Computer Sciences Commons^™

Causal Inference In Psychology And Neuroscience: From Association To Causation, Dehua Liang

Computational and Data Sciences (PhD) Dissertations

In psychology and neuroscience, inferring causality in non-experimental studies is almost taboo, because data in these studies, e.g., survey data and resting-state neuroimaging data, are often contaminated by unmeasured confounders. Psychologists and neuroscientists are often cautious about their results, and reluctant to make false claims about causality in non-experimental studies. Therefore, they adopt less stringent statistical analysis techniques that can only infer associational relations. However, the ambiguity about causality in traditional statistical analysis creates much confusion in interpreting analytical results - some studies make implicit causal claims about their results using words such as “impacts”, “lead to” and “affects”. This …

A Pipeline To Generate Deep Learning Surrogates Of Genome-Scale Metabolic Models, Achilles Rasquinha

School of Computing: Dissertations, Theses, and Student Research

Genome-Scale Metabolic Models (GEMMs) are powerful reconstructions of biological systems that help metabolic engineers understand and predict growth conditions subjected to various environmental factors around the cellular metabolism of an organism in observation, purely in silico. Applications of metabolic engineering range from perturbation analysis and drug-target discovery to predicting growth rates of biotechnologically important metabolites and reaction objectives within dierent single-cell and multi-cellular organism types. GEMMs use mathematical frameworks for quantitative estimations of flux distributions within metabolic networks. The reasons behind why an organism activates, stuns, or fluctuates between alternative pathways for growth and survival, however, remain relatively unknown. GEMMs …

An Effective Deep Learning Approach For The Classification Of Bacteriosis In Peach Leave, Muneer Akbar, Mohib Ullah, Babar Shah, Rafi Ullah Khan, Tariq Hussain, Farman Ali, Fayadh Alenezi, Ikram Syed, Kyung Sup Kwak

All Works

Bacteriosis is one of the most prevalent and deadly infections that affect peach crops globally. Timely detection of Bacteriosis disease is essential for lowering pesticide use and preventing crop loss. It takes time and effort to distinguish and detect Bacteriosis or a short hole in a peach leaf. In this paper, we proposed a novel LightWeight (WLNet) Convolutional Neural Network (CNN) model based on Visual Geometry Group (VGG-19) for detecting and classifying images into Bacteriosis and healthy images. Profound knowledge of the proposed model is utilized to detect Bacteriosis in peach leaf images. First, a dataset is developed which consists …

Farmer Adoption Of Advanced Technology In Agribusiness, Justin W. Belcher

USF Tampa Graduate Theses and Dissertations

Normally, family-owned farms are slow to adopt advanced technologies though these technologies can provide several benefits to the farm and have the potential to increase farm production volumes to help meet future population growth. The goal of this study was to document the factors that influence the adoption decision of advanced technologies by family-owned farms and what strategies can be used to motivate adoption. Case study research was conducted to gather data in a more structured way from family-owned farms typically excluded from past research for the purpose of comparing similarities across similar and dissimilar farms. For generalizing similarities, a …

A Comprehensive Artificial Intelligence Framework For Dental Diagnosis And Charting, Tanjida Kabir, Chun-Teh Lee, Luyao Chen, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

BACKGROUND: The aim of this study was to develop artificial intelligence (AI) guided framework to recognize tooth numbers in panoramic and intraoral radiographs (periapical and bitewing) without prior domain knowledge and arrange the intraoral radiographs into a full mouth series (FMS) arrangement template. This model can be integrated with different diseases diagnosis models, such as periodontitis or caries, to facilitate clinical examinations and diagnoses.

METHODS: The framework utilized image segmentation models to generate the masks of bone area, tooth, and cementoenamel junction (CEJ) lines from intraoral radiographs. These masks were used to detect and extract teeth bounding boxes utilizing several …

Quality Evaluation Of Agricultural And Food Products By Using Image Processing And Soft Computing Paradigm, Narendra Vg

Technical Collection

My research interests revolve around the problem of quality evaluation of Agricultural and Food Products by using Image Processing and Soft Computing Paradigm. Much of my recent work focuses on develop a framework for quality evaluation of Edible Nuts using Computer Vision and Soft Computing Techniques. Also, my interest in developing a framework for defects recognition and classification of Fruits and Vegetables using deep learning methods. My research has also explored many problems related to Blockchain Technology while considering the supply chain management of Agricultural and Food products in between with formers, retailers, and consumers.

1. http://doi.org/10.1109/DELCON54057.2022.9752836
2. http://doi.org/10.1007/978-3-031-07012-9_56
3. http://doi.org/10.1007/978-981-15-8603-3_30
4. http://doi.org/10.1007/978-981-15-8603-3_29
5. http://doi.org/10.1007/978-981-15-8603-3_29

Text Mining Policy Documents To Support Transboundary Integrated Ecosystem Assessment : The Case Of The South Mid-Atlantic Ridge, Debora Cristina Ferrari Ramalho

World Maritime University Dissertations

No abstract provided.

Deep Learning-Based Segmentation And Classification Of Leaf Images For Detection Of Tomato Plant Disease, Muhammad Shoaib, Tariq Hussain, Babar Shah, Ihsan Ullah, Sayyed Mudassar Shah, Farman Ali, Sang Hyun Park

All Works

Plants contribute significantly to the global food supply. Various Plant diseases can result in production losses, which can be avoided by maintaining vigilance. However, manually monitoring plant diseases by agriculture experts and botanists is time-consuming, challenging and error-prone. To reduce the risk of disease severity, machine vision technology (i.e., artificial intelligence) can play a significant role. In the alternative method, the severity of the disease can be diminished through computer technologies and the cooperation of humans. These methods can also eliminate the disadvantages of manual observation. In this work, we proposed a solution to detect tomato plant disease using a …

Gpu Accelerated Estimation Of A Shared Random Effect Joint Model For Dynamic Prediction, Shikun Wang, Zhao Li, Lan Lan, Jieyi Zhao, W Jim Zheng, Liang Li

Faculty, Staff and Student Publications

In longitudinal cohort studies, it is often of interest to predict the risk of a terminal clinical event using longitudinal predictor data among subjects at risk by the time of the prediction. The at-risk population changes over time; so does the association between predictors and the outcome, as well as the accumulating longitudinal predictor history. The dynamic nature of this prediction problem has received increasing interest in the literature, but computation often poses a challenge. The widely used joint model of longitudinal and survival data often comes with intensive computation and excessive model fitting time, due to numerical optimization and …

Small Molecule Modulation Of Microbiota: A Systems Pharmacology Perspective, Qiao Liu, Bohyun Lee, Lei Xie

Publications and Research

Background

Microbes are associated with many human diseases and influence drug efficacy. Small-molecule drugs may revolutionize biomedicine by fine-tuning the microbiota on the basis of individual patient microbiome signatures. However, emerging endeavors in small-molecule microbiome drug discovery continue to follow a conventional “one-drug-one-target-one-disease” process. A systematic pharmacology approach that would suppress multiple interacting pathogenic species in the microbiome, could offer an attractive alternative solution.

Results

We construct a disease-centric signed microbe–microbe interaction network using curated microbe metabolite information and their effects on host. We develop a Signed Random Walk with Restart algorithm for the accurate prediction of effect of microbes …

Computational Study On The Effectiveness Of Flavonoids From Marsilea Crenata C. Presl As Potent Sirt1 Activators And Nfκb Inhibitors, Sri Rahayu, Sasangka Prasetyawan, Sri Widyarti, Mochammad Fitri Atho’Illah, Gatot Ciptadi

Karbala International Journal of Modern Science

Ovarian aging is a natural process in females, and it occurs due to an elevated ROS-induced inflammation caused by oxidative stress. SIRT-1 is a metabolic sensor that tightly regulates oxidative and inflammatory responses. However, this regulative function is antagonized by NFκB. Therefore, the objective of this study was to explore the pathways involved in aging and identify the flavonoid compounds from Marsilea crenata that might be useful as SIRT1 activators and NFκB inhibitors. The screening began with exploring the protein-protein interaction in the experimental process using BioGrid, and the role of the flavonoid was evaluated using STITCH. The interaction between …

Molecular Characterization Of Esbls And Ampc Β-Lactamases In Bacteria Isolated From Currency Notes Circulating In Mosul City, Iraq, Mahmood Zeki Al-Hasso, Shakir Ghazi Gergees, Zahraa Khairialdeen Mohialdeen

Karbala International Journal of Modern Science

The Iraqi currency notes circulating in Mosul city were evaluated for the occurrence of ESBLs and AmpC b-lactamaseproducing bacteria. Four hundred and twenty-two Gram-positive and negative bacterial isolates with different antimicrobial resistance profiles were recovered from 250 samples collected during the period from April to July 2021, among which 150 isolates (35.5%) were multi-drug resistant (MDR). The study found that 16.4% and 14.8% of Gram negative isolates were positive for ESBLs and AmpC phenotypic detection tests, respectively. Interestingly, 6.6% of the isolates were simultaneously positive for both tests. Molecular characterization was carried out using PCR technique to determine the prevalent …

Molecular Docking And Dynamics Simulation Studies To Predict Multiple Medicinal Plants’ Bioactive Compounds Interaction And Its Behavior On The Surface Of Denv-2 E Protein, Arief Hidayatullah, Wira Eka Putra, Muhaimin Rifa’I, Sustiprijatno Sustiprijatno, Diana Widiastuti, Muhammad Fikri Heikal, Hendra Susanto, Wa Ode Salma, Hilal Mulyadi

Karbala International Journal of Modern Science

The envelope protein (E) is a fusion class II protein that is essential for DENV fusion. We use two active compounds derived from commonly used plants in Indonesia: galangin and kaempferide. We ran a docking and 1000 ps molecular dynamic analysis with normal physiological parameters. During the simulation, galangin and kaempferide binding sites fluctuated. But chloroquine has lesser ligand mobility, hence keeping contact with fusion loops, whereas both drugs lose contact with hydrophobic pockets. However, the two active compounds have a more stable ligand configuration. Less than 2 Å alterations were seen in the RMSF simulation of the protein E …

Machine Learning And Scalable Informatics Methods To Predict Disease Status From Multimodal Biomedical Data, Hossein Mohammadian Foroushani

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biological understanding of complex diseases such as stroke and obesity is critical for the advancement of medicine. Further knowledge discovery can provide effective biomarkers to improve disease diagnosis and prognosis, identify driver mutations, predict individual genetic susceptibility for early prevention and effective disease management, and facilitate development of personalized drugs. Stroke is the second leading cause of death and long-term disability in the world. Thus, stroke management is a time-sensitive emergency. The initial hours after stroke onset map the trajectory of subsequent neurologic complications. Cerebral edema develops hours to days after acute ischemic stroke and may result in midline shift …

Development Of The Assessment Of Clinical Prediction Model Transportability (Apt) Checklist, Sean Chonghwan Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Clinical Prediction Models (CPM) have long been used for Clinical Decision Support (CDS) initially based on simple clinical scoring systems, and increasingly based on complex machine learning models relying on large-scale Electronic Health Record (EHR) data. External implementation – or the application of CPMs on sites where it was not originally developed – is valuable as it reduces the need for redundant de novo CPM development, enables CPM usage by low resource organizations, facilitates external validation studies, and encourages collaborative development of CPMs. Further, adoption of externally developed CPMs has been facilitated by ongoing interoperability efforts in standards, policy, and …

Secure Human Action Recognition By Encrypted Neural Network Inference, Miran Kim, Xiaoqian Jiang, Kristin Lauter, Elkhan Ismayilzada, Shayan Shams

Faculty, Staff and Student Publications

Advanced computer vision technology can provide near real-time home monitoring to support "aging in place" by detecting falls and symptoms related to seizures and stroke. Affordable webcams, together with cloud computing services (to run machine learning algorithms), can potentially bring significant social benefits. However, it has not been deployed in practice because of privacy concerns. In this paper, we propose a strategy that uses homomorphic encryption to resolve this dilemma, which guarantees information confidentiality while retaining action detection. Our protocol for secure inference can distinguish falls from activities of daily living with 86.21% sensitivity and 99.14% specificity, with an average …

Tfa Inference: Using Mathematical Modeling Of Gene Expression Data To Infer The Activity Of Transcription Factors, Cynthia Ma

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcription factors (TFs) are a set of proteins that play a key role in the information processing system that enables a cell to respond to changes in internal and external state. By binding near a gene in a cell’s DNA, a TF can influence that gene’s expression level, triggering the appropriate increase or decrease in production levels of proteins that are needed to handle stressors like a change in nutrient availability or damage to the cell’s internal structures. Transcription factor activity (TFA) is a measure of how much effect a TF has on its target genes in a given sample …

Purifications Of Iraqi Petroleum Using Ceramic Ball Nano Cobalt Nickel Ferrite Filter, Huda Jabbar, Enas Muhi, Tahseen Hussien

Karbala International Journal of Modern Science

Iraqi petroleum, especially from the Al-Ahdab, has a big problem resulting from its high percentage of heavy metals. In this paper, heavy metals were reduced or removed from Iraqi petroleum using a Ceramic Ball Nano Cobalt Nickel Ferrite Filter (BCNF), synthesized by combining kaolin and palm frond in a 30% ratio with Co0.8Ni0.2Fe2O4 nanoparticles in a various ratios (5, 10, 15, and 20%). The sol-gel technique prepared Co0.8Ni0.2Fe2O4 nanoparticles. The structure and magnetic properties of the material are described using X-RD, FT-IR, and VSM techniques. In addition, the water ab-sorption ratio and apparent porosity were assessed. The results show that …

Studying The Physical And Biological Characteristics Of Denture Base Resin Pmma Reinforced With Zro2 And Tio2 Nanoparticles, Fatin A. Asim, Entessar H.A. Al-Mosaweb, Wafaa A. Hussain

Karbala International Journal of Modern Science

Polymethyl methacrylate (PMMA) suffers from poor mechanical properties that limit its application in the bio-medical field. In this study, PMMA was reinforced with zirconium dioxide (ZrO2) and titanium dioxide (TiO2) nanopar-ticles; subsequently, the hardness, porosity, biocompatibility, bacterial adhesion, and colonization of the reinforced PMMA with various oxide nanoparticles were characterized. The results of this study indicated that reinforced material inhibits bacterial growth and decreases bacterial adhesion by decreasing porosity and increasing PMMA hardness. Based on the findings, 3 wt% PMMA-ZrO2 and 3 wt% PMMA-ZrO2 -TiO2 composites significantly inhibited bacterial growth and adherence while maintaining hemolysis PT and INR and enhancing …

Skin Lesion Segmentation Based On U-Shaped Network, Muna Khalaf, Ban N. Dhannoon

Karbala International Journal of Modern Science

Skin lesion segmentation is an essential step toward accurate skin lesion diagnosis. The need to automate Skin lesion segmentation on the one hand, and the challenges it faces, on the other hand, have made it a growing area of research and focus. Automation of skin lesion segmentation helps reduce the effort and time needed for diagnosis and treatment and helps make better utilization of available data and shared experiences. The challenges faced by the automation of skin lesion segmentation can be broadly defined by (but not limited to); variations in texture, shape, and size for skin lesions and the low …

C60 Hydrofullerene Induced Autophagy And Ameliorated Gfap In H2o2 Treated Human Malignant Glioblastoma U-373 Cell Line, Aryan M. Faraj, Can A. Agca, Victor S. Nedzvetsky, Artem A. Tykhomyrov

Karbala International Journal of Modern Science

Glioblastoma is one of the most combative astrocytoma that is resistant to chemotherapy and radiotherapy. This resistance makes it very difficult to treat. However, researches have shown that nanoparticles especially C60 hydrofullerene have antioxidant and anticancer activity. The effect of C60 hydrofullerene in cancer has been extensively studied; however, the potential regulation of autophagy and modulation of the Glial Fibrillary Acidic Protein (GFAP) gene has not been addressed in glioblastomas. Glioblastoma U-373 cell was treated with 0.5 µM of C60 hydrofullerene and/or 1 mM of hydrogen peroxide (H2O2) for 24 hours. This study demonstrated that C60 hydrofullerene and H2O2 significantly …

Improving Prediction Of Arabic Fake News Using Fuzzy Logic And Modified Random Forest Model, Tahseen A. Wotaifi, Ban N. Dhannoon

Karbala International Journal of Modern Science

Throughout the last few years, the world is witnessing the so-called age of social media, as there is a complete dependence on these sites for following up on events and activities. The problem is that the misinformation or fake news is always released at the appropriate time, so this false news spreads quickly and takes a very wide resonance. Although several studies are performed to determine English fake news, the identification of Arabic misinformation remains underdeveloped. This study aims to build an improved learning model for detecting fake news in the Arabic language. Unlike previous studies that depended on analyzing …

Synthesized Zinc Nanoparticles Via Pulsed Laser Ablation: Characterization And Antibacterial Activity, Sahar Naji Rashid, Kadhim A. Aadim, Awatif Sabir Jasim, Arshad Mahdi Hamad

Karbala International Journal of Modern Science

The pulsed laser ablation of a metallic target in the liquid (PLAL) is a modern and good method for creating a variety of nanomaterials that have piqued the interest of researchers in the last decade. It is used in this work to prepare zinc na-noparticles and zinc oxide nanoparticles (ZnPNs and ZnO NPs) using Nd: YAG laser with the two wavelengths (532 nm) and (355 nm) using the energies (600 mJ) and (500 mJ) respectively, and the number of the pulse (500, 600, 700, 800, and 900 Pulses); for each wavelength used in this work. The properties of the prepared …

A Successful Elimination Of Indonesian Sars-Cov-2 Variants And Airborne Transmission Prevention By Cold Plasma In Fighting Covid-19 Pandemic: A Preliminary Study, Muhammad Nur, Chairul A. Nidom, Setyarina Indrasari, Arif N. M. Ansori, Mohamad Y. Alamudi, Astria N. Nidom, Sumariyah Sumariyah, Eva Sasmita, Eko Yulianto, Andi W. Kinandana, Anwar Usman, Muhammad K. J. Kusala, Irine Normalina, Reviany V. Nidom

Karbala International Journal of Modern Science

Global infection and mortality rates have soared to millions due to SARS-CoV-2 human-to-human transmission from via droplets which then declared as pandemic. This study examined the created cold plasma equipment (CPE) effectiveness in reducing COVID-19 transmission in a confined space. CPE sucked air using a fan in a test chamber then pushed it into a cold plasma reactor. The results indicated that it was able to terminate all SARS-CoV-2 variants along with bacteria and fungi indoors by keeping it turned on for 30 minutes’ minimum. CPE was proven as safe and effective to hinder virus transmission with the acceptable ozone …

The Distinction Of Logical Decision According To The Model Of The Analysis Of Brain Signals (Eeg), Akeel Abdulkareem Al-Sakaa, Zaid H. Nasralla, Mohsin Hasan Hussein, Saif A. Abd, Hazim Alsaqaa, Kesra Nermend, Anna Borawska

Karbala International Journal of Modern Science

Recently, brain signal patterns have been recruited by researchers in different life activities. Researchers have studied each life activity and how brain signal patterns appear. These patterns could then be generalised and used in different disciplines. In this paper, we study the brain state during decision making in a lottery experiment. An EEG device is used to capture brain signals during an experiment to extract the optimal state for logical decision making. After collecting data, extracting useful information and then processing it, the proposed method is able to identify rational decisions from irrational ones with a success rate of 67%.

Classification Models For 2,4-D Formulations In Damaged Enlist Crops Through The Application Of Ftir Spectroscopy And Machine Learning Algorithms, Benjamin Blackburn

Theses and Dissertations

With new 2,4-Dichlorophenoxyacetic acid (2,4-D) tolerant crops, increases in off-target movement events are expected. New formulations may mitigate these events, but standard lab techniques are ineffective in identifying these 2,4-D formulations. Using Fourier-transform infrared spectroscopy and machine learning algorithms, research was conducted to classify 2,4-D formulations in treated herbicide-tolerant soybeans and cotton and observe the influence of leaf treatment status and collection timing on classification accuracy. Pooled Classification models using k-nearest neighbor classified 2,4-D formulations with over 65% accuracy in cotton and soybean. Tissue collected 14 DAT and 21 DAT for cotton and soybean respectively produced higher accuracies than the …

Green Approach For Iron Oxide Nanoparticles Synthesis: Application In Antimicrobial And Anticancer- An Updated Review, Norul Aini Zakariya, Wan Hafizah W. Jusof, Shahnaz Majeed

Karbala International Journal of Modern Science

Cancer and microbial infections create numerous challenges nowadays. Chemotherapy agents cause severe side effects, while microbial infections, especially multidrug-resistant bacterial strains hard to treat with available antibiotics. Therefore, this review provides an overview of the green synthesis of Iron oxide nanoparticles (IONPs) with their physicochemical properties and mechanism of action . The IONPs causes cytotoxicity and antimicrobial activity by causing oxidative distress through the production of Reactive Oxygen Species (ROS). The IONPs as an anticancer and antimicrobial agent may help to overcome the limitation of conventional treatments but needs toxicity evaluation before usage in clinical applications.

A High Yield Method For Protoplast Isolation And Ease Detection Of Rol B And C Genes In The Hairy Roots Of Cauliflower (Brassica Oleracea L.) Inoculated With Agrobacterium Rhizogenes, Qutaiba Shuaib Al-Nema, Ghazwan Qasim Hasan, Omar Abdulazeez Alhamd

Karbala International Journal of Modern Science

Protoplasts represent a unique experimental system for the circulation and formation of genetically modified plants. Here, protoplasts were isolated from genetically modified hairy root tissues of Brassica oleracea L. induced by the Agrobacterium rhizogenes strain (ATCC13332). The concentration of enzyme solutions utilized for protoplast isolation was 1.5 % Cellulase YC and 0.1 % Pectolyase Y23 in 13% mannitol solution, which resulted in high efficiency of isolation within 8 hours, in which the protoplast yield was 2 × 104 cells ml-1 and the percentage of viability was 72%. Each protoplast has one nucleus with a nucleation of 48%. A polymerase chain …

Tapioca Starch In The Sol-Gel Synthesis Of Cobalt Ferrites With Divalent Cation Substitutions, Anuchit Hunyek, Chitnarong Sirisathitkul, Krit Koyvanich

Karbala International Journal of Modern Science

An aqueous solution of tapioca starch was successfully used as a chelating agent in the sol-gel synthesis of Co0.7Me0.3Fe2O4, where Me denotes Co, Mn, Cu, Ni, or Zn. The hysteresis loops of all sintered ferrites revealed ferrimagnetic properties. The saturation magnetization was reduced in Co0.7Cu0.3Fe2O4 and Co0.7Ni0.3Fe2O4 because of the ion substitutions with smaller magnetic moments. Interestingly, Co0.7Cu0.3Fe2O4 exhibited the highest saturation magnetization and the lowest coercive field. This result demonstrates the value addition of local agricultural products in controlling nanoparticle formation during sol-gel synthesis.

Investigating The Nuclear Properties Of 162-172 Er Isotopes Using Ibm-1, Sef, And Nee, Amal M. Al-Nuaimi, R.B. Alkhayat, Mushtaq Abed Al-Jubbori

Karbala International Journal of Modern Science

The energy levels of the ground state band (GSB), , and γ-bands for 162-172Er isotopes are calculated in this work by adopting the Interacting Boson Model (IBM-1), the Semi-Empirical Formula (SEF) and the New Empirical Equation (NEE). The GSB, , and γ-bands results revealed that IBM-1, SEF, NEE, and the available experimental data are all in agreement with certain variations. The NEE is more compatible with the experimental data than the IBM-1 and SEF calculations. This study demonstrates that the SEF and NEE equations are able to describe the energy spectra of Er isotopes in comparison to IBM-1. The Er …