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Articles 751 - 780 of 294561
Full-Text Articles in Entire DC Network
A Transformer-Based Approach With Data Augmentation For Multilabel Emotional Context Detection, Mohsin Hasan Hussein, Marem H. Abdulabas, Azha Talal Mohammed Ali, Homam Aziz Ghazi
A Transformer-Based Approach With Data Augmentation For Multilabel Emotional Context Detection, Mohsin Hasan Hussein, Marem H. Abdulabas, Azha Talal Mohammed Ali, Homam Aziz Ghazi
Al-Bahir
Emotion identification in texts is becoming increasingly difficult because of the wide variety of ways emotions are represented. This study uses a fine-tuned Robustly Optimized Bidirectional Encoder Representations from Transformers Approach
(RoBERTa) to offer a Transformer-based model for identifying multilabel emotional context in textual data. To balance emotion categories and enhance the model's capacity for generalization, data augmentation is applied on two different datasets: Semantic Evaluation and Cross-lingual Emotion Dataset (SemEval and XED) English corpus. This stage is considered one of the most important steps in preprocessing as it greatly helps to improve the results. The RoBERTa model was then …
From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik
From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik
Communications of the IIMA
Advances in machine learning for healthcare are abundant, yet most validated models remain confined to research notebooks and never reach secure, usable clinical software. This paper addresses that deployment gap by presenting a unified, security-hardened software platform that operationalizes two complementary streams of doctoral research inside a single, role-based hospital information system. The first stream contributes a clinical-prediction capability: an ultra-hybrid ensemble that couples a quantum-inspired feature transformation, particle-swarm feature selection, and calibrated soft voting for cancer-outcome prediction (96.41% accuracy, AUC-ROC 0.983 on TCGA-BRCA), survival stratification, multi-cancer generalization, and pharmacogenomic drug-response classification (89.31% mean accuracy across 25 compounds). The second …
A Fundamental Study Of Fatty Acid Ionic Liquids And Their Effects On Biomolecules, Achismita Dutta
A Fundamental Study Of Fatty Acid Ionic Liquids And Their Effects On Biomolecules, Achismita Dutta
Theses and Dissertations
Fatty acid ionic liquids (FAILs) are a class of ionic liquids (ILs) with relatively low toxicity and potential applications in biological systems. This study examined the interactions of tetramethylguanidinium decanoate, tetramethylguanidinium octanoate, choline decanoate, and choline octanoate with lipid membranes, proteins, and nucleic acids. Membrane leakage experiments using model lipid vesicles showed that decanoate-based FAILs produced greater membrane permeabilization than octanoate-based analogues, consistent with their higher membrane permeability. These effects were stronger for the ILs than for decanoate alone and occurred below the critical micelle concentration (CMC), suggesting that micelle formation may not be essential for membrane disruption. The ability …
A Hybrid Rule-Based And Large Language Model Framework For Extracting Acronym–Definition Pairs From Scientific Literature, Petro Skrypnyk
A Hybrid Rule-Based And Large Language Model Framework For Extracting Acronym–Definition Pairs From Scientific Literature, Petro Skrypnyk
Theses and Dissertations
Authors of scientific papers rely heavily on acronyms and often use them without defining them, making the literature harder to read and index. This thesis develops and evaluates a hybrid rule-based and large language model (LLM) framework that extracts acronym–definition pairs from scientific PDF documents. It extends an earlier Rowan University system that combined a regular-expression parser with a single LLM on 200 papers. That system showed that neither the parser nor the LLM alone is sufficient for accurate extraction of the pairs. The framework is a fully automated pipeline from PDF input to scored results. It compares four LLM …
Re: Request For Change To The Butte Priority Soils Operable Unit Clark Tailings Consolidated Waste Management Area Site Investigation Quality Assurance Project Plan Revision 0 (2026 Update), Josh Bryson
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Cultivating Collaboration In Biomolviz: Key Attributes For Building A Stem Educator Community Of Practice, Pamela S. Mertz, Charmita Burch, Roderico Acevedo, Josh T. Beckham, Didem Vardar-Ulu, Kristin M. Fox, Lauren A. Genova, Rachel M. Mitton-Fry, Swati Agrawal, Daniel R. Dries, Kristen Procko
Cultivating Collaboration In Biomolviz: Key Attributes For Building A Stem Educator Community Of Practice, Pamela S. Mertz, Charmita Burch, Roderico Acevedo, Josh T. Beckham, Didem Vardar-Ulu, Kristin M. Fox, Lauren A. Genova, Rachel M. Mitton-Fry, Swati Agrawal, Daniel R. Dries, Kristen Procko
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
BioMolViz is an educational community of practice (CoP) focused on creating resources to improve biomolecular visual literacy instruction and assessment. The community of life science instructors developed in three phases, beginning with a small Core Team that emerged from a conference session and established the domain of interest for the CoP. In-person workshops, supported by short-term funding, drove the initial expansion of the community and the development of shared activities in Phase 2. This CoP was sustained through intentional choices about how members interact, collaborate, and share work. As the community matured in Phase 3, it was supported by longer-term …
Gc-Ms Profiling And Antibacterial Activity Of Cold-Macerated Garlic Extracts Against Multidrug-Resistant Uropathogens, Fatima A. Khalaf, Saeed A. Fayadh
Gc-Ms Profiling And Antibacterial Activity Of Cold-Macerated Garlic Extracts Against Multidrug-Resistant Uropathogens, Fatima A. Khalaf, Saeed A. Fayadh
Karbala International Journal of Modern Science
The growing number of cases of multidrug-resistant (MDR) urinary tract infections has made the clinical management of urinary tract diseases a significant challenge; therefore, the need for effective adjunctive therapies cannot be overemphasized. This study evaluated the bioactive components and antibacterial efficacy of cold-macerated garlic extracts obtained using distilled water, 70% ethanol and hexane solvents against antimicrobial-resistant urinary isolates. Out of 250 urine samples that were analyzed, 124 (49.6%) showed significant microbial growth, with Escherichia coli being the most frequently isolated organism. The results of the phytochemical screening and Gas Chromatography-Mass Spectrometry (GC-MS) analysis showed that the ethanolic extract had …
A Guided Size Exclusion Chromatography Demonstration For Teaching Polymer Separation And Characterization, Daniel Rivero, Nicole Paccha, Amrita Sarkar
A Guided Size Exclusion Chromatography Demonstration For Teaching Polymer Separation And Characterization, Daniel Rivero, Nicole Paccha, Amrita Sarkar
Department of Chemistry and Biochemistry Faculty Scholarship and Creative Works
Practical experience with modern analytical instruments is an essential component of undergraduate chemistry education, yet access to advanced instruments varies widely among institutions because of differences in available resources. Although size exclusion chromatography (SEC) is extensively used in polymer characterization in both academia and industry, undergraduate students at Montclair State University previously had limited opportunities to gain hands-on experience to this technique. To address this need, a demonstration using a multidetector-equipped Malvern Panalytical OMNISEC system was developed and incorporated into a second-year organic chemistry laboratory course during the 2025–2026 academic year. This activity engaged more than 300 undergraduate students representing …
Hyperlattice-Valued And Superhyperlattice-Valued Uncertain Sets With Decision Applications, Takaaki Fujita, Ajoy Kanti Das, Sankar Prasad Mondal, Arif Mehmood, Arkan Ghaib
Hyperlattice-Valued And Superhyperlattice-Valued Uncertain Sets With Decision Applications, Takaaki Fujita, Ajoy Kanti Das, Sankar Prasad Mondal, Arif Mehmood, Arkan Ghaib
Neutrosophic Systems with Applications
Fuzzy set theory enriches classical sets by assigning to each element a graded membership in [0,1], thereby capturing partial inclusion and uncertainty. The notion of an Uncertain Set further abstracts this idea by allowing membership to take values in a general degree-domain, providing a unified language that subsumes fuzzy, intuitionistic fuzzy, neutrosophic, plithogenic, and related models. On the algebraic side, a hyperlattice replaces one lattice operation by a multivalued hyperoperation, enabling the representation of ambiguous or non-deterministic combinations, while a superhyperlattice iterates this structure through powerset lifting to obtain higher-order layers of interaction. Motivated by these developments, we introduce HyperLattice-valued …
The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban
The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban
Faculty Publications
Nondestructive evaluation (NDE) methods are powerful tools for detecting and characterizing flaws in structural components, but their reliability must be evaluated before they can be used in critical applications. For more than 50 years, probabilistic and statistical methods have been used effectively to estimate reliability by describing an NDE system’s Probability of Detection (POD) for flaws of realistic sizes. The POD methods used by the USAF and NASA, like Hit/Miss, Signal-Response (â vs. a), and Point Estimate method (PEM, a.k.a. 29/29) have evolved, alongside newer approaches like Limited Sample POD (LS-POD) method, and Model Assisted Probability of Detection …
A Neutrosophic Event-Graph Legal Ai System For Detecting Contradictions In Witness Testimonies Under Egyptian Law, Shimaa Abdelghany Attalla, Alaa Elmor, Nada Hesham, Abduallah Gamal
A Neutrosophic Event-Graph Legal Ai System For Detecting Contradictions In Witness Testimonies Under Egyptian Law, Shimaa Abdelghany Attalla, Alaa Elmor, Nada Hesham, Abduallah Gamal
Neutrosophic Systems with Applications
Witness testimony is an important source of evidence in criminal proceedings, but it may contain contradictions, incomplete details, or conflicts with other case-file materials. This paper proposes a neutrosophic event-graph legal AI framework for detecting materially contested claims in witness testimonies under the Egyptian criminal-procedure context. The framework converts testimony and related records into structured claims containing actor, action, object, time, location, source, and modality. These claims are then connected through an event graph and evaluated using neutrosophic components of support, indeterminacy, and opposition. The system produces source-grounded legal-review alerts when a claim has sufficient opposition from other claims or …
An Interval-Valued Spherical Fuzzy Critic–Waspas Framework For Prioritizing Healthcare Delivery Models To Enhance Patient Satisfaction Under Uncertainty, Mariam Hamada, Ahmed Samy, Mohamed M. Abdelhafeez, Shrouk El-Amir
An Interval-Valued Spherical Fuzzy Critic–Waspas Framework For Prioritizing Healthcare Delivery Models To Enhance Patient Satisfaction Under Uncertainty, Mariam Hamada, Ahmed Samy, Mohamed M. Abdelhafeez, Shrouk El-Amir
Neutrosophic Systems with Applications
Selecting an appropriate healthcare delivery model is important for improving the quality of healthcare services and enhancing patient satisfaction. However, this decision is complex because it involves several criteria, uncertainty, and different expert opinions. To handle this uncertainty, this paper uses Interval-Valued Spherical Fuzzy Sets (IVSFSs), which allow experts to express their evaluations more flexibly. This paper proposes an integrated interval-valued spherical fuzzy CRITIC-WASPAS approach to prioritize healthcare delivery models. The CRITIC method is used to determine the objective weights of the evaluation criteria, while the WASPAS method is used to rank the healthcare delivery models. Expert evaluations are expressed …
20 Years Of Neutrosophic Statistics: A Bibliometric Analysis, Hammad Khalid, Arshad Hameed
20 Years Of Neutrosophic Statistics: A Bibliometric Analysis, Hammad Khalid, Arshad Hameed
Neutrosophic Systems with Applications
Florentin Smarandache introduced neutrosophic statistics (NS), a formalism for representing uncertainty and indeterminacy in observations, parameters and statistics in an extension to classical and interval statistics. Although widespread in various contexts, such as statistical quality control, hypothesis testing, medical diagnosis, and decision science, and increasingly used and developed, the scientific evolution and conceptual framework of the science of decision making remain largely unexamined. To fill this gap, the present study has been conducted with a comprehensive bibliometric analysis of NS research articles published between 2003 to 2025 from Scopus which has been conducted following the SPAR-4-SLR protocol. In all, 501 …
A Unified Framework For Neutrosophic Estimation Using Fractional Power, Exponential, And Logarithmic Functions With Bivariate Auxiliary Information, Anchal Yadav, Anuj Yadav
A Unified Framework For Neutrosophic Estimation Using Fractional Power, Exponential, And Logarithmic Functions With Bivariate Auxiliary Information, Anchal Yadav, Anuj Yadav
Neutrosophic Systems with Applications
This study develops a generalized neutrosophic ratio-type estimator for estimating the population mean by incorporating information from two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The proposed methodology extends the conventional single-auxiliary-variable approach by jointly incorporating bivariate auxiliary information within the neutrosophic framework, thereby accounting for uncertainty, indeterminacy, and inconsistency in the available information. The bias and mean squared error of the proposed estimator are derived using first-order approximations, and the corresponding efficiency conditions are established through theoretical comparisons with existing neutrosophic estimators. The performance of the proposed estimator is further examined using a real medical dataset represented …
Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2025 Butte Reclamation Evaluation System (Bres) Site Specific Corrective Action Plans For Quadrant 2 (Dated July 22, 2026), Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Approval Letter For The Draft Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur-53 – South Of Surprise Dump, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Re: Approval Letter For The Draft Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur 51 – Area Near Bres No.50 –Zelia And Mountain Con Mine, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Approval Letter For The Draft Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites Field Sampling And Investigation Plan – Ur-52 Area West Of Bres No. 133 – Dexter Mill, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Monitoring System In The Georeactor Area During The Underground Coal Gasification Process, Aleksandra Tokarz, Jacek Grabowski, Krzysztof Korczak
Monitoring System In The Georeactor Area During The Underground Coal Gasification Process, Aleksandra Tokarz, Jacek Grabowski, Krzysztof Korczak
Journal of Sustainable Mining
Safety control of the underground coal gasification (UCG) process involves ensuring that the process runs smoothly, monitoring changes occurring on the surface and in the rock mass, and counteracting the negative environmental impact of the process. The article presents the application of a monitoring system implemented in Poland, both in pilot tests conducted in shallow coal seams at the Barbara Experimental Mine and in deep coal seams at the Wieczorek mine, where a full-scale gasification process was tested. The analysis of the monitoring results carried out during the gasification experiment in an operating mine allowed for the identification of key …
Fast Computation And Model Order Reduction Of The Friction Stir Welding Process With Pod-Deim, Joshua Kay, Zilong Song
Fast Computation And Model Order Reduction Of The Friction Stir Welding Process With Pod-Deim, Joshua Kay, Zilong Song
Mathematics and Statistics Student Research and Class Projects
Friction stir welding (FSW) is a solid-state manufacturing process widely used in joining aluminum and other metal workpieces. The FSW process can be modeled by a coupled system of non-Newtonian Navier–Stokes and heat-transfer equations. However, solving this non-linear system with high accuracy requires significant computational power. This work refines the system by introducing corrected coefficients and new treatments for boundary conditions near the tool. Then, model order reduction, including the Proper Orthogonal Decomposition (POD) and Discrete Empirical Interpolation Method (DEIM), is applied to efficiently solve the FSW system in a low-dimensional space. To enhance accuracy and effectiveness, two novel treatments …
Using Approximations Of Practice To Support Calculus Instructors’ Enactment Of Equitable Active Learning Teaching Practices, Kaitlyn Stephens Serbin, Karina Uhing
Using Approximations Of Practice To Support Calculus Instructors’ Enactment Of Equitable Active Learning Teaching Practices, Kaitlyn Stephens Serbin, Karina Uhing
School of Mathematical & Statistical Sciences Faculty Publications
We implemented a semester-long professional development workshop series to help Calculus I and II instructors implement active learning and equitable teaching practices. The workshops actively engaged instructors in approximations of practice (Grossman et al., 2009) in which they learned to enact various teaching practices like designing tasks; eliciting, noticing, and responding to evidence of student thinking; orchestrating class discussions; fostering inclusive social norms; and equitably managing student participation. After they participated in the workshops, we interviewed the instructors about their decisions to implement the teaching practices from the approximations of practice in their teaching. We analyzed the instructors’ resources, orientations, …
Fastest-Warming States And Cities In The Mountain West, 2025, Maisoon Faris, Kahlen Coss, Kevin Yang, Caitlin J. Saladino, William E. Brown Jr.
Fastest-Warming States And Cities In The Mountain West, 2025, Maisoon Faris, Kahlen Coss, Kevin Yang, Caitlin J. Saladino, William E. Brown Jr.
Environment
This fact sheet presents data published by Climate Central on the change in average annual temperatures for the five Mountain West states of Arizona, Colorado, Nevada, New Mexico, and Utah and 15 Mountain West cities from 1970 to 2025. City-level data are derived from Applied Climate Information System (ACIS) operated by National Oceanic and Atmospheric Administration (NOAA), state-level data are derived from NOAA’s National Centers for Environmental Information (NCEI).
Re: Approval Letter For The Draft Final Butte Priority Soils Operable Unit Insufficiently Reclaimed Sites Temporary Best Management Practices Work Plan: Bres No. 16 – Curry And Bres No. 50 – Zelia, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Using Graphic Novels In The Teaching And Learning Of Mathematics And Physics, Jason Ho, David Klanderman, Sarah Klanderman, James Turner
Using Graphic Novels In The Teaching And Learning Of Mathematics And Physics, Jason Ho, David Klanderman, Sarah Klanderman, James Turner
University Faculty Publications and Creative Works
Are you looking for innovative teaching strategies for geometry or other mathematics and physics courses? In this article, we o!er a discussion of several graphic novels and their potential for successful teaching and learning at the high school and university levels. We describe how engaging stories, combined with mathematical and scientific meaning found in both text and image, can help to excite students, enrich learning, and explain mathematical concepts. We report on recent data collected from multiple mathematics and physics classes that extend prior research on the use of graphic novels to teach English Language Arts (Boerman-Cornell and Kim, 2020) …
Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2024 Surface Water, Groundwater, And Soil Characterization, Woodard & Curran
Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2024 Surface Water, Groundwater, And Soil Characterization, Woodard & Curran
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Development Of A Chip-Scale Optical Gyroscope With Weak Measurement Amplification Readout, Kagan Yanik, Meiting Song, Yuhan Mei, Jaime Cardenas, Andrew N. Jordan
Development Of A Chip-Scale Optical Gyroscope With Weak Measurement Amplification Readout, Kagan Yanik, Meiting Song, Yuhan Mei, Jaime Cardenas, Andrew N. Jordan
Mathematics, Physics, and Computer Science Faculty Articles and Research
We establish the theoretical framework and investigate the fundamental limits for an integrated optical chip design containing a rotation sensing ring resonator coupled to an inverse weak value amplified Sagnac interferometer that amplifies the signal with phase information. We achieve, for conservative parameter choices, a minimum detectable angular rotation rate of ∼0.1 °/hr and an Allan deviation of∼0.08 °/hr assuming shot noise limited performance. For matched detected optical power, our design can improve the signal-to-noise ratio, reduce the minimum detectable angular rotation rate, and Allan deviation by more than ten times compared to an ideal standard Sagnac interferometer with balanced …
Approval Letter For The Butte Priority Soils Operable Unit Field Sampling Plan And Investigation Plan: Ur-41 - Montana Street And Interstate-90, Molly Roby
Silver Bow Creek/Butte Area Superfund Site
No abstract provided.
Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos
Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos
Undergraduate Scholarship and Creative Works
Physics-informed neural networks solve the Helmholtz equation without labeled data, but a low residual alone does not confirm that a solution preserves the physical distinction a downstream task depends on. We trained a four-layer SIREN with physics-based residuals, a Sommerfeld condition, Adam, and L-BFGS, modeling a Gaussian source and a plane wave scattering from a small dielectric inclusion. Fine-tuning from four base models produced 600 complex fields spanning omega = 4 to 20. A compact CNN, three ResNet-18 variants, and a frozen OpenCLIP encoder classified these fields under five random seeds. The CNN achieved (95.65 +/- 0.77)% accuracy, outperforming OpenCLIP …
2026 September 3 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University
2026 September 3 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University
Tennessee Climate Office Weekly Drought Summaries
No abstract provided.
Learning-Based Entanglement Generation For Quantum Routing, Tasdiqul Islam, Rasman Mubtasim Swargo, Md Arifuzzaman
Learning-Based Entanglement Generation For Quantum Routing, Tasdiqul Islam, Rasman Mubtasim Swargo, Md Arifuzzaman
Computer Science Faculty Research & Creative Works
Entanglement generation in long-distance quantum networks is challenging because resources are limited and entanglement swapping is probabilistic. To maximize the rate of successful requests, existing quantum routing algorithms often rely on computationally expensive methods such as Integer Linear Programming (ILP) to determine which links to entangle and use for end-To-end entanglement generation. However, these approaches fail to meet the latency requirements of real-world quantum networks. In this study, we propose a Reinforcement Learning (RL)-based model that determines which links to entangle in each time slot, replacing the slow ILP-based link-selection phase used in prior algorithms. The proposed Deep Q-learning model …