Physical Sciences and Mathematics Commons^™

Aspdb: An Integrative Knowledgebase Of Human Protein Isoforms From Experimental And Ai-Predicted Structures, Rongbin Li, Wenbo Chen, Chiamaka S Diala, Meer A Ali, Yi Xu, Albon Wu, Sayed-Rzgar Hosseini, Erfei Bi, Hongyu Zhao, Pora Kim, W Jim Zheng

Faculty, Staff and Student Publications

Alternative splicing is a crucial cellular process in eukaryotes, enabling the generation of multiple protein isoforms with diverse functions from a single gene. To better understand the impact of alternative splicing on protein structures, protein-protein interaction and human diseases, we developed ASpdb (https://biodataai.uth.edu/ASpdb/), a comprehensive database integrating experimentally determined structures and AlphaFold 2-predicted models for human protein isoforms. ASpdb includes over 3400 canonical isoforms, each represented by both experimentally resolved and predicted structures, and >7200 alternative isoforms with AlphaFold 2 predictions. In addition to detailed splicing events, 3D structures, sequence variations and functional annotations, ASpdb uniquely offers comparative analyses and …

Metsdb: A Knowledgebase Of Cancer Metastasis At Bulk, Single-Cell And Spatial Levels, Zhaocan Zhang, Zhennan Lu, Pora Kim, Xiaobo Zhou, Liyu Huang

Faculty, Staff and Student Publications

Cancer metastasis, the process by which tumour cells migrate and colonize distant organs from a primary site, is responsible for the majority of cancer-related deaths. Understanding the cellular and molecular mechanisms underlying this complex process is essential for developing effective metastasis prevention and therapy strategies. To this end, we systematically analysed 1786 bulk tissue samples from 13 cancer types, 988 463 single cells from 17 cancer types, and 40 252 spots from 45 spatial slides across 10 cancer types. The results of these analyses are compiled in the metsDB database, accessible at https://relab.xidian.edu.cn/metsDB/. This database provides insights into alterations in …

Crisprofft: Comprehensive Database Of Crispr/Cas Off-Targets, Pora Kim, Qianqian Song, Xiaona Liu, Xiaobo Zhou

Faculty, Staff and Student Publications

The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated protein) programmable nuclease system continues to evolve, with in vivo therapeutic gene editing increasingly applied in clinical settings. However, off-target effects remain a significant challenge, hindering its broader clinical application. To enhance the development of gene-editing therapies and the accuracy of prediction algorithms, we developed CRISPRoffT (https://ccsm.uth.edu/CRISPRoffT/). Users can access a comprehensive repository of off-target regions predicted and validated by a diverse range of technologies across various cell lines, Cas enzyme variants, engineered sgRNAs (single guide RNAs) and CRISPR editing systems. CRISPRoffT integrates results of off-target analysis from 74 studies, encompassing …

Infografía: El Nexo De Unión Entre Ciencia Y Diseño Gráfico, Ángel Serrano Valverde, Almudena Torres Pardo

GDI. Revista de investigación de Género, Diseño e Innovación

En la divulgación científica, tanto en la que se realiza en congresos de alto impacto y nivel académico, como en la que encontramos en los museos, en los libros de texto o en las redes sociales, se están utilizando infografías. Principalmente, para explicar procesos complejos y sucesos no observables sin el uso de instrumentación específica, o no reproducibles con sencillez.

Este artículo investiga esa relación entre ciencia y diseño a través de la infografía, recorriendo la historia de la infografía científica y su uso en los diferentes ámbitos divulgativos actuales.

Desde un punto de vista científico y de diseño, analizaremos …

Constructing A Metadata Knowledge Graph As An Atlas For Demystifying Ai Pipeline Optimization, Revathy Venkataramanan, Aalap Tripathy, Tarun Kumar, Sergey Serebryakov, Annmary Justine, Arpit Shah, Suparna Bhattacharya, Martin Foltin, Paola Faraboschi, Kaushik Roy, Amit P. Sheth

Faculty Publications

The emergence of advanced artificial intelligence (AI) models has driven the development of frameworks and approaches that focus on automating model training and hyperparameter tuning of end-to-end AI pipelines. However, other crucial stages of these pipelines such as dataset selection, feature engineering, and model optimization for deployment have received less attention. Improving efficiency of end-to-end AI pipelines requires metadata of past executions of AI pipelines and all their stages. Regenerating metadata history by re-executing existing AI pipelines is computationally challenging and impractical. To address this issue, we propose to source AI pipeline metadata from open-source platforms such as Papers-with-Code, OpenML, …

Elastomeric Nanocomposite With Solvent-Free, One Step, In Situ Shear Exfoliation Of Graphite To Graphene, Ashiqur Rahman, Md Abdur Rahman Bin Abdus Salam, Matthew G. Boebinger, Ahmed Touhami, Jennifer Lynch, Ali Ashraf

Physics & Astronomy Faculty Publications

A graphene nanoflake (GNF)-enhanced elastomeric nanocomposite (G-EMC) is fabricated following an innovative, cost-effective, single-step, in situ shear exfoliation (ISE) method from low-cost bulk material, graphite, where uniform mixing happens simultaneously within the elastomer matrix. Electron microscopy, atomic force microscopy, and photo-induced force microscopy results show good dispersion of GNFs with exfoliation to a few layers and uniform distribution in the elastomer matrix. X-ray photoelectron spectroscopy analysis shows less than 1% oxygen-containing functional groups/impurity, enhanced bonding through the formation of edge sites as fracture occurs across the GNF basal plane, and pi-pi interactions with newly exfoliated planar basal plane surfaces of …

Ur-213 Generative Ai & Cybersecurity, Seth G Canada, Shreya Katare

C-Day Computing Showcase

This research project details the impact of Generative AI on Cybersecurity through both its potential enhancements and threats. Using advanced AI algorithms, this project explores how Generative AI can strengthen cybersecurity through systems like Anomaly Detection, Intrusion Detection Systems (IDS), and Malware Analysis. Also, this project addresses the growing challenges posed from Generative AI. In particular, issues surrounding Deepfake Phishing and Polymorphic Malware are discussed. Solutions to mitigate these issues are also provided to engage further understanding in the field. The goal of this research is to offer practical solutions for addressing the growing field of AI-driven cybersecurity.

An Attempt To Determine The Strong Tremors Causes During Longwall Mining Of Destressed Bottom Layer Of A Thick Coal Seam, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska

Journal of Sustainable Mining

The sequence and method of coal seam mining can significantly minimize the risk of rock bursts. The planning of exploitation in the Bielszowice part of the Ruda Hard Coal Mine involves maximizing the destress effect associated with the mining of adjacent coal seams or layers of thick coal seams. Longwall mining of destressed coal seams is characterized by much lower seismic activity; however, even during such mining, high-energy tremors may occur. This article analyzes the seismic activity accompanying the mining of longwall panels in the bottom and top layers of thick seam No. 510 and seam No. 507 in the …

Collision-Free Exploration By Mobile Agents Using Pebbles, Sajal K. Das, Amit Kumar Dhar, Barun Gorain, Madhuri Mahawar

Computer Science Faculty Research & Creative Works

In this paper, we study collision-free graph exploration in an anonymous network. The network is modeled as a graph G = (V, E) where the nodes of the graph are unlabeled, and each edge incident to a node v has a unique label, called the port number, in {0, 1, ⋯, d - 1}, where d is the degree of the node v. Two identical mobile agents, starting from different nodes in G have to explore the nodes of G in such a way that for every node v in G, at least one mobile agent visits v and no …

Smevca: Stable Matching-Based Ev Charging Assignment In Subscription-Based Models, Arindam Khanda, Anurag Satpathy, Anusha Vangala, Sajal K. Das

Computer Science Faculty Research & Creative Works

The rapid shift from internal combustion engine vehicles to battery-powered electric vehicles (EVs) presents considerable challenges, such as limited charging points (CPs), unpredictable wait times for charging, and difficulty in selecting appropriate CPs for EVs. To address these challenges, we propose a novel end-to-end framework, called Stable Matching based EV Charging Assignment (SMEVCA) that efficiently assigns charge-seeking EVs to CPs with the assistance of roadside units (RSUs). The proposed framework operates within a subscription-based model, ensuring that the subscribed EVs complete their charging within a predefined time limit enforced by a service level agreement (SLA). The framework SMEVCA employs a …

Adaptive Workload Management For Enhanced Function Performance In Serverless Computing, Priyanka Ashok Birajdar, V. Harsha, Anurag Satpathy, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

Serverless computing streamlines application deployment by removing the need for infrastructure management, but fluctuating workloads make resource allocation challenging. To solve this, we propose an adaptive workload manager that intelligently balances workloads, optimizes resource use, and adapts to changes with auto-scaling, ensuring efficient and reliable serverless performance. Preliminary experiments demonstrate an ≈ 0.6X% and 2X% improvement in execution time and resource utilization compared to the First-Come-First Serve (FCFS) scheduling algorithm.

A Second Candidate Magnetic Helium Core White Dwarf And 3 Other Variable White Dwarfs In The Globular Cluster Ngc 6397, Manuel Pichardo Marcano, Liliana E. Rivera Sandoval, Thomas J. Maccarone, Rene D. Rohrmann, Leandro G. Althaus, Craig O. Heinke, Diogo Belloni, Arash Bahramian

Physics & Astronomy Faculty Publications

Using archival Hubble Space Telescope observations, we report the discovery of four variable low-mass white dwarfs (WDs; 0.18 M⊙ ≤ M ≤ 0.5 M⊙) in the globular cluster NGC 6397. One source exhibits a periodic optical modulation of 5.21 ± 0.02 hr, which we interpret as potentially due to the rotation of a magnetic helium core WD (He WD). This makes this candidate the second magnetic He WD in NGC 6397, and one of the few He WDs with a measured rotation period. The other three candidates show aperiodic variability, with a change in magnitude ranging from ∼0.11 …

In Memoriam: Dr. Rodney M. “Rod” Feldmann (1939–2024), Sigma Gamma Epsilon’S Longest-Serving Chapter Advisor, Joseph D. Ortiz, Richard L. Ford

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon (SGE), Kent State University (KSU), and the geoscience community lost a loyal supporter, remarkable student mentor, and world-renowned paleontologist when Dr. Rodney M. “Rod” Feldmann died peacefully at home on May 1, 2024, at the age of 84. He is survived by his wife Dr. Carrie Schweitzer (Kent, OH), his daughter Aissa Feldmann (Durham, NC), and his brothers, Frank George (Helen) DuPree (Billings, MT) and Don Keck (Mary Grace) DuPree (Atlanta, GA).

Geospatial Machine Learning Approaches For Studying Urbanization Impact, Surface Reflectance Patterns, And Groundwater Health Risks, Bibhash Nath

Theses and Dissertations

Geospatial machine learning techniques have been used to study: the impact of urbanization on land use and land cover change, surface reflectance patterns in boreal regions, and groundwater health risks from arsenic in India. These studies combined spatial data, remote sensing, and predictive models to gain valuable insights for sustainable living and protecting human health.

Supplementary Files For: "Structure Identification For High-Dimensional Data In The Vicinity Of Bear Lake", Ben Shaw, Haley Burger, Brennan Bean, Kevin Moon

Browse all Datasets

This report focuses on seven water quality measurements taken at 43 different depths on the Bear Lake for the months of June - November in the years 2018 - 2023. These measurements create a high-dimensional dataset on which we apply state-of-the-art machine learning (ML) techniques to look for low-dimensional structure in the data. A similar effort was made for weather measurements taken near the lake. Our analysis revealed that water quality measurements tend to cluster (i.e., group together) by year, while weather measurements tend to cluster by time of the year. This suggests that the structure observed in the water …

Data Supporting "Cloud Microphysical Response To Entrainment Of Dry Air Containing Aerosols", Will Cantrell, Jae Min Yeom, Hamed F. Sadi, Jesse Anderson, Fan Yang, Raymond Shaw

Michigan Tech Research Data

Aerosol particles play a pivotal role in shaping clouds, precipitation, and climate. However, it still remains one of the significant uncertainties in climate change. While most aerosols are activated at the cloud base, the aerosol particles entrained from the cloud top or edges can also contribute to droplet formation above the base. This process might significantly impact cloud properties and lifetimes.

In this study, we investigate how entraining aerosol-laden air affects cloud microphysics by adding aerosol particles to the dry-air inflow in the Pi chamber experiments. The findings show that the cloud droplet number concentration and liquid water content increase …

Elastic Scheduling For Graceful Degradation Of Mixed-Criticality Systems, Zhuoran Sun, Marion Sudvarg, Christopher Gill

Computer Science Faculty Research & Creative Works

Many mixed-criticality system models drop all jobs of low-criticality tasks when a criticality mode switch occurs, ensuring that high-criticality tasks still can meet their deadlines in the new mode. However, this means that even important low-criticality tasks are discarded, which may not be acceptable in some systems in practice. This paper addresses that distinction between criticality and importance through a new Inelastic Graceful Earliest Deadline First with Virtual Deadlines (IG-EDF-VD) scheme that upon a criticality mode switch only discards the least important low-criticality tasks necessary to ensure feasibility. Moreover, we consider elastic scheduling within our mixed-criticality model (EG-EDF-VD), using compression …

Development Of Interface-Specific Two-Dimensional Vibrational-Electronic (I2d-Ve) Spectroscopy For Vibronic Couplings At Interfaces, Yuqin Qian, Zhi-Chao Huang-Fu, Jesse B. Brown, Yi Rao

Chemistry and Biochemistry Faculty Publications

Bulk 2D electronic–vibrational (2D-EV) and 2D vibrational–electronic spectroscopies (2D-VE) were previously developed to correlate the electronic and vibrational degrees of freedom simultaneously, which allow for the study of couplings between electronic and vibrational transitions in photo-chemical systems. Such bulk-dominated methods have been used to extensively study molecular systems, providing unique information such as coherence sensitivity, molecular configurations, enhanced resolution, and correlated states and their dynamics. However, the analogy of interfacial 2D spectroscopy has fallen behind. Our recent work presented interface-specific 2D-EV spectroscopy (i2D-EV). In this work, we develop interface-specific two-dimensional vibrational–electronic spectroscopy (i2D-VE). The fourth-order spectroscopy is based on a …

Sigma Gamma Epsilon Student Research Poster Session, Geological Society Of America Connects 2024, Anaheim, California, Usa, Scott R. Beason, Lee S. Potter

The Compass: Earth Science Journal of Sigma Gamma Epsilon

The Society of Sigma Gamma Epsilon sponsors a poster session at every annual meeting of the Geological Society of America. The 36th Sigma Gamma Epsilon undergraduate research poster session took place during the 2024 Geological Society of America Annual Meeting (GSA Connects) in Anaheim, California, USA, on Monday, September 23, 2024. Twenty-eight (28) posters were presented in Exhibit Hall D at the Anaheim Convention Center between 8:00 AM and 5:30 PM at the poster session. Titles, authors (italics for the presenting author), affiliations, and abstracts for each poster are listed in this report. Additionally, winners of the Austin A. Sartin …

Spring 2025 Letter From The President Of Sigma Gamma Epsilon, Steve W. Bennett

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

Spring 2025 Letter From The National Secretary-Treasurer Of Sigma Gamma Epsilon, Richard L. Ford

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

The Compass - Volume 94 Issue 1 - Complete Issue, Scott R. Beason

The Compass: Earth Science Journal of Sigma Gamma Epsilon

No abstract provided.

Development And Characterization Of Sodium Alginate-Based Active Edible Films Functionalized With Olive Mill Wastewater Extract, Nassima Hadri, Mohamed Didi Ould El-Hadj, Zineb Mahcene, Fatih Bozkurt, Rusen Metin Yildirim, Youcef Rahmani, Aicha Tedjani, Muhammet Arici

Karbala International Journal of Modern Science

Phenolic compounds from olive mill wastewater (PCO) of Algerian origin were used to produce sodium alginate-based active films using the casting method. The effects of adding various concentrations of PCO (0%, 0.1%, and 0.2% w/v) were evaluated regarding the molecular, morphological, thermal, physicochemical, optical, barrier, biodegradability, antimicrobial, and antioxidant properties of the alginate films. The FTIR and SEM results elucidated the development of a coherent cross-linked structure attributed to hydrogen bonding interactions between PCO and alginate chains. Consequently, the films exhibited enhanced crystallinity and thermal stability, as revealed by DSC analysis. Moreover, PCO addition positively influenced several film properties, including …

2025 January - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Exhibit 2 “Basement Iswp” 223 N. Alabama St. Butte, Mt 59701 January 2, 2025 Database Residential Identifier: R-00455, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Multiparametric Mri Along With Machine Learning Predicts Prognosis And Treatment Response In Pediatric Low-Grade Glioma, Anahita Fathi Kazerooni, Adam Kraya, Komal Rathi, Meen Chul Kim, Arastoo Vossough, Nastaran Khalili, Ariana Familiar, Deep Gandhi, Neda Khalili, Varun Kesherwani, Debanjan Haldar, Hannah Anderson, Run Jin, Aria Mahtabfar, Sina Bagheri, Yiran Guo, Qi Li, Xiaoyan Huang, Yuankun Zhu, Alex Sickler, Matthew R Lueder, Saksham Phul, Mateusz Koptyra, Phillip Storm, Jeffrey Ware, Yuanquan Song, Christos Davatzikos, Jessica Foster, Sabine Mueller, Michael J Fisher, Adam Resnick, Ali Nabavizadeh

Department of Neurosurgery Faculty Papers

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness and suitability for immunotherapy has the potential to improve clinical management and outcomes. Here, we present a radiogenomic analysis of pLGGs, integrating MRI and RNA sequencing data. We identify three immunologically distinct clusters, with one group characterized by increased immune activity and poorer prognosis, indicating potential benefit from immunotherapies. We develop a radiomic signature that predicts these immune profiles with over 80% accuracy. Furthermore, our clinicoradiomic model predicts progression-free …

Optimizing Electrode Configurations For Eeg Mild Cognitive Impairment Detection, Jiayuan He, Ning Jiang

Faculty, Staff and Student Publications

The Optimal electrode configuration of Electroencephalograms (EEG) systems for mild cognitive impairment (MCI) detection and monitoring in non-clinical settings, i.e. number of electrodes and the positions of the electrodes, remains to be explored. In the current study, we explored the optimization of electrode configuration for MCI detection. We used a 32-channel EEG device to record the data of 21 MCI patients and 20 cognitively normal elderly (NC) undergoing working memory (WM) tasks. Based on the differential value (MCI group vs. NC group) from the Power Spectral Density (PSD) value of each electrode in θ and α frequency band during WM …

An Agent-Based Model Of Microglia And Neuron Interaction: Implications In Neurodegenerative Disease, Cheyenne Ty, Amanda Case, Emmanuel Mezzulo, Abigail Penland, Kamila Larripa

Spora: A Journal of Biomathematics

Whether immune cells protect or harm the brain is an open question depending on context, and their role is implicated in multiple diseases such as Alzheimer's disease, dementia, and other neurological disorders. Microglia, a specific type of immune cell in the central nervous system, play a key role in homeostasis, and genes associated with an elevated risk of Alzheimer's disease correspond with deficiencies in their behavior. We created an agent-based model that incorporates inflammatory signaling, chemotaxis, and phagocytosis of damaged neurons and allows the exploration of crucial pathways in the maintenance of brain health. We specifically investigated pathways related to …

On Solving Differential Equations Describing The Ecology Of Shallow Lakes: A Comparison Of Classical And Modern Computational Methods Through Python, Vruddhi Kapre, Jeffrey R. Anderson, Alessandro Maria Selvitella

Spora: A Journal of Biomathematics

In this exposition paper, we describe some computational methodologies to solve numerically differential equations modeling the shallow lake ecosystem, with particular focus on the dynamics of the phosphorus. We describe in detail Python implementations of classical algorithms, like Runge-Kutta, and more modern approaches, including physics-informed neural networks.

Another Milestone Achieved, Editorial Board

Spora: A Journal of Biomathematics

With due thanks to the Intercollegiate Biomathematics Alliance for their unending support, Spora is offering once again another highly respected platform for collaborative research in mathematics, biology, and related fields. Spora's role in disseminating work especially accessible to students makes it a unique platform to expand the body of knowledge in mathematical biology. Spora welcomes submissions related to Ph.D. dissertations, master's theses, and undergraduate research projects as well as original research.