of fresh water, and it supplies around one-third of the world's fresh water. Agriculture is the primary economic sector on the coast in the southern district (Nowshera). More food productivity is required due to the expanding population and diminishing agricultural lands, which increases the use of chemical pesticides and fertilizers in farming. The current study was conducted in northwestern parts of Pakistan to evaluate the impacts of the frequent use of pesticides and fertilizers in agricultural fields. Nine hydrogeological parameters were considered, and …

Unfolding Cascading Impacts Of Changing South Asia Monsoon On A Hindu Kush Himalayas Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Arshad Ansari, Suraj Tiwari, Roma Thakurathi, Rejoice Thomas, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Study region

Study focus

New hydrological insights for the region

Adopting Association Rule Learning For Detecting And Ranking Influential Users On Hashtags, Layal Abu Daher, Islam Elkabani, Rashed Zantout

BAU Journal - Science and Technology

Social Media platforms are networks of relationships in which users are considered as nodes in a graph and relationships between users are considered edges. These graphs symbolize online groups or communities. It has been a challenge for researchers to study the evolution of such communities due to their rapid and dynamic development. The contribution of our work is twofold: (i) studying the effectiveness of a set of Direct and Indirect Influence Measures that identify the factors that urges users to participate in certain communities; (ii) proposing an Association Rule Mining technique to identify influential users on a dataset of a …

Cropsync: Ai-Powered Sustainable Crop Management, Ziad Doughan, Ibrahim Mneimneh, Zouheir Nakouzi, Noor Al Khaib, Samer Damaj, Jamal Chaaban, Hamza Mrad, Sari Itani

BAU Journal - Science and Technology

CropSync is a smart agriculture system that uses AI and IoT technologies to enable sustain- able crop management and precision farming. The system aims to address the challenges faced by the agriculture sector, such as increasing food production to meet global population demands while minimizing environmental impact. CropSync integrates sensors, cameras, and cloud-based analytics to provide farmers with real-time insights and recommendations for optimizing crop cul- tivation. The system upholds engineering professional and ethical standards, considering broader social, environmental, and economic implications. From a social perspective, CropSync improves food security and enhances farmers’ livelihoods through increased productivity and efficient re- …

Designed For Limb Loss: An Artificial Intelligence-Based Bionic Prosthetic Arm Transition From Simulation To Reality, Amira J. Zaylaa Dr., Imane Haidar, Ziad Doughan, Mohammad Moumnieh, Hamza Mrad, Ali M. Haidar

BAU Journal - Science and Technology

Limb or organ loss of human remains challenging especially in the world of incessant reliance on touch-based screens and tasks. Thereby, patients can barely withstand and cope with the augmenting restrictions that they encounter due to this loss. Modern means and technologies, such as advanced and artificial parts reduced restrictions on patients with disabilities or a lost limb or organ. Hand prostheses, for instance, provided a powerful tool for improving the functional capabilities of human limbs, thereby improving the quality of life of the user. However, patients using prosthetic arms are still encountering numerous problems, such as, suffering from intact …

The Faithfulness Of An Extension Of Lawrence-Krammer-Bigelow Representation On The Group Of Conjugating Automorphisms $C_N$ In The Cases $N=3$ And $N=4$, Mohamad Nasser

BAU Journal - Science and Technology

Let $C_n$ be the group of conjugating automorphisms. V. Bardakov defined a representation $\rho$ of $C_n$, which is an extension of Lawrence-Krammer-Bigelow representation of the braid group $B_n$. Bardakov proved that the representation $\rho$ is unfaithful for $n \geq 5$. The cases $n=3,4$ remain open. M. N. Nasser and M. N. Abdulrahim made attempts towards the faithfulness of $\rho$ in the case $n=3$. In this work, we prove that $\rho$ is unfaithful in the both cases $n=3$ and $n=4$.

A Novel Format For Math Circles: Circles With No Center, Frederick A. Peck, Ian P. Renga, Nick Grener, David R. Erickson, Matt B. Roscoe, Ke Wu

Journal of Math Circles

This paper shares a novel format for Math Circles, which we call “circles with no center.” Circles with no center do not have a traditional facilitator. The problem or activity is novel to everyone in the room. All members engage in mathematical inquiry, and everyone takes responsibility for running the gathering. The “no center” format has benefits for participants and organizers. For participants, the format offers more freedom and more responsibility. For organizers, the format is easier to organize, more fun, and involves less pressure. Our assessment of a 3-day retreat for teachers suggests participants may prefer a circle with …

Optimizing Vgg16 Deep Learning Model With Enhanced Hunger Games Search For Logo Classification, Mohammed Hussain, Thaer Thaher, Mohamed Basel Almourad, Majdi Mafarja

All Works

Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming. Swarm intelligence algorithms have been widely adopted to solve many highly nonlinear, multimodal problems and have succeeded significantly. The Hunger Games Search (HGS) is a recent swarm intelligence algorithm that has shown good performance across various applications. However, the standard HGS still faces limitations, such as restricted population …

Understanding Women, Infant And Children Feeding Decisions In Emergencies: The Case Of Covid-19 And The Formula Shortage, Davida Mensah, Edmund F. Agyemang, Constance Gewa

School of Mathematical & Statistical Sciences Faculty Publications

Background: The advantages of breastfeeding and its role in emergencies are undeniable. Studies show that many women in developed countries choose formula over breastmilk, even in emergencies. Nevertheless, no one knows if postpartum women under the Women, Infants and Children (WIC) program turned out to breastfeed or re-lactate their infants during these crises. This study aims to better understand WIC participants' perceptions about breastfeeding their babies in emergencies.

Methods: A chi-square test of independence was used to assess the association between breastfeeding choice and demographic characteristics and potential covariates of respondents. A post hoc analysis using Dunn's multiple comparisons test …

Surgical Delay-Associated Mortality Risk Varies By Subtype In Loco-Regional Breast Cancer Patients In Seer-Medicare, Macall Leslie Salewon, Rashmi Pathak, William Dooley, Ronald Squires, Hallgeir Rui, Inna Chervoneva, Takemi Tanaka

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

Substantial evidence supports that delay of surgery after breast cancer diagnosis is associated with increased mortality risk, leading to the introduction of a new Commission on Cancer quality measure for receipt of surgery within 60 days of diagnosis for non-neoadjuvant patients. Breast cancer subtype is a critical prognostic factor and determines treatment options; however, it remains unknown whether surgical delay-associated breast cancer-specific mortality (BCSM) risk differs by subtype. This retrospective cohort study aimed to assess whether the impact of delayed surgery on survival varies by subtype (hormone [HR] + /HER2 -, HR -/HER2 -, and HER2 +) in patients with …

Combining Direct Black Hole Mass Measurements And Spatially Resolved Stellar Kinematics To Calibrate The Mbh–Σ⋆ Relation Of Active Galaxies, Nico Winkel, Vardha N. Bennert, Raymond P. Remigio, Tommaso Treu, Knud Jahnke, Vivian U, Aaron J. Barth, Matthew Malkan, Bernd Husemann, Xuheng Ding

Physics

The origin of the tight scaling relation between the mass of supermassive black holes (SMBHs; MBH) and their host-galaxy properties remains unclear. Active galactic nuclei (AGNs) probe phases of ongoing SMBH growth and offer the only opportunity to measure MBH beyond the local Universe. However, determining an AGN's host galaxy's stellar velocity dispersion, σ⋆, and its galaxy dynamical mass, Mdyn, is complicated by AGN contamination, aperture effects, and different host-galaxy morphologies. We select a sample of AGNs for which MBH has been independently determined to high accuracy by state-of-the-art techniques: dynamical modeling of the reverberation …

Agfi-Gan: An Attention-Guided And Feature-Integrated Watermarking Model Based On Generative Adversarial Network Framework For Secure And Auditable Medical Imaging Application, Xinyun Liu, Ronghua Xu, Chen Zhao

Michigan Tech Publications

With the rapid digitization of healthcare, the secure transmission of medical images has become a critical concern, especially given the increasing prevalence of cyber threats and data privacy breaches. Medical images are frequently transmitted via the Internet and cloud platforms, making them susceptible to unauthorized access, tampering, and theft. While traditional cryptographic techniques play a vital role, they are often insufficient to fully ensure the integrity and confidentiality of these sensitive images. In this paper, we present AGFI-GAN, a robust and secure framework for medical image watermarking that leverages attention-guided and Feature-Integrated mechanisms within a Generative Adversarial Network (GAN). Specifically, …

Spectral Differencing Of Glories Reflects Cloud Droplet Size Distribution, Ilan Koren, Alex Kostinski, Uri Wollner

Michigan Tech Publications

The glory, a striking optical phenomenon seen from space in unpolarized satellite images can be mapped onto the cloud's droplet sizes with a characteristic scale of 10 (Formula presented.). Such a mapping allows us to infer the mean and variance of the cloud droplets' radius, an important property that has remained elusive and inaccessible to passive unpolarized satellite sensing. Here, we propose a simple and robust polarization-like differential approach to map the glory's spectral properties to the desired moments of the droplet size distribution. By taking the differences between two spectrally close channels, we reduce multiple scattering contributions and amplify …

Text-To-Text Generative Approach For Enhanced Complex Word Identification, Patrycja Śliwiak, Syed Afaq Ali Shah

Research outputs 2022 to 2026

This paper presents a novel approach for solving the Complex Word Identification (CWI) task using the text-to-text generative model. The CWI task involves identifying complex words in text, which is a challenging Natural Language Processing task. To our knowledge, it is a first attempt to address CWI problem into text-to-text context. In this work, we propose a new methodology that leverages the power of the Transformer model to evaluate complexity of words in binary and probabilistic settings. We also propose a novel CWI dataset, which consists of 62,200 phrases, both complex and simple. We train and fine-tune our proposed model …

Electrochemical-Method-Induced Strong Metal-Support Interaction In Pt-Cnt@Sno2 For Co-Tolerant Hydrogen Oxidation Reaction, Shen-Zhou Li, Zi-Jie Lin, Qi-An Chen, Zhao Cai, Qing Li

Journal of Electrochemistry

Inducing the classic strong metal-support interaction (SMSI) is an effective approach to enhance the performance of supported metal catalysts by encapsulating the metal nanoparticles (NPs) with supports. Conventional thermal reduction method for inducing SMSI processes is often accompanied by undesirable structural evolution of metal NPs. In this study, a mild electrochemical method has been developed as a new approach to induce SMSI, using the cable structured core@shell CNT@SnO₂ loaded Pt NPs as a proof of concept. The induced SnO_x encapsulation layer on the surface of Pt NPs can protect Pt NPs from the poisoned of CO impurity in …

Dendrite-Free Strategies For Aqueous Zinc-Ion Batteries: Structure, Electrolyte, And Separator, Gang Wu, Wu-Hai Yang, Yang Yang, Hui-Jun Yang

Journal of Electrochemistry

Continued growth in energy demand and increased environmental pollution constitute major challenges that need to be addressed urgently. The development and utilization of renewable, sustainable, and clean energy sources, such as wind and solar, are crucial. However, the instability of these intermittent energy sources makes the need for energy storage systems increasingly urgent. Aqueous zinc-ion batteries (AZIBs) have received widespread attention due to their unique advantages, such as high energy density, cost-effectiveness, environmental friendliness, and safety. However, AZIBs face significant challenges, mainly the formation of zinc dendrites that seriously affect the stability and lifetime of the batteries, leading to battery …

All-Solid-State Sodium-Ion Batteries: A Leading Contender In The Next-Generation Battery Race, Rui-Jie Zhu, Ze-Chen Li, Wei Zhang, Akira Nasu, Hiroaki Kobayashi, Masaki Matsui

Journal of Electrochemistry

All-solid-state lithium-ion batteries (LIBs) using ceramic electrolytes are considered the ideal form of rechargeable batteries due to their high energy density and safety. However, in the pursuit of all-solid-state LIBs, the issue of lithium resource availability is selectively overlooked. Considering that the amount of lithium required for all-solid-state LIBs is not sustainable with current lithium resources, another system that also offers the dual advantages of high energy density and safety— all-solid-state sodium-ion batteries (SIBs) —holds significant sustainable advantages and is likely to be the strong contender in the competition for developing next-generation high-energy-density batteries. This article briefly introduces the research …

Contributions To Journal Of Electrochemistry, The Flagship Journal Of Chinese Chemical Society Electrochemical Committee, Will Be Listed As A New Recommendation Policy For China Youth Awards Of Electrochemist, Editorial Office Of J.Electrochem.

Journal of Electrochemistry

No abstract provided.

Muramyl Peptide Blend Ameliorates Intestinal Inflammation And Barrier Integrity In Caco-2 Cells, Dmytro M. Masiuk, Victor S. Nedzvetsky, Giyasettin Baydas

Karbala International Journal of Modern Science

Intestinal barrier function depends on epithelial adhesion, which restricts permeability and microbial invasion from the internal environment. Impairment of barrier integrity and gut function is closely linked to pro-inflammatory changes. Inflammation is often the primary factor that provokes gut function disorders. The anti-inflammatory potential of postbiotics has been reported in recent years. Muramyl peptides (MPs) are small signaling molecules that stimulate intracellular pathogen receptors and can regulate cell responses. However, the molecular mechanisms of MPs' effects on intestinal cells remain unknown. The study of MPs treatment on lipopolysaccharide (LPS)-challenged Caco-2 intestinal cells aimed to investigate the postbiotic effects on intestinal …

The Globular Cluster System Of The Virgo Cluster Ultradiffuse Galaxy Vcc 615, J. C. Mihos, Patrick R. Durrell, Elisa Toloba, Eric W. Peng, Sungsoon Lim, Patrick Côté, Puragra Guhathakurta, Laura Ferrarese

Pacific Faculty Work

We use Hubble Space Telescope imaging to study the globular cluster system of the Virgo Cluster ultradiffuse galaxy (UDG) VCC 615. We select globular cluster candidates through a combination of size and color, while simultaneously rejecting contamination from background galaxies that would be unresolved in ground-based imaging. Our sample of globular cluster candidates is essentially complete down to a limiting magnitude of F814W = 24.0, ≈90% down the globular cluster luminosity function (GCLF). We estimate a total globular cluster population for VCC 615 of N GC = 25 . 1 − 5.4 + 6.5 , resulting in a specific frequency …

Potential Health Risks From Trace Elements In Four Commercially Important Fish Species From The Gulf Of Alaska And Bering Sea Excel Data Sheet, Miranda Brohman, Dimtirios Giarikos, Amy Hirons

SECLER Data

Alaskan waters support a diverse array of fish species that are critical to apex predators and substantial commercial fisheries. Archived white lateral muscle tissue for capelin, herring, walleye pollock, and Pacific cod, from 1993 to 1996 were analyzed for 15 trace elements using induced coupled plasma mass spectrometry. This analysis serves as a proxy for assessing trace element concentrations in the Gulf of Alaska and Bering Sea. The highest concentrations of eight of the 15 elements (cadmium, chromium, cobalt, iron, manganese, selenium, vanadium, and zinc) were found in fish from the central Gulf of Alaska, while capelin showed the …

Explainable Artifacts For Synthetic Western Blot Source Attribution, João Phillipe Cardenuto, Sara Mandelli, Daniel Moreira, Paolo Bestagini, Edward J. Delp, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Recent advancements in artificial intelligence have enabled generative models to produce synthetic scientific images that are indistinguishable from pristine ones, posing a challenge even for expert scientists habituated to working with such content. When exploited by organizations known as paper mills, which systematically generate fraudulent articles, these technologies can significantly contribute to the spread of misinformation about ungrounded science, potentially undermining trust in scientific research. While previous studies have explored black-box solutions, such as Convolutional Neural Networks, for identifying synthetic content, only some have addressed the challenge of generalizing across different models and providing insight into the artifacts in synthetic …

Localization Of Synthetic Manipulations In Western Blot Images, Anmol Manjunath, Viola Negroni, Sara Mandelli, Daniel Moreira, Paolo Bestagini

Computer Science: Faculty Publications and Other Works

Recent breakthroughs in deep learning and generative systems have significantly fostered the creation of synthetic media, as well as the local alteration of real content via the insertion of highly realistic synthetic manipulations. Local image manipulation, in particular, poses serious challenges to the integrity of digital content and societal trust. This problem is not only confined to multimedia data, but also extends to biological images included in scientific publications, like images depicting Western blots. In this work, we address the task of localizing synthetic manipulations in Western blot images. To discriminate between pristine and synthetic pixels of an analyzed image, …

Effects Of Missing Data Imputation Methods On Univariate Blood Pressure Time Series Data Analysis And Forecasting With Arima And Lstm, Nicholas Niako, Jesus D. Melgarejo, Gladys E. Maestre, Kristina Vatcheva

School of Mathematical & Statistical Sciences Faculty Publications

Background: Missing observations within the univariate time series are common in real-life and cause analytical problems in the flow of the analysis. Imputation of missing values is an inevitable step in every incomplete univariate time series. Most of the existing studies focus on comparing the distributions of imputed data. There is a gap of knowledge on how different imputation methods for univariate time series affect the forecasting performance of time series models. We evaluated the prediction performance of autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) network models on imputed time series data using ten different imputation techniques. …

Immune Checkpoint Inhibitor-Associated Cutaneous Adverse Events: Mechanisms Of Occurrence, Abdulaziz M. Eshaq, Thomas W. Flanagan, Abdulqader A. Ba Abbad, Zain Alabden A. Makarem, Mohammed S. Bokir, Ahmed K. Alasheq, Sara A. Al Asheikh, Abdullah M. Almashhor, Faroq Binyamani, Waleed A. Al-Amoudi, Abdulaziz S. Bawzir, Youssef Haikel, Mossad Megahed, Mohamed Hassan

School of Medicine Faculty Publications

Immunotherapy, particularly that based on blocking checkpoint proteins in many tumors, including melanoma, Merkel cell carcinoma, non-small cell lung cancer (NSCLC), triple-negative breast (TNB cancer), renal cancer, and gastrointestinal and endometrial neoplasms, is a therapeutic alternative to chemotherapy. Immune checkpoint inhibitor (ICI)-based therapies have the potential to target different pathways leading to the destruction of cancer cells. Although ICIs are an effective treatment strategy for patients with highly immune-infiltrated cancers, the development of different adverse effects including cutaneous adverse effects during and after the treatment with ICIs is common. ICI-associated cutaneous adverse effects include mostly inflammatory and bullous dermatoses, as …