Computer Sciences Commons^™

Ultrasound-Assisted Dibutyl Phthalate Nanocapsules Preparation And Its Application As Corrosion Inhibition Coatings, Uday Bagale, Ammar Kadi, Irina Potoroko, Vinay Rangari, Minakshi Mahale

Karbala International Journal of Modern Science

The current research employs an encapsulation of dibutyl phthalate (DBP) as a corrosion inhibitor in situ polymerization using a sonochemical method to form nanocapsules. The prepared nanocapsules were characterization by using Malvern particle size, Fouri-er transforms infrared spectroscopy (FTIR), Scanning electron microscope (SEM) and Transmission electron microscope (TEM), and thermal and mechanical test to check particle size, morphology, and stability of nanocapsules. Later prepared DBP nanocapsules were incorporated in standard epoxy coating to check its corrosion inhibition resistance. The results show that nanocapsules are spherical, with an average particle size of 337 nm. Scratch nanocapsules epoxy coating shows improves coating …

Heterogeneous Catalytic Degradation Of Dye By Fenton-Like Oxidation Over A Continuous System Based On Box–Behnken Design And Traditional Batch Experiments, Imad M. Luaibi, Mohammed A. Atiya, Ahmed K. Hassan, Zainab A. Mahmoud

Karbala International Journal of Modern Science

In this study, iron was coupled with copper to form a bimetallic compound through a biosynthetic method, which was then used as a catalyst in the Fenton-like processes for removing direct Blue 15 dye (DB15) from aqueous solution. Characterization techniques were applied on the resultant nanoparticles such as SEM, BET, EDAX, FT-IR, XRD, and zeta potential. Specifically, the rounded and shaped as spherical nanoparticles were found for green synthesized iron/copper nanoparticles (G-Fe/Cu NPs) with the size ranging from 32-59 nm, and the surface area was 4.452 m2/g. The effect of different experimental factors was studied in both batch and continuous …

Optical Measurement And Performance Prediction Of Solar Pv System In Al-Khidhir Zone/Iraq, Faten Sh. Zainulabdeen, Jaber O. Dahloos, Ahmed F. Atwan, Naseer K. Kasim

Karbala International Journal of Modern Science

People have tended for investing the sources of renewable energy, especially solar energy, as they are clean and environmentally friendly sources. The present work aims to invest the measured data of solar irradiance, maximum ambient temperatures and wind speed provided by Al Khidhir Meteorological Station to predict the minimum performance of photovoltaic solar systems (NT-R0E3E-SHARP) for electric power generation. The single diode model is used to calculate the minimum output power produced by solar module and its minimum conversion efficiency based on soalr irradiance, maximum ambient temperatures and wind speed throughout 2020. The results indicate that the annual solar irradiance …

Simulating Polistes Dominulus Nest-Building Heuristics With Deterministic And Markovian Properties, Benjamin Pottinger

Undergraduate Honors Theses

European Paper Wasps (Polistes dominula) are social insects that build round, symmetrical nests. Current models indicate that these wasps develop colonies by following simple heuristics based on nest stimuli. Computer simulations can model wasp behavior to imitate natural nest building. This research investigated various building heuristics through a novel Markov-based simulation. The simulation used a hexagonal grid to build cells based on the building rule supplied to the agent. Nest data was compared with natural data and through visual inspection. Larger nests were found to be less compact for the rules simulated.

Comparative Analyses Of De Novo Transcriptome Assembly Pipelines For Diploid Wheat, Natasha Pavlovikj

School of Computing: Dissertations, Theses, and Student Research

Gene expression and transcriptome analysis are currently one of the main focuses of research for a great number of scientists. However, the assembly of raw sequence data to obtain a draft transcriptome of an organism is a complex multi-stage process usually composed of pre-processing, assembling, and post-processing. Each of these stages includes multiple steps such as data cleaning, error correction and assembly validation. Different combinations of steps, as well as different computational methods for the same step, generate transcriptome assemblies with different accuracy. Thus, using a combination that generates more accurate assemblies is crucial for any novel biological discoveries. Implementing …

Using Ai To Examine Nocturnal Moth Pollination, Conor Moriarty

Biological Sciences Undergraduate Honors Theses

The importance of insect-mediated agriculture cannot be understated especially in the wake of pollinator population declines. Most research of insect-mediated pollination is focused on diurnal pollinators like the honeybee (Apis mellifera). Deepening our understanding of how other pollinators, such as nocturnal pollinators, can benefit agriculture and ecosystems will be very important as honeybee populations decline. I explored nocturnal moth interactions with flowering apple flowers during their pollination season to better understand how these nocturnal pollinators interact with the plants. To accomplish this, I used a University of Arkansas farm area with a dedicated apple orchard. I gathered my raw data …

Mapping Salt-Affected Land In The South-West Of Western Australia Using Satellite Remote Sensing, P A. Caccetta, John A. Simons, S Furby, Nicholas J. Wright, Richard J. George Dr

Natural resources published reports

Dryland salinity is a pervasive form of land degradation that has resulted from the clearing of about 17 M ha of native vegetation and the introduction of predominately cereal and pasture-based farming systems in the South-West of Western Australia. The change in water balance caused by clearing deep rooted endemic woodlands increased recharge and resulted in rising groundwater levels. After a lag period, the regolith began filling and groundwater approached the soil surface, evaporating and depositing stored salts in the rootzone of salt sensitive crops. Groundwater levels also rise and affect areas of remnant native vegetation, streams, wet-lands and rural …

Using Machine Learning To Recognize Chronic Rhinosinusitis, Irene Liu '23

Student Publications & Research

Chronic Rhinosinusitis (CRS) is a nasal disease characterized by the inflammation of the mucosa and paranasal sinuses with a duration of at least 12 consecutive weeks. So, to diagnose CRS, one needs to keep a record of their symptoms for ~12 weeks before they are recommended to get a tomography which will allow physicians to classify them as a patient with CRS or without. This is a timely and costly process; thus, machine learning should be used to speed the process up. Since patients with CRS have more obstructed noses, the sound produced should be different than an individual without …

Volume 13, Payton Davenport, Audrey Lemons, Jacob Shope, Haley Smith, Cassandra Poole, Rachel Cannon, Rachel Boch, Suzanne Stetson

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Roger A. Byrne, Dean

From the Editor Dr. Larissa “Kat” Tracy

From the Designers Rachel English, Rachel Hanson

The Effect of Compliment Type on the Estimated Value of the Compliment by Payton Davenport, Audrey Lemons, and Jacob Shope

The Imperial Japanese Military: A New Identity in the Twentieth Century, 1853–1922 by Haley Smith

Longwood University’s campus: Human-cultivated Soil has Higher Microbial Diversity than Soil Collected from Wild Sites by Cassandra Poole

Reminiscent Modernism: Poetry Magazine’s Modernist Nostalgia for the Past by Rachel Cannon

Challenges Faced by Healthcare Workers During the COVID-19 Pandemic: A Preliminary Study of Age and …

Ubjective Information And Survival In A Simulated Biological System, Tyler S. Barker, Massimiliano Pierobon, Peter J. Thomas

School of Computing: Faculty Publications

Information transmission and storage have gained traction as unifying concepts to characterize biological systems and their chances of survival and evolution at multiple scales. Despite the potential for an information-based mathematical framework to offer new insights into life processes and ways to interact with and control them, the main legacy is that of Shannon’s, where a purely syntactic characterization of information scores systems on the basis of their maximum information efficiency. The latter metrics seem not entirely suitable for biological systems, where transmission and storage of different pieces of information (carrying different semantics) can result in different chances of survival. …

Sibnet: Food Instance Counting And Segmentation, Huu-Thanh. Nguyen, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has recently attracted considerable research attention due to its significance for health risk analysis. In the literature, the majority of research efforts are dedicated to food recognition. Relatively few works are conducted for food counting and segmentation, which are essential for portion size estimation. This paper presents a deep neural network, named SibNet, for simultaneous counting and extraction of food instances from an image. The problem is challenging due to varying size and shape of food as well as arbitrary viewing angle of camera, not to mention that food instances often occlude each other. SibNet is novel for …

Novel Methodology For The Investigation Of Dmrt3a Interneurons In Larval Zebrafish, Alfred Amendolara

Annual Research Symposium

No abstract provided.

Dissecting Mutational Allosteric Effects In Alkaline Phosphatases Associated With Different Hypophosphatasia Phenotypes: An Integrative Computational Investigation, Fei Xiao, Ziyun Zhou, Xingyu Song, Mi Gan, Jie Long, Gennady M. Verkhivker, Guang Hu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the …

Fusionai, A Dna-Sequence-Based Deep Learning Protocol Reduces The False Positives Of Human Fusion Gene Prediction, Pora Kim, Hua Tan, Jiajia Liu, Himansu Kumar, Xiaobo Zhou

Faculty, Staff and Student Publications

Even though there were many tool developments of fusion gene prediction from NGS data, too many false positives are still an issue. Wise use of the genomic features around the fusion gene breakpoints will be helpful to identify reliable fusion genes efficiently. For this aim, we developed FusionAI, a deep learning pipeline predicting human fusion gene breakpoints from DNA sequence. FusionAI is freely available via https://compbio.uth.edu/FusionGDB2/FusionAI. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021b).

Design And Development Of Software With A Graphical User Interface To Display And Convert Multiple Microscopic Histology Images, Sayed Ahmadreza Razian, Majid Jadidi, Alexey Kamenskiy

UNO Student Research and Creative Activity Fair

Histological images are widely used to assess the microscopic anatomy of biological tissues. Recent advancements in image analysis allow the identification of structural features on histological sections that can help advance medical device development, brain and cancer research, drug discovery, vascular mechanobiology, and many other fields. Histological slide scanners create images in SVS and TIFF formats that were designed to archive image blocks and high-resolution textual information. Because these formats were primarily intended for storage, they are often not compatible with conventional image analysis software and require conversion before they can be used in research. We have developed a user-friendly …

Development Of Effectual Substrates For Sers By Nanostructurs-Coated Porous Silicon, Fatima J. Moaen, Hammad R. Humud, Fouad G. Hamzah

Karbala International Journal of Modern Science

The current paper provides an efficient method for making active and effectual substrates used for detecting molecules by improving surface-enhanced Raman scattering (SERS). These substrates were fabricated using nanostructure-coated porous silicon. The nanostructures were prepared through the electrical exploding wire (EEW) technique. The silver nanowires (AgNWs) were coated with a polydopamine (PDA) layer to form an AgNWs@PDA colloidal solution. Then, the Ag wire was electrically exploded in the colloidal solution to form the (AgNWs@PDA@AgNPs) plasmonic nanostructures as a metal-insulator-metal. The effect of the plasmonic nanostructures’ morphologies on the absorptances spectra and SERS activities were studied utilising Rhodamine 6G (Rh6G) dye …

Preparation And Characteristics Study Of Porous Silicon For Vacuum Sensor Application, Noor S. Dawood, Mehdi Q. Zayer, Muslim F. Jawad

Karbala International Journal of Modern Science

Vacuum is a technique that can be employed to measure pressures less than atmosphere (101325 mbar), the vacuum is too important in numerous fields of life. In the present research, the sensor of vacuum has been produced using a porous layer of silicon (Psi). N-type of silicon wafer (Si) has been used for formulating Psi samples utilizing photo-electrochemical etching (PECE) technique. The experimental work was carried out under different etching times (30, 60, and 90 min) while fixing the other parameters, including (24%) Hydrofluoric (HF) acid and (20 mA/cm²) current density. The pore width and depth and porosity …

In-Vitro Evaluation Of High Dosage Of Curcumin Encapsulation In Palm-Oil-In-Water, Nanoemulsion Stabilized With A Sonochemical Approach, Uday Dasharath Bagale Phd, Aram Tsaturov, Irina Potoroko, Shital Potdar, Shirish Sonawane Phd

Karbala International Journal of Modern Science

Curcumin is unstable under different environmental conditions. To increase the bioavailability and stability of curcumin, it is proposed in the present study to encapsulate it in palm oil-in-water nanoemulsions using ultrasound. The present work deals with maximum curcumin encapsulation into oil forms stable nanoemulsion using a food-grade surfactant and examines its antioxidant assay and in-vitro study. The synthesized curcumin nanoemulsion (CuNE) shows particle size in the range of 14.7 ± 3 nm, 95 ± 0.5% encapsulation efficiency, and provides stability against different environmental parameters. Furthermore, in-vitro analysis of high dosage CuNE shows more than 80-90% retention during simulated gastric and …

Seizure Prediction In Epilepsy Patients, Gary Dean Cravens

NSU REACH and IPE Day

Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …

Silver Nanoparticles Synthesized By Nd: Yag Laser Ablation Technique: Characterization And Antibacterial Activity, Sahar Naji Rashid Msc., Kadhim A. Aadim Ph.D., Awatif Sabir Jasim Ph.D.

Karbala International Journal of Modern Science

The pulsed laser ablation in liquid (PLAL) technique can produce high purity nanoparticles, it is a top-down physical method based on the principle of dividing metal ion bulk precursors into metal atoms, this method was used in this work to synthesize silver nanoparticles (AgPNs) by using Nd: YAG laser with two wavelengths (355 nm) and (532 nm) at energies (500 mJ) and (600 mJ) respectively, with the number of pulses (500, 600, 700, 800, and 900 pulses) for each wavelength. The properties of the prepared nanoparticles were investigated by UV-Vis, XRD, SEM with EDX, AFM, and FTIR analysis and then …

Simulation And Improvement Of The Efficiency Of The Cfts Solar Cell Using Scaps-1d, Hardan T. Ghanem Dr., Ayed N. Saleh, Muaamer A. Kamil

Karbala International Journal of Modern Science

A simulation of the AZO/i-ZnO/CdS/CFTS solar cell was carried out using SCAPS software. The results were obtained (Voc=0.55 V, Jsc=6.2 mA/cm², FF=39 %, ɳ=1.35 %). Simulation results were compared with experimental research and we got convergence in the results (Voc=0.56 V, Jsc=6.5 mA/cm², FF=37 %, ɳ=1.37 %). The simulated solar cell is improved by increasing the doping concentration and thickness of the buffer and absorption layers. The efficiency of the solar cell was improved to ɳ=4.29%, fill factor FF=52.92%, open circuit voltage Voc=0.74 V and short circuit current Jsc=10.8 mA/cm²

Molecular Characterization Of Wild Pleurotus Ostreatus (Mw457626) And Evaluation Of Β-Glucans Polysaccharide Activities, Ghazwan Q. Hasan Ph.D., Shimal Y. Abdulhadi Ph.D.

Karbala International Journal of Modern Science

Pleurotus ostreatus is a common cultivated edible mushroom worldwide. The fruiting bodies of P. ostreatus is a rich source of a β-glucans polysaccharide. The current study aimed to investigate the effectiveness of β-glucans as a natural polysaccharide produced by P. ostreatus as an antioxidant, antimicrobial, and anticancer. The molecular identification of P. ostreatus isolate was confirmed by Internal Transcribed Spacer (ITS) sequence. The sequence alignment and phylogenetic evolutionary relationship of studied ITS sequence were performed against some deposited sequences in GenBank. The analysis of high-performance liquid chromatography (HPLC) as well as the result of fourier transform infrared spectroscopy …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Understanding The Decline In Successful Cattle Pregnancies, Andre Tu Nguyen

Research on Capitol Hill

USU junior Andre, a local Loganer, studies computer science and biology.He has been working in an animal science lab. Over time, we have seen a decline in successful dairy cattle pregnancies. This is a huge cause for concern for Utah, with milk sales at an estimated value of $405 million in 2020. Andre’s work has been in studying a certain protein in pregnant cattle; now that he has determined there is a decrease in this protein over the course of the pregnancy, he hopes to see whether that might impact its viability. Andre got involved in research in a high …

Imidazole Derivative Improves Antioxidant Status And Causes Differential Alteration Of Redox-Status In Drosophila Melanogaster, Elizabeth Temidayo Oluwayemi, Oluwakemi Josephine Awakan, Abiodun Omokehinde Eseola, Winfried Plass, Oluyomi Stephen Adeyemi

Karbala International Journal of Modern Science

This study investigated the toxicity of a new imidazole compound, 1-(1,4,5-triphenyl-1H-imidazol-2-yl)-naphthalen-2-ol, through the evaluation of selected oxidative stress markers and antioxidants. Both male and female D. melanogaster (3–5 days old) were fed a diet containing the imidazole derivative (20, 50, and 100 mg IMZ/kg diet) for five days. After cessation of imidazole treatment, half the population of the imidazole-exposed flies was homogenized for biochemical assays, while the other half of the flies was allowed to have a normal diet for an additional five days to see if any induced effect would be resolved. Imidazole derivatives did not significantly …

Glcms Based Multi-Inputs 1d Cnn Deep Learning Neural Network For Covid-19 Texture Feature Extraction And Classification, Elaf Ali Abbood, Tawfiq A. Al-Assadi

Karbala International Journal of Modern Science

Coronavirus disease 2019 epidemic (COVID-19) is an infectious disease that appeared because of the newest version of discovered coronavirus. The advent and rapid spread of this disease over the world necessitated a concerted effort to contain and eradicate it. Computer Tomography (CT) imaging and X-Ray images are considered as one of the important medical examinations used for disease diagnosis. To speed up and confirm the correctness of the medical diagnosis, many artificial intelligence techniques and machine learning methods are proposed. In this paper, a new and efficient proposed system is introduced to extract appropriate and meaningful features for CT scans …

A Convenient Green Method To Synthesize Β-Carotene From Edible Carrot And Nanoparticle Formation, Baker A. Joda, Zena M. Abed Al-Kadhim, Hussian J. Ahmed, Alaa K. H. Al-Khalaf

Karbala International Journal of Modern Science

A simple green chemistry approach was used to synthesize β-carotene from edible carrot without using solvent and heat. In this study, beta-carotene was extracted from edible carrots through a natural extraction method with several physical technical steps. The extracted sample was isolated using high-performance liquid chromatography (HPLC). A β-carotene peak was detected from HPLC with an absorbance maximum (2.135 mAU). The absorption of UV-Visible spectrum indicated that beta-carotene absorbs most strongly between 230-300 and 400-500 nm. The functional groups, namely, C=C (1649 cm^-1), =C-H (900-900 cm^-1) vibrations of antisymmetric deformation of CH₃ groups and CH …

Machine Learning-Based Soft Computing Regression Analysis Approach For Crime Data Prediction, Rabia Musheer Aziz, Aftab Hussain, Prajwal Sharma, Pavan Kumar

Karbala International Journal of Modern Science

The crime rate in India is considerably increasing day by day. Consequently, the data associated with crime is also increasing, opening doors for data-driven approaches to these data to extract insightful knowledge, which can help police and other law enforcement organizations of the country in crime control and prevention. Crime prediction using machine learning algorithms on crime data can predict region-wise crime counts. In this paper, a machine learning-based soft computing regression analysis approach for Indian Crime Data Analysis (ICDA) is proposed. Different regression algorithms, namely, Simple Linear Regression (SLR), Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Support Vector …

Emotion Recognition With Audio, Video, Eeg, And Emg: A Dataset And Baseline Approaches, Jin Chen, Tony Ro, Zhigang Zhu

Publications and Research

This paper describes a new posed multimodal emotional dataset and compares human emotion classification based on four different modalities - audio, video, electromyography (EMG), and electroencephalography (EEG). The results are reported with several baseline approaches using various feature extraction techniques and machine-learning algorithms. First, we collected a dataset from 11 human subjects expressing six basic emotions and one neutral emotion. We then extracted features from each modality using principal component analysis, autoencoder, convolution network, and mel-frequency cepstral coefficient (MFCC), some unique to individual modalities. A number of baseline models have been applied to compare the classification performance in emotion recognition, …

Comparative Evaluation Of Assemblers For Metagenomic Data Analysis, Matheus Pavini Franco Ferreira

Honors Undergraduate Theses

Metagenomics is a cultivation-independent approach for obtaining the genomic composition of microbial communities. Microbial communities are ubiquitous in nature. Microbes which are associated with the human body play important roles in human health and disease. These roles span from protecting us against infections from other bacteria, to being the causes of these diseases. A deeper understanding of these communities and how they function inside our bodies allows for advancements in treatments and preventions for these diseases. Recent developments in metagenomics have been driven by the emergence of Next-Generation Sequencing technologies and Third-Generation Sequencing technologies that have enabled cost-effective DNA sequencing …