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Uab Researcher Studying Ways To Reduce Toxicity In Breast Cancer Treatment, Staff

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Uab Neurosurgery Launches Stem Initiative In Elementary Schools, Staff

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Operational Water Forecast Ability Of The Hrrr-Isnobal Combination: An Evaluation To Adapt Into Production Environments, Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, S. Mckenzie Skiles

Geosciences Faculty Publications and Presentations

Operational water-resource forecasters, such as the Colorado Basin River Forecast Center (CBRFC) in the Western United States, currently rely on historical records to calibrate the temperature-index models used for snowmelt runoff predictions. This data dependence is increasingly challenged, with global and regional climatological factors changing the seasonal snowpack dynamics in mountain watersheds. To evaluate and improve the CBRFC modeling options, this work ran the physically based snow energy balance iSnobal model, forced with outputs from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model across 4 years in a Colorado River Basin forecast region. Compared to in situ, remotely sensed, …

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Cnn-Ps: Electroencephalogram Classification Of Brain States Using Hybrid Machine -Deep Learning Approach, Osama Mohsin Abdulaziz, O A. Saltykova

Iraqi Journal for Computer Science and Mathematics

Electroencephalography (EEG) has been used for quite some time as a diagnostic technique in neurology. The goal of this publication is to serve as a resource for researchers interested in applying deep learning methods to EEG data. This paper proposes a unique Hybrid Machine-Deep Learning model that can learn and classify EEG signals on its own. This method allows the model to classify EEG signals of varied sampling frequencies and durations automatically. The proposed model used feature extraction methods from artificial design and performed extensive tests with EEG data collected at varying sample rates to determine how well our suggested …

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Profeatx: A Parallelized Protein Feature Extraction Suite For Machine Learning, David Guevara-Barrientos, Rakesh Kaundal

Computer Science Student Research

Machine learning algorithms have been successfully applied in proteomics, genomics and transcriptomics. and have helped the biological community to answer complex questions. However, most machine learning methods require lots of data, with every data point having the same vector size. The biological sequence data, such as proteins, are amino acid sequences of variable length, which makes it essential to extract a definite number of features from all the proteins for them to be used as input into machine learning models. There are numerous methods to achieve this, but only several tools let researchers encode their proteins using multiple schemes without …

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Exploring The Potential Of Intranasally Administered Naturally Occurring Quercetin Loaded Into Polymeric Nanocapsules As A Novel Platform For The Treatment Of Anxiety, Shady Swidan, Khaled Younis Mahmoud, Nahla Ahmed Elhesaisy, Abdelrahman Rashed, Ebram Mikhael, Mahmoud Fadl, Mahmoud Elsadek, Merna Mohamed, Merna Mostafa, Mohamed Hassan, Omar Halema, Youssef Elnemer

Pharmacy

Anxiety is one of the most prevalent forms of psychopathology that afects millions worldwide. It gained more importance under the pandemic status that resulted in higher anxiety prevalence. Anxiolytic drugs such as benzodiazepines have an unfavorable risk/beneft ratio resulting in a shift toward active ingredients with better safety profle such as the naturally occurring quercetin (QRC). The delivery of QRC is hampered by its low water solubility and low bioavailability. The potential to enhance QRC delivery to the brain utilizing polymeric nanocapsules administered intranasally is investigated in the current study. Polymeric nanocapsules were prepared utilizing the nanoprecipitation technique. The best …

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Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi

Theses and Dissertations

Bound states in the continuum (BICs) are waves that remain in the continuous spectrum of radiating waves that carry energy, however, still localized within the spectrum. BICs, also embedded eigenmodes, exhibit high quality factors that have been observed in optical and acoustic waveguides, photonic structures, and other material systems. Presently, there are limited means to select these BICs in terms of the quality factor and their excitation. In this work, we show that a different type of BIC, Quasi-BICs (Q-BICs), in open resonators can have their quality attuned by introducing embedded scatters. Using microwave cavities and dielectric scatters as an …

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Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki

Theses and Dissertations

The adoption of the internet as a global platform has birthed a significant rise in cyber-attacks of various forms ranging from Trojans, worms, spyware, ransomware, botnet malware, rootkit, etc. In order to tackle the issue of all these forms of malware, there is a need to understand and detect them. There are various methods of detecting malware which include signature, behavioral, and machine learning. Machine learning methods have proven to be the most efficient of all for malware detection. In this thesis, a system that utilizes both the signature and dynamic behavior-based detection techniques, with the added layer of the …

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Classification Of Covid-19 Symptoms Using Multilayerperceptron, Mohd Arfian Ismail, Nurulain Nusrah Mohd Azam, Mohd Saberi Mohamad, Ashraf Osman Ibrahim, Shermina Jeba

Iraqi Journal for Computer Science and Mathematics

The COVID-19 virus had easily affected people worldwide through direct contact. Individualsdiagnosed with positive COVID-19 virus may be affected with many symptoms, such as fever, tiredness, dry cough,difficulty in breathing, sore throat, chest pain, nasal congestion, runny nose, and diarrhea. An individual can alsobe diagnosed with COVID-19 even when he does not have any symptoms or be in contact with an infected person.Data classification was required due to the size of COVID-19 data that will be analyzed for future countermeasuresdetermination. Some problems in data classification occurred due to unorganized data, such as time consumption,human error in complexity of symptom features …

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Modeling And Analyzing Homogeneous Tumor Growth Under Virotherapy, Chayu Yang, Jin Wang

Department of Mathematics: Faculty Publications

We present a mathematical model based on ordinary differential equations to investigate the spatially homogeneous state of tumor growth under virotherapy. The model emphasizes the interaction among the tumor cells, the oncolytic viruses, and the host immune system that generates both innate and adaptive immune responses. We conduct a rigorous equilibrium analysis and derive threshold conditions that determine the growth or decay of the tumor under various scenarios. Numerical simulation results verify our analytical predictions and provide additional insight into the tumor growth dynamics.

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An Intelligent Prairie Dog Optimization (Ipdo) And Deep Auto-Neural Network (Dann) Based Ids For Wsn Security, D Hemanand, P Mohankumar, N Manoj Kumar, S Vaitheki, P Saranya

Iraqi Journal for Computer Science and Mathematics

Wireless sensor networks (WSNs) are targets of intrusion, which seeks to make these networks lesscapable of performing their duties or even completely eradicate them. The Intrusion Detection System (IDS) is highly important for WSN, sinceit aids in the identification and detection of harmful attacks that impair the network's regular functionality. In order to strengthen the security of WSN, several machine learning and deep learning approaches are employed in thetraditional works. However, its main drawbacks are computational burden, system complexity, poornetwork performance outcomes, and high falsealarms. Therefore, the goal of this study is to develop an intelligent IDS framework for significantly …

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Enhancement Methods For Energy Consumption Prediction In Smart House Based On Machine Learning, Musa A. Hameed, Esam T. Yassen, Wesam M. Jasim

Iraqi Journal for Computer Science and Mathematics

Energy efficiency in modern homes has recently become a significant concerndue to the emergence of smart-home infrastructure. Numerous public structures, such as homes, hospitals, schools, and other institutions, use more energy. To come close to meeting the actual energy demand, it is crucial that as much energyis created. The utilization of machine learning has various advantages in improvingthe effectiveness and efficiency of smart-home systems and appliances, including the managementand the reduction of energy use. Additionally, as a key component of the smart-home idea, the potential integration of machine learningbased on some algorithm methodologiesshould be explored as away to improve power …

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Decision-Making Techniques Based On Similarity Measures Ofpossibility Interval Fuzzy Soft Environment, Faisa Al Sharqi, Ashraf Al Quran, Mamika Ujianita Romdhini

Iraqi Journal for Computer Science and Mathematics

The fuzzy set (FS) is a powerful logic designed to measure uncertain information and plays a crucialrole in solving real-life problems such as decision-making. This article is split into two parts. In the first part, wehighlight the notion of possibility for interval-valued fuzzy soft sets (PI-VFSSs) by collecting all interval fuzzy sets(IVFSs) with soft sets (SSs) under possibility properties. A basic set theories, some numerical examples, and someproperties for this hybrid model have been created. Then, in order to test the efficiency of the proposed method insolving some real-life problems, we construct an algorithm using a PIV-FSS. On the other …

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More-Speed: Enhancing Protein Activity Prediction From Dna Sequences, Samahe Al Janabi, Zena Kadhuim

Iraqi Journal for Computer Science and Mathematics

This work presents More-SPEED, a novel model for accurately predicting protein activity while minimizing computational demands. Leveraging optimized structures anddata preprocessing techniques, More-SPEED achieves high accuracy in protein activity prediction. The model incorporates thedata compression three dimension (DC-3D)layer, utilizing the graph mining pattern-fist frequency graph mining (GMP-FFGM)algorithmfor efficient preprocessing of complex Deoxyribonucleic acid (DNA)sequence datasets. Additionally, the deterministic structure network using the natural-inspired optimization algorithm calledWhale Optimization Algorithm(DSN-WOA)structure optimizes parameters of the Biological dynamic long short term memory (BDLSTM)model, reducing processing time and eliminating manual parameter selection. The BDLSTM layer plays a crucial role in matching codons and predicting protein …

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3d Model Visualization Function For Responsive Web Design, Sora Nazhan Kamal, Abdullahi Abdu Ibrahim

Iraqi Journal for Computer Science and Mathematics

Except for critical basic implementations seen in historical records, the abundanceof similar frameworks, platforms, and apps available may be deceptive. Striking a balance between3D certified displaysitsa basically vital tool for today’s quantitative simulation science. Since the seeing is the main sensefor humanities.and incorporated complicated features continues to be difficult. Geometrically precise point clouds and meshes are the result of cutting-edge methodology (computer vision, reverse engineering, and digital photogrammetry), this technology (LiDAR, laser scanners, and unmanned aerial vehicles), and random research approaches.These represent random research approaches a by-product of the procedure.. As the precision, size, and complexity of these things rise, …

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An Age-Dependent Immuno-Epidemiological Model With Distributed Recovery And Death Rates, Samiran Ghosh, Vitaly Volpert, Malay Banerjee

Faculty, Staff and Student Publications

The work is devoted to a new immuno-epidemiological model with distributed recovery and death rates considered as functions of time after the infection onset. Disease transmission rate depends on the intra-subject viral load determined from the immunological submodel. The age-dependent model includes the viral load, recovery and death rates as functions of age considered as a continuous variable. Equations for susceptible, infected, recovered and dead compartments are expressed in terms of the number of newly infected cases. The analysis of the model includes the proof of the existence and uniqueness of solution. Furthermore, it is shown how the model can …

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An Overview Of State Funding For Outdoor Recreation And Tourism In Utah, Jordan W. Smith, Casey Trout

Environment and Society Faculty Publications

The state of Utah supports outdoor recreation and tourism through legislative appropriations, revenue generating mechanisms, taxes, and federal programs that are administered by the state. This review provides an overview of the various programs and funding mechanisms that currently exist within Utah, describes how and to what extent they are funded, outlines how they support outdoor recreation and tourism, and highlights opportunities where the state can strategically refine or build upon them.

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Teaching Routines And Student-Centered Mathematics Instruction: The Essential Role Of Conferring To Understand Student Thinking And Reasoning, Eva Thanheiser, Kathleen Melhuish

Mathematics and Statistics Faculty Publications and Presentations

We compare two lessons with respect to how a teacher centers student mathematical thinking to move instruction forward through enactment of five mathematically productive teaching routines: Conferring To Understand Student Thinking and Reasoning, Structuring Mathematical Student Talk, Working With Selected and Sequenced Student Math Ideas, Working with Public Records of Students’ Mathematical Thinking, and Orchestrating Mathematical Discussion. Findings show that the lessons differ in the enactment of teaching routines, especially Conferring to Understand Student Thinking and Reasoning which resulted in a difference in student-centeredness of the instruction. This difference highlights whose mathematics was being centralized in the classroom and whether …

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Simulations Of The Holocene Climate In Europe Using An Interactive Downscaling Within The Iloveclim Model (Version 1.1), Frank Arthur, Didier M. Roche, Ralph Fyfe, Aurélien Quiquet, Hans Renssen

School of Geography, Earth and Environmental Sciences

Abstract. This study presents the application of an interactive downscaling in Europe using iLOVECLIM (a model of intermediate complexity), increasing its atmospheric resolution from 5.56 to 0.25∘ kilometric. A transient simulation using the appropriate climate forcings for the entire Holocene (11.5–0 ka BP) was done for both the standard version of the model and with an interactive downscaling applied. Our results show that simulations from downscaling present spatial variability that agrees better with proxy-based reconstructions and other climate models as compared to the standard model. The downscaling scheme simulates much higher (by at least a factor of 2) precipitation maxima …

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Audio-Video Synchronization With Arbitrary, Non-Periodic Video Sources, Hao-Wei Lee, Jason Chihhao Lee, Hung-Jen Yu, Hung Ren Liang, James Chen Chao Huang, Jabez Hsu Chung, Eric Huang, Yi-Chin Shih

Defensive Publications Series

The latency between audio and video streams of a device is usually measured using stock test videos. Although the use of stock test videos eases analysis, the test video differs materially from real-world videos, which tend to be far more diverse in content and encoding schemes, resulting in laborious experimental setup and inaccurate synchronization. This disclosure describes techniques to measure the latency between the audio and video streams of a given device using arbitrary, real-world, audio-visual footage (test video). Characteristic video and audio frames and their differences in timestamps (characteristic durations) are identified within the test video. The test video …

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Coping Mechanisms In Graduate School: A Discipline Comparison, Sandra P. Montenegro

The Pegasus Review: UCF Undergraduate Research Journal

The current study aimed to provide an overview of graduate students’ stress and coping mechanisms. Per self-reported questionnaires, participants (N=95) rated their experiences with academic-related stressors, common coping mechanisms, and strain outcomes (somatic symptoms, insomnia, and burnout). This study found that task-related stressors were the most prevalent for graduate schoolwork. More specifically, graduate students in STEM, Arts & Humanities, and Social Sciences rated the amount and difficulty of the tasks (quantitative and qualitative properties of tasks) as the highest stressors in graduate school. The preferred coping strategies across all fields were planning and emotional coping. Additionally, students in STEM reported …

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Hitting Two Birds With One Emissions-Based Maintenance Stone – A Literature Review On Improving Overall Productivity Of Underground Diesel Fleets, Johannes Deon Swanepoel, Jennifer Hines, Vinod Gopaldasani, Brian Davies

Journal of Sustainable Mining

Many industries regard occupational health and safety as a core value and an integral component to maintaining high productivity, and, thus, shareholder value. Diesel fleets’ engine maintenance is instrumental in ensuring affected workplaces meet production requirements while controlling health and safety hazards that these fleets introduce to the workplace. This systematic literature review focuses on production and occupational health and safety advantages associated with the implementation and adherence to an emissions-based maintenance (EBM) program. The literature review was conducted across eight databases relevant to workplace health and engineering. To be eligible for inclusion, the publication had to contain maintenance interventions …

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Research On Vibration-Based Early Diagnostic System For Excavator Motor Bearing Using 1-D Cnn, Dorjsuren Yandagsuren, Tatsuki Kurauchi, Hisatoshi Toriya, Hajime Ikeda, Tsuyoshi Adachi, Youhei Kawamura

Journal of Sustainable Mining

In mining, super-large machines such as rope excavators are used to perform the main mining operations. A rope excavator is equipped with motors that drive mechanisms. Motors are easily damaged as a result of harsh mining conditions. Bearings are important parts in a motor; bearing failure accounts for approximately half of all motor failures. Failure reduces work efficiency and increases maintenance costs. In practice, reactive, preventive, and predictive maintenance are used to minimize failures. Predictive maintenance can prevent failures and is more effective than other maintenance. For effective predictive maintenance, a good diagnosis is required to accurately determine motor-bearing health. …

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Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering, Helen Durand, Jihan Abou Halloun, Kip Nieman, Keshav Kasturi Rangan

Chemical Engineering and Materials Science Faculty Research Publications

Advances in computer science have been a driving force for change in process systems engineering for decades. Faster computers, expanded computing resources, simulation software, and improved optimization algorithms have all changed chemical engineers’ abilities to predict, control, and optimize process systems. Two newer areas relevant to computer science that are impacting process systems engineering are cybersecurity and quantum computing. This work reviews some of our group’s recent work in control-theoretic approaches to control system cybersecurity and touches upon the use of quantum computers, with perspectives on the relationships between process design and control when cybersecurity and quantum technologies are of …

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Dust And Loess As Archives And Agents Of Climate And Climate Change In The Late Paleozoic Earth System, Gerilyn S. Soreghan, Nicholas G. Heavens, Lily Pfeifer, Michael J. Soreghan

School of Earth & Environment Departmental Research

Palaeo-loess and silty aeolian-marine strata are well recognized across the Carboniferous–Permian of equatorial Pangaea. Aeolian-transported dust and loess appear in the Late Devonian in the west, are common by the Late Carboniferous, and predominate across equatorial Pangaea by the Permian. The thickest loess deposits in Earth history – in excess of 1000 m – date from this time, and archive unusually dusty equatorial conditions, especially compared to the dearth of equatorial dust in the Cenozoic. Loess archives a confluence of silt generation, aeolian emission and transport, and ultimate accumulation in dust traps that included ephemerally wet surfaces and epeiric seas. …

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New Types Of Topologies And Neutrosophic Topologies, Florentin Smarandache

Neutrosophic Systems with Applications

In this paper, we recall the six new types of topologies that we introduced in the last years (2019-2022), such as: Refined Neutrosophic Topology, Refined Neutrosophic Crisp Topology, NeutroTopology, AntiTopology, SuperHyperTopology, and Neutrosophic SuperHyperTopology.

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The Utah Statesman, January 9, 2023, Utah State University

The Utah Statesman

Weekly student newspaper of Utah State University in Logan.

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Reverse Social Impact Of Oil Palm Plantation Expansion: A Study Of Three Communities In Jambi, Indonesia, Pahmi Pahmi, Budhi Gunawan, Johan Iskandar, Rini Soemarwoto

Forest and Society

Studies on the social impacts of oil palm development have focused on various communities with distinct characteristics. Due to the rarity of comparative investigations, this study aimed to examine the impact of oil palm plantation expansion on the Suku Anak Dalam, Jambi Malay, and the Javanese transmigrant, the three communities with different socio-economic characteristics. In-depth interviews and observations were conducted to understand the communities' interaction and dependence on forest resources. The study also conducted a household census to assess 67 Malay and 66 Javanese transmigrant families. However, a household census could not be conducted to asses 45 families of …

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Impact Of Chat Gpt On Scientific Research: Opportunities, Risks, Limitations, And Ethical Issues, Omar Ibrahim Obaid, Ahmed Hussein Ali, Mohanad Ghazi Yaseen

Iraqi Journal for Computer Science and Mathematics

The creation of chatbots, such as Generative Pre-trained Transformer(GPT), is a result of recent developments in natural language processing(NLP). Even though Chat GPT has demonstrated enormous promise in a number of areas, including scientific research, this impact is still developing. This paperattempts to investigate the possibilities, threats, limits,and ethical issuessurrounding Chat GPT in scientific research. Theassessment of the literature on Chat GPT and scientific researchis followed by the presentation of case examples that demonstrate the potential advantages and difficulties of Chat GPT usein scientific research. Finally, we conclude by pointing about the ethical issues that need to be tackled before …

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The Sight Of Sublimity, Grace Lukens

Student Scholarship

No abstract provided.

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Full-Text Articles in Entire DC Network

Uab Researcher Studying Ways To Reduce Toxicity In Breast Cancer Treatment, Staff

Browse All News

Uab Neurosurgery Launches Stem Initiative In Elementary Schools, Staff

Browse All News

Operational Water Forecast Ability Of The Hrrr-Isnobal Combination: An Evaluation To Adapt Into Production Environments, Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, S. Mckenzie Skiles

Geosciences Faculty Publications and Presentations

Cnn-Ps: Electroencephalogram Classification Of Brain States Using Hybrid Machine -Deep Learning Approach, Osama Mohsin Abdulaziz, O A. Saltykova

Iraqi Journal for Computer Science and Mathematics

Profeatx: A Parallelized Protein Feature Extraction Suite For Machine Learning, David Guevara-Barrientos, Rakesh Kaundal

Computer Science Student Research

Pharmacy

Using Dielectric Scatters To Selectively Excite Embedded Eigenstates In Cavity Resonators, Olugbenga Joshua Gbidi

Theses and Dissertations

Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki

Theses and Dissertations

Classification Of Covid-19 Symptoms Using Multilayerperceptron, Mohd Arfian Ismail, Nurulain Nusrah Mohd Azam, Mohd Saberi Mohamad, Ashraf Osman Ibrahim, Shermina Jeba

Iraqi Journal for Computer Science and Mathematics

Modeling And Analyzing Homogeneous Tumor Growth Under Virotherapy, Chayu Yang, Jin Wang

Department of Mathematics: Faculty Publications

An Intelligent Prairie Dog Optimization (Ipdo) And Deep Auto-Neural Network (Dann) Based Ids For Wsn Security, D Hemanand, P Mohankumar, N Manoj Kumar, S Vaitheki, P Saranya

Iraqi Journal for Computer Science and Mathematics

Enhancement Methods For Energy Consumption Prediction In Smart House Based On Machine Learning, Musa A. Hameed, Esam T. Yassen, Wesam M. Jasim

Iraqi Journal for Computer Science and Mathematics

Decision-Making Techniques Based On Similarity Measures Ofpossibility Interval Fuzzy Soft Environment, Faisa Al Sharqi, Ashraf Al Quran, Mamika Ujianita Romdhini

Iraqi Journal for Computer Science and Mathematics

More-Speed: Enhancing Protein Activity Prediction From Dna Sequences, Samahe Al Janabi, Zena Kadhuim

Iraqi Journal for Computer Science and Mathematics

3d Model Visualization Function For Responsive Web Design, Sora Nazhan Kamal, Abdullahi Abdu Ibrahim

Iraqi Journal for Computer Science and Mathematics

An Age-Dependent Immuno-Epidemiological Model With Distributed Recovery And Death Rates, Samiran Ghosh, Vitaly Volpert, Malay Banerjee

Faculty, Staff and Student Publications

An Overview Of State Funding For Outdoor Recreation And Tourism In Utah, Jordan W. Smith, Casey Trout

Environment and Society Faculty Publications

Teaching Routines And Student-Centered Mathematics Instruction: The Essential Role Of Conferring To Understand Student Thinking And Reasoning, Eva Thanheiser, Kathleen Melhuish

Mathematics and Statistics Faculty Publications and Presentations

Simulations Of The Holocene Climate In Europe Using An Interactive Downscaling Within The Iloveclim Model (Version 1.1), Frank Arthur, Didier M. Roche, Ralph Fyfe, Aurélien Quiquet, Hans Renssen

School of Geography, Earth and Environmental Sciences

Audio-Video Synchronization With Arbitrary, Non-Periodic Video Sources, Hao-Wei Lee, Jason Chihhao Lee, Hung-Jen Yu, Hung Ren Liang, James Chen Chao Huang, Jabez Hsu Chung, Eric Huang, Yi-Chin Shih

Defensive Publications Series

Coping Mechanisms In Graduate School: A Discipline Comparison, Sandra P. Montenegro

The Pegasus Review: UCF Undergraduate Research Journal

Hitting Two Birds With One Emissions-Based Maintenance Stone – A Literature Review On Improving Overall Productivity Of Underground Diesel Fleets, Johannes Deon Swanepoel, Jennifer Hines, Vinod Gopaldasani, Brian Davies

Journal of Sustainable Mining

Research On Vibration-Based Early Diagnostic System For Excavator Motor Bearing Using 1-D Cnn, Dorjsuren Yandagsuren, Tatsuki Kurauchi, Hisatoshi Toriya, Hajime Ikeda, Tsuyoshi Adachi, Youhei Kawamura

Journal of Sustainable Mining

Perspectives On Design Considerations Inspired By Security And Quantum Technology In Cyberphysical Systems For Process Engineering, Helen Durand, Jihan Abou Halloun, Kip Nieman, Keshav Kasturi Rangan

Chemical Engineering and Materials Science Faculty Research Publications

Dust And Loess As Archives And Agents Of Climate And Climate Change In The Late Paleozoic Earth System, Gerilyn S. Soreghan, Nicholas G. Heavens, Lily Pfeifer, Michael J. Soreghan

School of Earth & Environment Departmental Research

New Types Of Topologies And Neutrosophic Topologies, Florentin Smarandache

Neutrosophic Systems with Applications

The Utah Statesman, January 9, 2023, Utah State University

The Utah Statesman

Reverse Social Impact Of Oil Palm Plantation Expansion: A Study Of Three Communities In Jambi, Indonesia, Pahmi Pahmi, Budhi Gunawan, Johan Iskandar, Rini Soemarwoto

Forest and Society

Impact Of Chat Gpt On Scientific Research: Opportunities, Risks, Limitations, And Ethical Issues, Omar Ibrahim Obaid, Ahmed Hussein Ali, Mohanad Ghazi Yaseen

Iraqi Journal for Computer Science and Mathematics

The Sight Of Sublimity, Grace Lukens

Student Scholarship