Digital Commons Network^™

Dataset On Indoor And Outdoor Pm2.5 Concentrations At Two Residences Using Low-Cost Sensors In The Rio Grande Valley Region Of South Texas, Kabir Bahadur Shah, Sai Deepak Pinakana, Mkhitar A. Hobosyan, Armando Montes, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Fine particulate matter (PM2.5) is one of the criteria air pollutants associated with adverse respiratory and cardiovascular health effects. This dataset contains hourly and daily averaged measurements of PM2.5 concentrations (µg/m3) collected from two residential homes in the Rio Grande Valley (RGV) Region of South Texas, using PurpleAir-II-SD low-cost sensor. In addition, the dataset also includes temperature (ºC) and relative humidity (%) measured by the sensors. The data was collected for one month during the summer season from indoor (kitchen) and outdoor (front yard) environments at two locations: Home-1 in Weslaco City from June 16, 2024, to July 16, 2024, …

Isolation And Molecular Identification Of Pathogens Causing Sea Turtle Egg Fusariosis In Key Nesting Beaches In Costa Rica, Keilor E. Cordero-Umaña, Ruth Hernando-Martínez, María Martínez-Ríos, Jaime Restrepo, Roldán A. Valverde, Laura Martín-Torrijos, Pilar Santidrián Tomillo, Javier Diéguez-Uribeondo

School of Earth, Environmental, & Marine Sciences Faculty Publications

The global rise of fungal pathogens presents an emerging threat to biodiversity, with significant risks to species such as endangered sea turtles. The fungal disease known as sea turtle egg fusariosis (STEF) is associated with high embryo mortality rates and represents a substantial conservation challenge. This disease is caused by two fungal species, namely Fusarium falciforme (Ff) and Fusarium keratoplasticum (Fk), and their identification is essential for guiding future efforts to address potential fungal infections, particularly on important nesting beaches such as those in Costa Rica. In this study, we conducted fungal isolations from sea turtle eggshells …

S-Methyl Cysteine Sulfoxide And Its Potential Role In Human Health: A Scoping Review, Caroline R. Hill, Alex Haoci Liu, Lyn Mccahon, Liezhou Zhong, Armaghan Shafaei, Lois Balmer, Joshua R. Lewis, Jonathan M. Hodgson, Lauren C. Blekkenhorst

Research outputs 2022 to 2026

Higher intakes of cruciferous and allium vegetables are associated with a lower risk of cardiometabolic-related outcomes in observational studies. Whilst acknowledging the many healthy compounds within these vegetables, animal studies indicate that some of these beneficial effects may be partially mediated by S-methyl cysteine sulfoxide (SMCSO), a sulfur-rich, non-protein, amino acid found almost exclusively within cruciferous and alliums. This scoping review explores evidence for SMCSO, its potential roles in human health and possible mechanistic action. After systematically searching several databases (EMBASE, MEDLINE, SCOPUS, CINAHL Plus Full Text, Agricultural Science), we identified 21 original research articles meeting our inclusion criteria. These …

Sources Of Underwater Noise, Christine Erbe, Alec J. Duncan, Alexander Gavrilov, Montserrat Landero, Robert D. Mccauley, Iain Parnum, Evgeny Sidenko, Chandra Salgado-Kent, Evgeny Sidenko

Research outputs 2022 to 2026

The marine soundscape, whether in coastal areas or the deepest ocean, in the tropics or at the poles, contains a myriad of sounds. Sounds may be grouped by their origin into geophony (e.g., wind, precipitation, waves, earthquakes, volcanoes, and ice), biophony (e.g., invertebrates, fishes, and marine mammals), and anthropophony (e.g., port construction, mineral and hydrocarbon exploration and production, renewable energy installation, and shipping). This chapter gives a brief overview of the geophony and biophony, and then focuses on the anthropophony. The sounds of boats and ships of various types, marine seismic surveys, drilling, dredging, pile driving, windfarms, geotechnical site investigations, …

Modelling The Impacts Of Recreational Catch-And-Release Variability On Fish Stock Dynamics, Brett Crisafulli

Theses: Doctorates and Masters

Recreational fisheries often lack sufficient data for robust stock assessments, and post-release mortality (PRM) of discarded fish, particularly demersal species, poses a significant threat to sustainability. Because demersal fish often experience higher PRM (often due to barotrauma and stress), the substantial global interest in their recreational fisheries (e.g., Australia, Gulf of Mexico, Western Baltic Sea) raises conservation concerns. This study employs three distinct modelling approaches, applied to four reef-dwelling demersal species, to support effective recreational fisheries management by addressing data uncertainty, unintended consequences of management changes, and PRM effects. Specifically, this thesis (1) evaluates variability in average weights of recreationally-caught …

A Pollutant’S Tale: An Interactive Talk On The Chemistry Of The Earth’S Climate And Its Response To Pollutants, Timothy G. Harrison, Michael T. Davies-Coleman, Alison C. Rivett, M. Anwar H. Khan, Joyce D. Sewry, Magdalena Wajrak, Nicholas M. Barker, Jonny Furze, Sophie D. Franklin, Linda Sellou, Naomi K.R. Shallcross, Dudley E. Shallcross

Research outputs 2022 to 2026

A Pollutant’s Tale and its primary school version, Gases in the Air, are two talks that have been developed and modified over the last ca. 18 years, that provide audiences from approximately 4-90 years old with the background to the composition of the Earth’s lower atmosphere, the Earth’s climate, and the impact of air pollution. In this article, we describe the content of the talks and provide videos of each experiment individually as well as a recorded performance of both talks to an empty auditorium. In this article, we discuss ways that the talk can be further developed and its …

Protocol For An Integrative Meta-Analysis Of The Application Of Machine Learning Algorithms In The Prediction Of Chronic Disease Risks And Outcomes, Ebenezer Afrifa-Yamoah, Emmanuel Peprah-Yamoah, Enoch Odame Anto, Victor Opoku-Yamoah, Eric Adua

Research outputs 2022 to 2026

Background: Precise risk prediction of chronic diseases is essential for effective preventive care and management. Machine learning (ML) is a promising avenue to enhance chronic disease risk prediction; however, a comprehensive assessment of ML performance across various chronic diseases, populations, and health settings is needed. Methods: This meta-analysis aims to synthesize evidence on the performance of ML techniques for predicting the risks and outcomes of chronic diseases. A literature search was conducted through PubMed, Web of Science, Scopus, Science Direct, Medline, and Embase. Studies applying ML techniques to predict chronic disease risks or outcomes and reporting performance metrics were included. …

Ecological Resources Of A Heavily Modified And Utilised Temperate Coastal Embayment: Cockburn Sound, Peter J. Mitchell, Daniel E. Yeoh, Kurt N. Krispyn, Claire N. Greenwell, Sorcha Cronin-O’Reilly, Delphine B.H. Chabanne, Glenn A. Hyndes, Danielle Johnston, David V. Fairclough, Claire Wellington, Alan Cottingham, Gary Jackson, Jeffrey V. Norriss, Matias Braccini, Hector Lozano-Montes, Chandra P. Salgado Kent, Erin Clitheroe, Alissa Tate, James W. Penn, Marion Massam, Neil R. Loneragan, James R. Tweedley

Research outputs 2022 to 2026

Coastal environments and their associated biota provide numerous environmental, economic and societal services. Cockburn Sound, a temperate embayment on the lower west coast of Western Australia, is immensely important for the State and adjacent capital city of Perth. However, urbanisation and associated terrestrial and marine development has the potential to threaten this important ecosystem. This study collated published and unpublished data to review the current state of the ecological resources of Cockburn Sound and describe how they have changed over the past century. Post-WWII, the embayment began undergoing pronounced anthropogenic changes that limited oceanic water exchange, increased nutrient load, modified …

Survey: A Study On Image Encryption Using Dna In Bioinformatics, Rana M. Zaki, Zaed S. Mahdi, Matheel E. Abdulmunim

Journal of Soft Computing and Computer Applications

One area of study between computer science and biology is bioinformatics, which deals with methods for collecting, processing, storing, and evaluating biological data. Sequences of RiboNucleic Acid (RNA), DeoxyriboNucleic Acid (DNA), and proteins make up biological data, which has a wide range of uses in domains such as feature extraction, data segmentation, data security, and more. In cryptography, DNA sequences are used as data carriers, enhancing the unique properties of biomolecules. This approach involves using DNA sequences to enhance the security of confidential data that must be transmitted over networks or stored securely. Several DNA-based security techniques have been developed, …

Enhancing Image Classification Using A Convolutional Neural Network Model, Zena M. Saadi, Ahmed T. Sadiq, Omar Z. Akif, Marwa M. Eid

Journal of Soft Computing and Computer Applications

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as …

Learning Paradigms For Rhythm Detection And Generation Using Mathematical Models, Biophysical And Artificial Neural Networks, Prianka Bose

Dissertations

Humans possess an inherent ability to recognize evenly-spaced rhythms, known as isochronous rhythms, owing to the brain's predisposition to entrain to external auditory stimuli with regular temporal intervals. The central focus of this research is to understand how the brain learns and retains rhythmic time intervals in the context of music. This dissertation studies rhythm detection and generation through mathematical models, biophysical networks, and artificial neural networks, addressing both isochronous and non-isochronous patterns.

A primary focus of the thesis is on isochronous rhythms. In particular, given a perturbation to an isochronous rhythm such as a tempo change or phase shift …

Machine Learning Methods For Pattern Recognition Analysis Of Genomic And Molecular Data, Kuang Du

Dissertations

While immune therapies achieve remarkable success in treating various cancers, only a subset of patients achieves a durable clinical response, and many exhibit innate or acquired resistance. Precision medicine aims to tailor treatments to individual patients based on specific biological markers, ensuring that each patient receives the therapy most likely to be effective. Predictive biomarkers and gene signatures offer potential for more personalized treatment strategies by identifying patients likely to benefit. Recent studies suggest that gene signatures, comprising sets of genes, hold predictive value for certain clinical variables. Typically derived from biological expert knowledge, these signatures demonstrate substantial predictive potential, …

Crowd-Sourced Learning For Computer Graphics Applications, Yunhao Zhang

Dissertations

Computer Graphics (CG) revolves around virtual content creation using computational methods, spanning applications from games to visual effects. Typically, the creation of CG content is led by expert practitioners who guide computational algorithms towards satisfactory results. Thus, creating CG content often requires manual iterations encompassing algorithm design, parameter tuning, and aesthetic feedback. This work investigates how to leverage crowd-sourcing to streamline such creation processes, focusing on animation and simulation. In animation, a novel crowd-sourcing framework is proposed for combat animation, enabling users to analyze motion similarities, and retrieve matching motions using novel crowd-sourced motion features. Such features enable quantifying previously …

Developing A Roadmap For Green Port In Timor-Leste, Emanuel Da Silva Maia

World Maritime University Dissertations

No abstract provided.

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 …

Development Of Conceptual Scaffolding-Assisted Formative Assessment For Enhancing Understanding Of Temperature And Heat, Ana Lailatul Fitriyah, Sentot Kusairi, Markus Diantoro

Jurnal Pendidikan Sains

This research aims to develop formative assessment media assisted by conceptual scaffolding to improve students’ understanding of temperature and heat, test its validity and practicality, and gauge student responses. Utilizing the ADDIE model, the research follows five stages: Analysis, Design, Development, Implementation, and Evaluation. In the Analysis stage, a literature review was conducted to identify critical components, including formative assessment, conceptual scaffolding, concept mastery, and previous research. The Design stage involved identifying users, defining competencies and indicators, creating a storyboard, integrating assessment components, and determining mastery levels. During the Development stage, the assessment media were developed into a functional product. …

Composite Volume Learning Media Based On Augmented Reality To Enhance Students’ Visual-Spatial Intelligence, Ria Kurniawati, Susiswo Susiswo, Syamsul Hadi

Jurnal Pendidikan Sains

Augmented Reality (AR) technology, a three-dimensional visual tool that integrates virtual objects or environments into real-world displays in real time (Azuma et al., 2001), is particularly useful for grasping complex concepts such as the composite volume of solids, which often confuses students when they need to decompose solids into their individual components. While previous research has predominantly focused on the introduction of solids, spatial nets, and the volume of singular shapes, this study aims to develop composite volume learning media based on AR to enhance students’ visual-spatial intelligence in a valid, practical, and effective manner, aligning with their concrete operational …

Students’ Concept Maps Profile On Environmental Pollution Material During The Covid-19 Pandemic, Sunarni Sunarni, Sri Widoretno, Puguh Karyanto, Bowo Sugiharto, Sri Dwiastuti, Chandra Adi Prabowo

Jurnal Pendidikan Sains

The study investigates the performance of students in constructing Concept Maps (CM) related to environmental pollution material during the COVID-19 pandemic. The data reveals that the overall achievement in CM construction was suboptimal, with no component reaching more than half of its maximum potential. The highest achievement was recorded in the valid relationship component, which attained 9.75% of its maximum possible score. This was followed by the hierarchy component, achieving 7.34%, and the branching component at 3.42%. The pattern component ranked fourth with 1.31%, closely followed by the example component at 1.30%. The lowest performance was observed in the crosslink …

Analysis Of Students’ Problem-Solving Skills In Newton’S Law With 5e Learning Cycle, Nidya Desyana, Sutopo Sutopo, Nandang Mufti

Jurnal Pendidikan Sains

The aim of this study is to identify students’ problem-solving skills in Newton’s laws through the implementation of the 5E learning cycle in the classroom. A pre-experimental design with a one-group pretest-posttest approach was employed. Data on problem-solving skills were collected from students’ pre-test and post-test responses to two essay questions. The indicator with the highest percentage of problem-solving skills was useful description (83% of students), while the indicator with the lowest percentage was specific application of physics (33% of students). Due to the non-normal distribution of the data, the Wilcoxon test was utilized. The results indicated a significant difference …

Design Of Motivational-Realistic-Pancasila Learning In Mathematics, Marup Marup, Suradi Tahmir, Ahmad Talib, Nurzatulshima Kamaruddin

Jurnal Pendidikan Sains

Learning mathematics in class greatly influences students' learning success both in terms of knowledge and attitudes. In carrying out learning, a learning design is needed that can foster student motivation so that they provide learning outcomes to the learning objectives. Motivational-Realistic-Pancasila learning design is considered to be an alternative solution. Morela is a design that combines motivational, realistic indicators and Pancasila values. The teaching of mathematics in the classroom significantly influences students' academic success, both in terms of knowledge and attitude. To effectively carry out the teaching process, a well-designed instructional approach is necessary to foster students' motivation to achieve …

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 …

Mathematical Modelling And Analysis For The Co-Infection Of Viral And Bacterial Diseases: A Systematic Review Protocol, Timothy Kiprono Yano, Ebenezer Afrifa-Yamoah, Julia Collins, Ute Mueller, Steven Richardson

Research outputs 2022 to 2026

Introduction Breaking the chain of transmission of an infectious disease pathogen is a major public health priority. The challenges of understanding, describing and predicting the transmission dynamics of infections have led to a wide range of mathematical, statistical and biological research problems. Advances in diagnostic laboratory procedures with the ability to test multiple pathogens simultaneously mean that co-infections are increasingly being detected, yet little is known about the impact of co-infections in shaping the course of an infection, infectivity, and pathogen replication rate. This is particularly true of the apparent synergistic effects of viral and bacterial co-infections, which present the …

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- …

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 …

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 …

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 …

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, …

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 …

Coal Gasification Through Microbial Degradation In A Low-Pressure Co2 And H2 Environment: An Experimental Study, Jian Kuo, Fu Xuehai, Liu Mingjie, Liu Jian, Li Jin, Ru Zhongliang, Ji Xiaofeng, Wang Qiang

Coal Geology & Exploration

Objective and Methods This study aims to investigate the characteristics of CO₂ biomethanation and coal gasification through microbial degradation in a low-pressure environment. With low-rank bituminous coals (R_max = 0.67%) as fermentable substrates, this study conducted a 96-day gas production experiment through microbial fermentation in a low-pressure CO₂ and H₂ environment. Using techniques including gas chromatography, 16S rRNA gene sequencing, and low-temperature liquid nitrogen adsorption, this study delved into the intrinsic variation patterns of biogenic gas production, microbial communities, and coal structures. Results and Conclusions The results indicate that compared to conventional fermentation, the injection …